[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"similar-Ly0n--awesome-robotic-tooling":3,"tool-Ly0n--awesome-robotic-tooling":61},[4,18,26,36,44,53],{"id":5,"name":6,"github_repo":7,"description_zh":8,"stars":9,"difficulty_score":10,"last_commit_at":11,"category_tags":12,"status":17},4358,"openclaw","openclaw\u002Fopenclaw","OpenClaw 是一款专为个人打造的本地化 AI 助手，旨在让你在自己的设备上拥有完全可控的智能伙伴。它打破了传统 AI 助手局限于特定网页或应用的束缚，能够直接接入你日常使用的各类通讯渠道，包括微信、WhatsApp、Telegram、Discord、iMessage 等数十种平台。无论你在哪个聊天软件中发送消息，OpenClaw 都能即时响应，甚至支持在 macOS、iOS 和 Android 设备上进行语音交互，并提供实时的画布渲染功能供你操控。\n\n这款工具主要解决了用户对数据隐私、响应速度以及“始终在线”体验的需求。通过将 AI 部署在本地，用户无需依赖云端服务即可享受快速、私密的智能辅助，真正实现了“你的数据，你做主”。其独特的技术亮点在于强大的网关架构，将控制平面与核心助手分离，确保跨平台通信的流畅性与扩展性。\n\nOpenClaw 非常适合希望构建个性化工作流的技术爱好者、开发者，以及注重隐私保护且不愿被单一生态绑定的普通用户。只要具备基础的终端操作能力（支持 macOS、Linux 及 Windows WSL2），即可通过简单的命令行引导完成部署。如果你渴望拥有一个懂你",349277,3,"2026-04-06T06:32:30",[13,14,15,16],"Agent","开发框架","图像","数据工具","ready",{"id":19,"name":20,"github_repo":21,"description_zh":22,"stars":23,"difficulty_score":10,"last_commit_at":24,"category_tags":25,"status":17},3808,"stable-diffusion-webui","AUTOMATIC1111\u002Fstable-diffusion-webui","stable-diffusion-webui 是一个基于 Gradio 构建的网页版操作界面，旨在让用户能够轻松地在本地运行和使用强大的 Stable Diffusion 图像生成模型。它解决了原始模型依赖命令行、操作门槛高且功能分散的痛点，将复杂的 AI 绘图流程整合进一个直观易用的图形化平台。\n\n无论是希望快速上手的普通创作者、需要精细控制画面细节的设计师，还是想要深入探索模型潜力的开发者与研究人员，都能从中获益。其核心亮点在于极高的功能丰富度：不仅支持文生图、图生图、局部重绘（Inpainting）和外绘（Outpainting）等基础模式，还独创了注意力机制调整、提示词矩阵、负向提示词以及“高清修复”等高级功能。此外，它内置了 GFPGAN 和 CodeFormer 等人脸修复工具，支持多种神经网络放大算法，并允许用户通过插件系统无限扩展能力。即使是显存有限的设备，stable-diffusion-webui 也提供了相应的优化选项，让高质量的 AI 艺术创作变得触手可及。",162132,"2026-04-05T11:01:52",[14,15,13],{"id":27,"name":28,"github_repo":29,"description_zh":30,"stars":31,"difficulty_score":32,"last_commit_at":33,"category_tags":34,"status":17},1381,"everything-claude-code","affaan-m\u002Feverything-claude-code","everything-claude-code 是一套专为 AI 编程助手（如 Claude Code、Codex、Cursor 等）打造的高性能优化系统。它不仅仅是一组配置文件，而是一个经过长期实战打磨的完整框架，旨在解决 AI 代理在实际开发中面临的效率低下、记忆丢失、安全隐患及缺乏持续学习能力等核心痛点。\n\n通过引入技能模块化、直觉增强、记忆持久化机制以及内置的安全扫描功能，everything-claude-code 能显著提升 AI 在复杂任务中的表现，帮助开发者构建更稳定、更智能的生产级 AI 代理。其独特的“研究优先”开发理念和针对 Token 消耗的优化策略，使得模型响应更快、成本更低，同时有效防御潜在的攻击向量。\n\n这套工具特别适合软件开发者、AI 研究人员以及希望深度定制 AI 工作流的技术团队使用。无论您是在构建大型代码库，还是需要 AI 协助进行安全审计与自动化测试，everything-claude-code 都能提供强大的底层支持。作为一个曾荣获 Anthropic 黑客大奖的开源项目，它融合了多语言支持与丰富的实战钩子（hooks），让 AI 真正成长为懂上",149489,2,"2026-04-10T11:32:46",[14,13,35],"语言模型",{"id":37,"name":38,"github_repo":39,"description_zh":40,"stars":41,"difficulty_score":32,"last_commit_at":42,"category_tags":43,"status":17},2271,"ComfyUI","Comfy-Org\u002FComfyUI","ComfyUI 是一款功能强大且高度模块化的视觉 AI 引擎，专为设计和执行复杂的 Stable Diffusion 图像生成流程而打造。它摒弃了传统的代码编写模式，采用直观的节点式流程图界面，让用户通过连接不同的功能模块即可构建个性化的生成管线。\n\n这一设计巧妙解决了高级 AI 绘图工作流配置复杂、灵活性不足的痛点。用户无需具备编程背景，也能自由组合模型、调整参数并实时预览效果，轻松实现从基础文生图到多步骤高清修复等各类复杂任务。ComfyUI 拥有极佳的兼容性，不仅支持 Windows、macOS 和 Linux 全平台，还广泛适配 NVIDIA、AMD、Intel 及苹果 Silicon 等多种硬件架构，并率先支持 SDXL、Flux、SD3 等前沿模型。\n\n无论是希望深入探索算法潜力的研究人员和开发者，还是追求极致创作自由度的设计师与资深 AI 绘画爱好者，ComfyUI 都能提供强大的支持。其独特的模块化架构允许社区不断扩展新功能，使其成为当前最灵活、生态最丰富的开源扩散模型工具之一，帮助用户将创意高效转化为现实。",108322,"2026-04-10T11:39:34",[14,15,13],{"id":45,"name":46,"github_repo":47,"description_zh":48,"stars":49,"difficulty_score":32,"last_commit_at":50,"category_tags":51,"status":17},6121,"gemini-cli","google-gemini\u002Fgemini-cli","gemini-cli 是一款由谷歌推出的开源 AI 命令行工具，它将强大的 Gemini 大模型能力直接集成到用户的终端环境中。对于习惯在命令行工作的开发者而言，它提供了一条从输入提示词到获取模型响应的最短路径，无需切换窗口即可享受智能辅助。\n\n这款工具主要解决了开发过程中频繁上下文切换的痛点，让用户能在熟悉的终端界面内直接完成代码理解、生成、调试以及自动化运维任务。无论是查询大型代码库、根据草图生成应用，还是执行复杂的 Git 操作，gemini-cli 都能通过自然语言指令高效处理。\n\n它特别适合广大软件工程师、DevOps 人员及技术研究人员使用。其核心亮点包括支持高达 100 万 token 的超长上下文窗口，具备出色的逻辑推理能力；内置 Google 搜索、文件操作及 Shell 命令执行等实用工具；更独特的是，它支持 MCP（模型上下文协议），允许用户灵活扩展自定义集成，连接如图像生成等外部能力。此外，个人谷歌账号即可享受免费的额度支持，且项目基于 Apache 2.0 协议完全开源，是提升终端工作效率的理想助手。",100752,"2026-04-10T01:20:03",[52,13,15,14],"插件",{"id":54,"name":55,"github_repo":56,"description_zh":57,"stars":58,"difficulty_score":32,"last_commit_at":59,"category_tags":60,"status":17},4721,"markitdown","microsoft\u002Fmarkitdown","MarkItDown 是一款由微软 AutoGen 团队打造的轻量级 Python 工具，专为将各类文件高效转换为 Markdown 格式而设计。它支持 PDF、Word、Excel、PPT、图片（含 OCR）、音频（含语音转录）、HTML 乃至 YouTube 链接等多种格式的解析，能够精准提取文档中的标题、列表、表格和链接等关键结构信息。\n\n在人工智能应用日益普及的今天，大语言模型（LLM）虽擅长处理文本，却难以直接读取复杂的二进制办公文档。MarkItDown 恰好解决了这一痛点，它将非结构化或半结构化的文件转化为模型“原生理解”且 Token 效率极高的 Markdown 格式，成为连接本地文件与 AI 分析 pipeline 的理想桥梁。此外，它还提供了 MCP（模型上下文协议）服务器，可无缝集成到 Claude Desktop 等 LLM 应用中。\n\n这款工具特别适合开发者、数据科学家及 AI 研究人员使用，尤其是那些需要构建文档检索增强生成（RAG）系统、进行批量文本分析或希望让 AI 助手直接“阅读”本地文件的用户。虽然生成的内容也具备一定可读性，但其核心优势在于为机器",93400,"2026-04-06T19:52:38",[52,14],{"id":62,"github_repo":63,"name":64,"description_en":65,"description_zh":66,"ai_summary_zh":66,"readme_en":67,"readme_zh":68,"quickstart_zh":69,"use_case_zh":70,"hero_image_url":71,"owner_login":72,"owner_name":73,"owner_avatar_url":74,"owner_bio":75,"owner_company":76,"owner_location":77,"owner_email":78,"owner_twitter":79,"owner_website":80,"owner_url":81,"languages":79,"stars":82,"forks":83,"last_commit_at":84,"license":85,"difficulty_score":86,"env_os":87,"env_gpu":88,"env_ram":88,"env_deps":89,"category_tags":95,"github_topics":97,"view_count":32,"oss_zip_url":79,"oss_zip_packed_at":79,"status":17,"created_at":118,"updated_at":119,"faqs":120,"releases":121},6279,"Ly0n\u002Fawesome-robotic-tooling","awesome-robotic-tooling","Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.","awesome-robotic-tooling 是一份精心整理的开源工具清单，旨在为使用 C++ 和 Python 进行专业机器人开发的团队提供全方位支持。它特别涵盖了 ROS（机器人操作系统）、自动驾驶及航空航天领域的关键软件与硬件资源。\n\n在机器人开发中，开发者常面临“重复造轮子”的困境，难以快速找到经过验证的高质量工具。awesome-robotic-tooling 通过系统化的分类，解决了这一痛点。它将工具细分为通信协调、架构设计、仿真模拟、传感器处理（如雷达、激光点云）、定位建图、规划控制以及底层操作系统等数十个类别，帮助开发者迅速定位所需资源，从代码构建、调试测试到数据可视化，覆盖研发全生命周期。\n\n这份清单非常适合机器人软件工程师、算法研究人员以及系统架构师使用。无论是初创团队搭建技术栈，还是资深专家寻找特定领域的优化方案，都能从中获益。其独特亮点在于不仅罗列工具，更强调“专业性”与“生态互补”，将学术界的前沿算法与工业界的稳定框架相结合，并鼓励社区共同维护以确保内容的时效性与质量。对于希望提升开发效率、避免从零开始的机器人从业者而言，这是一份极具价值的导航图。","# Awesome Robotic Tooling [![Awesome](https:\u002F\u002Fawesome.re\u002Fbadge.svg)](https:\u002F\u002Fawesome.re)\n\n**A curated list of tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace**\n\n> To stop reinventing the wheel you need to know about the wheel. This list is an attempt to show the variety of open and free tools in software and hardware development, which are useful in professional robotic development.\n\nYour contribution is necessary to keep this list alive, increase the quality and to expand it. You can read more about it's origin and how you can participate in the [contribution guide](CONTRIBUTING.md) and related [blog post](https:\u002F\u002Frosindustrial.org\u002Fnews\u002F2020\u002F5\u002F11\u002Fguest-article-on-the-story-of-the-autonomous-logistics). All new project entries will have a tweet from [protontypes](https:\u002F\u002Ftwitter.com\u002Fprotontypes).\n\n\u003C!--lint ignore double-link-->\n[\u003Cimg src=\"https:\u002F\u002Fi.imgur.com\u002FqI1Jfyl.gif\" align=\"right\" width=\"60%\" \u002F>](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fxpp)\n\u003C!--lint ignore double-link-->\n[![](https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fprotontypes?style=social)](https:\u002F\u002Ftwitter.com\u002Fintent\u002Ffollow?screen_name=protontypes) [![Join the chat at https:\u002F\u002Fgitter.im\u002Fprotontypes\u002Fcommunity](https:\u002F\u002Fbadges.gitter.im\u002Fprotontypes\u002Fcommunity.svg)](https:\u002F\u002Fgitter.im\u002Fprotontypes\u002Fcommunity?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n\n\u003C!--toc-->\n\n## Contents\n\n* [Communication and Coordination](#communication-and-coordination)\n* [Documentation and Presentation](#documentation-and-presentation)\n* [Requirements and Safety](#requirements-and-safety)\n* [Architecture and Design](#architecture-and-design)\n* [Frameworks and Stacks](#frameworks-and-stacks)\n* [Development Environment](#development-environment)\n  * [Code and Run](#code-and-run)\n  * [Template](#template)\n  * [Build and Deploy](#build-and-deploy)\n  * [Unit and Integration Test](#unit-and-integration-test)\n  * [Lint and Format](#lint-and-format)\n  * [Debugging and Tracing](#debugging-and-tracing)\n  * [Version Control](#version-control)\n* [Simulation](#simulation)\n* [Electronics and Mechanics](#electronics-and-mechanics)\n* [Sensor Processing](#sensor-processing)\n  * [Calibration and Transformation](#calibration-and-transformation)\n  * [Perception Pipeline](#perception-pipeline)\n  * [Machine Learning](#machine-learning)\n  * [Parallel Processing](#parallel-processing)\n  * [Image Processing](#image-processing)\n  * [Radar Processing](#radar-processing)\n  * [Lidar and Point Cloud Processing](#lidar-and-point-cloud-processing)\n* [Localization and State Estimation](#localization-and-state-estimation)\n* [Simultaneous Localization and Mapping](#simultaneous-localization-and-mapping)\n  * [Lidar](#lidar)\n  * [Visual](#visual)\n  * [Vector Map](#vector-map)\n* [Prediction](#prediction)\n* [Behavior and Decision](#behavior-and-decision)\n* [Planning and Control](#planning-and-control)\n* [User Interaction](#user-interaction)\n  * [Graphical User Interface](#graphical-user-interface)\n  * [Acoustic User Interface](#acoustic-user-interface)\n  * [Command Line Interface](#command-line-interface)\n* [Data Visualization and Mission Control](#data-visualization-and-mission-control)\n  * [Annotation](#annotation)\n  * [Point Cloud](#point-cloud)\n  * [RViz](#rviz)\n* [Operation System](#operation-system)\n  * [Monitoring](#monitoring)\n  * [Database and Record](#database-and-record)\n  * [Network Distributed File System](#network-distributed-file-system)\n  * [Server Infrastructure and High Performance Computing](#server-infrastructure-and-high-performance-computing)\n  * [Embedded Operation System](#embedded-operation-system)\n  * [Real-Time Kernel](#real-time-kernel)\n* [Network and Middleware](#network-and-middleware)\n  * [Ethernet and Wireless Networking](#ethernet-and-wireless-networking)\n  * [Controller Area Network](#controller-area-network)\n  * [Sensor and Acuator Interfaces](#sensor-and-acuator-interfaces)\n* [Security](#security)\n* [Datasets](#datasets)\n\n\u003C!--toc_end-->\n\n## Communication and Coordination\n* [Agile Development](https:\u002F\u002Fagilemanifesto.org\u002F) - Manifesto for Agile Software Development.\n* [Gitflow](https:\u002F\u002Fgithub.com\u002Fnvie\u002Fgitflow) - Makes parallel development very easy, by isolating new development from finished work.\n* [DeepL](https:\u002F\u002Fgithub.com\u002Fuinput\u002Fdeeplator) - An online translator that outperforms Google, Microsoft and Facebook.\n* [Taiga](https:\u002F\u002Fgithub.com\u002Fbenhutchins\u002Fdocker-taiga) - Agile Projectmanagment Tool.\n* [Kanboard](https:\u002F\u002Fgithub.com\u002Fkanboard\u002Fkanboard) - Minimalistic Kanban Board.\n* [kanban](https:\u002F\u002Fgitlab.com\u002Fleanlabsio\u002Fkanban) - Free, open source, self-hosted, Kanban board for GitLab issues.\n* [Gitlab](https:\u002F\u002Fgithub.com\u002Fsameersbn\u002Fdocker-gitlab) - Simple Selfhosted Gitlab Server with Docker.\n* [Gogs](https:\u002F\u002Fgithub.com\u002Fgogs\u002Fgogs) - Build a simple, stable and extensible self-hosted Git service that can be setup in the most painless way.\n* [Wekan](https:\u002F\u002Fgithub.com\u002Fwekan\u002Fwekan) - Meteor based Kanban Board.\n* [JIRA API](https:\u002F\u002Fgithub.com\u002Fpycontribs\u002Fjira) - Python Library for REST API of Jira.\n* [Taiga API](https:\u002F\u002Fgithub.com\u002Fnephila\u002Fpython-taiga) - Python Library for REST API of Taiga.\n* [Chronos-Timetracker](https:\u002F\u002Fgithub.com\u002Fweb-pal\u002Fchronos-timetracker) - Desktop client for JIRA. Track time, upload worklogs without a hassle.\n* [Grge](https:\u002F\u002Fgitlab.com\u002FApexAI\u002Fgrge) - Grge is a daemon and command line utility augmenting GitLab.\n* [gitlab-triage](https:\u002F\u002Fgitlab.com\u002Fgitlab-org\u002Fgitlab-triage) - Gitlab's issues and merge requests triage, automated.\n* [Helpy](https:\u002F\u002Fgithub.com\u002Fhelpyio\u002Fhelpy) - A modern, open source helpdesk customer support application.\n* [ONLYOFFICE](https:\u002F\u002Fgithub.com\u002FONLYOFFICE\u002FCommunityServer) -  A free open source collaborative system developed to manage documents, projects, customer relationship and email correspondence, all in one place.\n* [discourse](https:\u002F\u002Fgithub.com\u002Fdiscourse\u002Fdiscourse) - A platform for community discussion. Free, open, simple.\n* [Gerrit](https:\u002F\u002Fgerrit.googlesource.com\u002Fgerrit\u002F) - A code review and project management tool for Git based projects.\n* [jitsi-meet](https:\u002F\u002Fgithub.com\u002Fjitsi\u002Fjitsi-meet) - Secure, Simple and Scalable Video Conferences that you use as a standalone app or embed in your web application.\n* [mattermost](https:\u002F\u002Fgithub.com\u002Fmattermost\u002Fmattermost-server) - An open source, private cloud, Slack-alternative.\n* [openproject](https:\u002F\u002Fgithub.com\u002Fopf\u002Fopenproject) - The leading open source project management software.\n* [leantime](https:\u002F\u002Fgithub.com\u002FLeantime\u002Fleantime) - Leantime is a lean project management system for innovators.\n* [gitter](https:\u002F\u002Fgitlab.com\u002Fgitlab-org\u002Fgitter\u002Fwebapp) - Gitter is a chat and networking platform that helps to manage, grow and connect communities through messaging, content and discovery.\n\n## Documentation and Presentation\n* [Typora](https:\u002F\u002Ftypora.io\u002F) - A Minimalist Markdown Editor.\n* [Markor](https:\u002F\u002Fgithub.com\u002Fgsantner\u002Fmarkor) - A Simple Markdown Editor for your Android Device.\n* [Pandoc](https:\u002F\u002Fgithub.com\u002Fjgm\u002Fpandoc) - Universal markup converter.\n* [Yaspeller](https:\u002F\u002Fgithub.com\u002Fhcodes\u002Fyaspeller) - Command line tool for spell checking.\n* [ReadtheDocs](https:\u002F\u002Fdocs.readthedocs.io\u002Fen\u002Fstable\u002Fdevelopment\u002Fbuildenvironments.html) - Build your local ReadtheDocs Server.\n* [Doxygen](https:\u002F\u002Fgithub.com\u002Fdoxygen\u002Fdoxygen) - Doxygen is the de facto standard tool for generating documentation from annotated C++ sources.\n* [Sphinx](https:\u002F\u002Fgithub.com\u002Fsphinx-doc\u002Fsphinx\u002F) - A tool that makes it easy to create intelligent and beautiful documentation for Python projects.\n* [Word-to-Markdown](https:\u002F\u002Fgithub.com\u002Fbenbalter\u002Fword-to-markdown) - A ruby gem to liberate content from Microsoft Word document.\n* [paperless](https:\u002F\u002Fgithub.com\u002Fthe-paperless-project\u002Fpaperless) - Index and archive all of your scanned paper documents.\n* [carbon](https:\u002F\u002Fgithub.com\u002Fcarbon-app\u002Fcarbon) - Share beautiful images of your source code.\n* [undraw](https:\u002F\u002Fundraw.co\u002Fillustrations) - Free Professional business SVGs easy to customize.\n* [asciinema](https:\u002F\u002Fgithub.com\u002Fasciinema\u002Fasciinema) - Lets you easily record terminal sessions and replay them in a terminal as well as in a web browser.\n* [inkscape](https:\u002F\u002Finkscape.org\u002F) - Inkscape is a professional vector graphics editor for Linux, Windows and macOS.\n* [Reveal-Hugo](https:\u002F\u002Fgithub.com\u002Fdzello\u002Freveal-hugo) - A Hugo theme for Reveal.js that makes authoring and customization a breeze. With it, you can turn any properly-formatted Hugo content into a HTML presentation.\n* [Hugo-Webslides](https:\u002F\u002Fgithub.com\u002FRCJacH\u002Fhugo-webslides) - This is a Hugo template to create WebSlides presentation using markdown.\n* [jupyter2slides](https:\u002F\u002Fgithub.com\u002Fdatitran\u002Fjupyter2slides) - Cloud Native Presentation Slides with Jupyter Notebook + Reveal.js.\n* [patat](https:\u002F\u002Fgithub.com\u002Fjaspervdj\u002Fpatat) - Terminal-based presentations using Pandoc.\n* [github-changelog-generator](https:\u002F\u002Fgithub.com\u002Fgithub-changelog-generator\u002Fgithub-changelog-generator) - Automatically generate change log from your tags, issues, labels and pull requests on GitHub.\n* [GitLab-Release-Note-Generator](https:\u002F\u002Fgithub.com\u002Fjk1z\u002FGitLab-Release-Note-Generator) - A Gitlab release note generator that generates release note on latest tag.\n* [OCRmyPDF](https:\u002F\u002Fgithub.com\u002Fjbarlow83\u002FOCRmyPDF) - Adds an OCR text layer to scanned PDF files, allowing them to be searched.\n* [papermill](https:\u002F\u002Fgithub.com\u002Fnteract\u002Fpapermill) - A tool for parameterizing, executing, and analyzing Jupyter Notebooks.\n* [docsy](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fdocsy-example) - An example documentation site using the Docsy Hugo theme.\n* [actions-hugo](https:\u002F\u002Fgithub.com\u002Fpeaceiris\u002F) - Deploy website based on Hugo to GitHub Pages.\n* [overleaf](https:\u002F\u002Fgithub.com\u002Foverleaf\u002Foverleaf) - An open-source online real-time collaborative LaTeX editor.\n* [landslide](https:\u002F\u002Fgithub.com\u002Fadamzap\u002Flandslide) - Generate HTML5 slideshows from markdown, ReST, or textile.\n* [libreoffice-impress-templates](https:\u002F\u002Fgithub.com\u002Fdohliam\u002Flibreoffice-impress-templates) - Freely-licensed LibreOffice Impress templates.\n* [opensourcedesign](https:\u002F\u002Fopensourcedesign.net\u002Fresources\u002F) - Community and Resources for Free Design and Logo Creation.\n* [olive](https:\u002F\u002Fwww.olivevideoeditor.org\u002F) - A free non-linear video editor aiming to provide a fully-featured alternative to high-end professional video editing software.\n* [buku](https:\u002F\u002Fgithub.com\u002Fjarun\u002Fbuku) - Browser-independent bookmark manager.\n* [swiftlatex](https:\u002F\u002Fwww.swiftlatex.com\u002F) - A WYSIWYG Browser-based LaTeX Editor.\n* [ReLaXed](https:\u002F\u002Fgithub.com\u002FRelaxedJS\u002FReLaXed) - Allows complex PDF layouts to be defined with CSS and JavaScript, while writing the content in a friendly, minimal syntax close to Markdown or LaTeX.\n* [foam](https:\u002F\u002Fgithub.com\u002Ffoambubble\u002Ffoam) - Foam is a personal knowledge management and sharing system inspired by Roam Research, built on Visual Studio Code and GitHub.\n* [CodiMD](https:\u002F\u002Fgithub.com\u002Fcodimd\u002Fserver) - Open Source Online Real-time collaborate on team documentation in markdown.\n* [jupyter-book](https:\u002F\u002Fgithub.com\u002Fexecutablebooks\u002Fjupyter-book) - Build interactive, publication-quality documents from Jupyter Notebooks.\n* [InvoiceNet](https:\u002F\u002Fgithub.com\u002FnaiveHobo\u002FInvoiceNet) - Deep neural network to extract intelligent information from invoice documents.\n* [tesseract](https:\u002F\u002Fgithub.com\u002Ftesseract-ocr\u002Ftesseract) - Open Source OCR Engine.\n* [mkdocs](https:\u002F\u002Fgithub.com\u002Fmkdocs\u002Fmkdocs\u002F) - A fast, simple and downright gorgeous static site generator that's geared towards building project documentation.\n* [PlotNeuralNet](https:\u002F\u002Fgithub.com\u002FHarisIqbal88\u002FPlotNeuralNet) - Latex code for drawing neural networks for reports and presentation.\n* [Excalidraw](https:\u002F\u002Fgithub.com\u002Fexcalidraw\u002Fexcalidraw) - Virtual whiteboard for sketching hand-drawn like diagrams.\n* [SVGrepo](https:\u002F\u002Fwww.svgrepo.com\u002F) - Download free SVG Vectors for commercial use.\n* [gollum](https:\u002F\u002Fgithub.com\u002Fgollum\u002Fgollum) - A simple, Git-powered wiki with a sweet API and local frontend.\n* [GanttLab](https:\u002F\u002Fgitlab.com\u002Fganttlab\u002Fganttlab) - The easy to use, fully functional Gantt chart for GitLab and GitHub.\n* [Zotero](https:\u002F\u002Fgithub.com\u002Fzotero\u002Fzotero) - A free, easy-to-use tool to help you collect, organize, cite, and share your research sources.\n\n\n## Requirements and Safety\n* [awesome-safety-critical](https:\u002F\u002Fgithub.com\u002Fstanislaw\u002Fawesome-safety-critical) - List of resources about programming practices for writing safety-critical software.\n* [open-autonomous-safety](https:\u002F\u002Fgithub.com\u002Fvoyage\u002Fopen-autonomous-safety) - OAS is a fully open-source library of Voyage's safety processes and testing procedures, designed to supplement existing safety programs at self-driving car startups across the world.\n* [CarND-Functional-Safety-Project](https:\u002F\u002Fgithub.com\u002Fudacity\u002FCarND-Functional-Safety-Project) - Create functional safety documents in this Udacity project.\n* [Automated Valet Parking Safety Documents](https:\u002F\u002Favp-project.uk\u002Fpublication-of-safety-documents) - Created to support the safe testing of the Automated Valet Parking function using the StreetDrone test vehicle in a car park.\n* [safe_numerics](https:\u002F\u002Fgithub.com\u002Fboostorg\u002Fsafe_numerics) - Replacements to standard numeric types which throw exceptions on errors.\n* [Air Vehicle C++ development coding standards](http:\u002F\u002Fwww.stroustrup.com\u002FJSF-AV-rules.pdf) - Provide direction and guidance to C++ programmers that will enable them to employ good programming style and proven programming practices leading to safe, reliable, testable, and maintainable code.\n* [AUTOSAR Coding Standard](https:\u002F\u002Fwww.autosar.org\u002Ffileadmin\u002Fuser_upload\u002Fstandards\u002Fadaptive\u002F17-10\u002FAUTOSAR_RS_CPP14Guidelines.pdf) - Guidelines for the use of the C++14 language in critical and safety-related system.\n* [The W-Model and Lean Scaled Agility for Engineering](https:\u002F\u002Fassets.vector.com\u002Fcms\u002Fcontent\u002Fconsulting\u002Fpublications\u002FAgileSystemsEngineering_Vector_Ford.pdf) - Ford applied an agile V-Model method from Vector that can be used in safety related project management.\n* [doorstop](https:\u002F\u002Fgithub.com\u002Fdoorstop-dev\u002Fdoorstop) - Requirements management using version control.\n* [capella](https:\u002F\u002Fwww.eclipse.org\u002Fcapella\u002F) - Comprehensive, extensible and field-proven MBSE tool and method\nto successfully design systems architecture.\n* [robmosys](https:\u002F\u002Frobmosys.eu\u002F) - RobMoSys envisions an integrated approach built on top of the current code-centric robotic platforms, by applying model-driven methods and tools.\n* [Papyrus for Robotics](https:\u002F\u002Fwww.eclipse.org\u002Fpapyrus\u002Fcomponents\u002Frobotics\u002F) - A graphical editing tool for robotic applications that complies with the RobMoSys approach.\n* [fossology](https:\u002F\u002Fgithub.com\u002Ffossology\u002Ffossology) - A toolkit you can run license, copyright and export control scans from the command line.\n* [ScenarioArchitect](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002FScenarioArchitect) - The Scenario Architect is a basic python tool to generate, import and export short scene snapshots.\n\n\n## Architecture and Design\n* [Guidelines](https:\u002F\u002Fgithub.com\u002FS2-group\u002Ficse-seip-2020-replication-package\u002Fblob\u002Fmaster\u002FICSE_SEIP_2020.pdf) - How to architect ROS-based systems.\n* [yEd](https:\u002F\u002Fwww.yworks.com\u002Fproducts\u002Fyed) - A powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.\n* [yed_py](https:\u002F\u002Fgithub.com\u002Ftrue-grue\u002Fyed_py) - Generates graphML that can be opened in yEd.\n* [Plantuml](https:\u002F\u002Fgithub.com\u002Fplantuml\u002Fplantuml-server) - Web application to generate UML diagrams on-the-fly in your live documentation.\n* [rqt_graph](https:\u002F\u002Fwiki.ros.org\u002Frqt_graph) - Provides a GUI plugin for visualizing the ROS computation graph.\n* [rqt_launchtree](https:\u002F\u002Fgithub.com\u002Fpschillinger\u002Frqt_launchtree) - An RQT plugin for hierarchical launchfile configuration introspection.\n* [cpp-dependencies](https:\u002F\u002Fgithub.com\u002Ftomtom-international\u002Fcpp-dependencies) - Tool to check C++ #include dependencies (dependency graphs created in .dot format).\n* [pydeps](https:\u002F\u002Fgithub.com\u002Fthebjorn\u002Fpydeps) - Python Module Dependency graphs.\n* [aztarna](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002Faztarna) -  A footprinting tool for robots.\n* [draw.io](https:\u002F\u002Fwww.draw.io\u002F) - A free online diagram software for making flowcharts, process diagrams, org charts, UML, ER and network diagrams.\n* [vscode-drawio](https:\u002F\u002Fgithub.com\u002Fhediet\u002Fvscode-drawio) - This extension integrates Draw.io into VS Code.\n* [Architecture_Decision_Record](https:\u002F\u002Fgithub.com\u002Fjoelparkerhenderson\u002Farchitecture_decision_record) - A document that captures an important architectural decision made along with its context and consequences.\n\n## Frameworks and Stacks\n* [ROS](https:\u002F\u002Fgithub.com\u002Fros) - (Robot Operating System) provides libraries and tools to help software developers create robot applications.\n* [awesome-ros2](https:\u002F\u002Fgithub.com\u002Ffkromer\u002Fawesome-ros2) - A curated list of awesome Robot Operating System Version 2.0 (ROS 2) resources and libraries.\n* [Autoware.Auto](https:\u002F\u002Fgitlab.com\u002Fautowarefoundation\u002Fautoware.auto) - Autoware.Auto applies best-in-class software engineering for autonomous driving.\n* [Autoware.ai](https:\u002F\u002Fgithub.com\u002FAutoware-AI) - Autoware.AI is the world's first \"All-in-One\" open-source software for autonomous driving technology.\n* [OpenPilot](https:\u002F\u002Fgithub.com\u002Fcommaai\u002Fopenpilot) - Open Source Adaptive Cruise Control (ACC) and Lane Keeping Assist System (LKAS).\n* [Apollo](https:\u002F\u002Fgithub.com\u002FApolloAuto\u002Fapollo) - High performance, flexible architecture which accelerates the development, testing, and deployment of Autonomous Vehicles.\n* [PythonRobotics](https:\u002F\u002Fgithub.com\u002FAtsushiSakai\u002FPythonRobotics\u002F) - This is a Python code collection of robotics algorithms, especially for autonomous navigation.\n* [Stanford Self Driving Car Code](https:\u002F\u002Fgithub.com\u002Femmjaykay\u002Fstanford_self_driving_car_code) - Stanford Code From Cars That Entered DARPA Grand Challenges.\n* [astrobee](https:\u002F\u002Fgithub.com\u002Fnasa\u002Fastrobee) - Astrobee is a free-flying robot designed to operate as a payload inside the International Space Station (ISS).\n* [CARMAPlatform](https:\u002F\u002Fgithub.com\u002Fusdot-fhwa-stol\u002FCARMAPlatform) - Enables cooperative automated driving plug-in.\n* [Automotive Grade Linux](https:\u002F\u002Fwww.automotivelinux.org\u002F) - Automotive Grade Linux is a collaborative open source project that is bringing together automakers, suppliers and technology companies to accelerate the development and adoption of a fully open software stack for the connected car.\n* [PX4](https:\u002F\u002Fgithub.com\u002FPX4\u002FFirmware) - An open source flight control software for drones and other unmanned vehicles.\n* [KubOS](https:\u002F\u002Fgithub.com\u002Fkubos\u002Fkubos) - An open-source software stack for satellites.\n* [mod_vehicle_dynamics_control](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fmod_vehicle_dynamics_control) - TUM Roborace Team Software Stack - Path tracking control, velocity control, curvature control and state estimation.\n* [Aslan](https:\u002F\u002Fgithub.com\u002Fproject-aslan\u002FAslan) - Open source self-driving software for low speed environments.\n* [open-source-rover](https:\u002F\u002Fgithub.com\u002Fnasa-jpl\u002Fopen-source-rover) - A build-it-yourself, 6-wheel rover based on the rovers on Mars from JPL.\n* [pybotics](https:\u002F\u002Fgithub.com\u002Fengnadeau\u002Fpybotics) -  An open-source and peer-reviewed Python toolbox for robot kinematics and calibration.\n* [makani](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fmakani) - Contains the working Makani flight simulator, controller (autopilot), visualizer, and command center flight monitoring tools.\n* [mir_robot](https:\u002F\u002Fgithub.com\u002Fdfki-ric\u002Fmir_robot) - This is a community project to use the MiR Robots with ROS.\n* [COMPAS](https:\u002F\u002Fgithub.com\u002Fcompas-dev\u002Fcompas_fab) - Robotic fabrication package for the COMPAS Framework.\n* [JdeRobot Academy](https:\u002F\u002Fgithub.com\u002FJdeRobot\u002FRoboticsAcademy) - JdeRobot Academy is an open source collection of exercises to learn robotics in a practical way.\n* [clover](https:\u002F\u002Fgithub.com\u002FCopterExpress\u002Fclover) - ROS-based framework and RPi image to control PX4-powered drones.\n* [ArduPilot](https:\u002F\u002Fgithub.com\u002FArduPilot\u002Fardupilot) - Open source control software for autonomous vehicles - copters\u002Fplanes\u002Frovers\u002Fboats\u002Fsubmersibles.\n* [F Prime](https:\u002F\u002Fgithub.com\u002Fnasa\u002Ffprime) - A component-driven framework that enables rapid development and deployment of spaceflight and other embedded software applications.\n\n## Development Environment\n### Code and Run\n* [Vim-ros](https:\u002F\u002Fgithub.com\u002Ftaketwo\u002Fvim-ros) - Vim plugin for ROS development.\n* [Visual Studio Code](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fvscode) - Code editor for edit-build-debug cycle.\n* [atom](https:\u002F\u002Fgithub.com\u002Fatom\u002Fatom) - Hackable text editor for the 21st century.\n* [Teletype](https:\u002F\u002Fgithub.com\u002Fatom\u002Fteletype) - Share your workspace with team members and collaborate on code in real time in Atom.\n* [Sublime](https:\u002F\u002Fwww.sublimetext.com\u002F) - A sophisticated text editor for code, markup and prose.\n* [ade-cli](https:\u002F\u002Fgitlab.com\u002FApexAI\u002Fade-cli) - The ADE Development Environment (ADE) uses docker and Gitlab to manage environments of per project development tools and optional volume images.\n* [recipe-wizard](https:\u002F\u002Fgithub.com\u002Ftrn84\u002Frecipe-wizard) - A Dockerfile generator for running OpenGL (GLX) applications with nvidia-docker2, CUDA, ROS, and Gazebo on a remote headless server system.\n* [Jupyter ROS](https:\u002F\u002Fgithub.com\u002FRoboStack\u002Fjupyter-ros) - Jupyter widget helpers for ROS, the Robot Operating System.\n* [ros_rqt_plugin](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Fros_qtc_plugin) - The ROS Qt Creator Plug-in for Python.\n* [xeus-cling](https:\u002F\u002Fgithub.com\u002FQuantStack\u002Fxeus-cling) - Jupyter kernel for the C++ programming language.\n* [ROS IDEs](http:\u002F\u002Fwiki.ros.org\u002FIDEs) - This page collects experience and advice on using integrated development environments (IDEs) with ROS.\n* [TabNine](https:\u002F\u002Fgithub.com\u002Fzxqfl\u002FTabNine) - The all-language autocompleter.\n* [kite](https:\u002F\u002Fkite.com\u002F) - Use machine learning to give you useful code completions for Python.\n* [jedi](https:\u002F\u002Fgithub.com\u002Fdavidhalter\u002Fjedi) - Autocompletion and static analysis library for python.\n* [roslibpy](https:\u002F\u002Fgithub.com\u002Fgramaziokohler\u002Froslibpy) - Python ROS Bridge library allows to use Python and IronPython to interact with ROS, the open-source robotic middleware.\n* [pybind11](https:\u002F\u002Fgithub.com\u002Fpybind\u002Fpybind11) - Seamless operability between C++11 and Python.\n* [Sourcetrail](https:\u002F\u002Fgithub.com\u002FCoatiSoftware\u002FSourcetrail) - Free and open-source cross-platform source explorer.\n* [rebound](https:\u002F\u002Fgithub.com\u002Fshobrook\u002Frebound) - Command-line tool that instantly fetches Stack Overflow results when an exception is thrown.\n* [mybinder](https:\u002F\u002Fmybinder.org\u002F) - Open notebooks in an executable environment, making your code immediately reproducible by anyone, anywhere.\n* [ROSOnWindows](https:\u002F\u002Fms-iot.github.io\u002FROSOnWindows\u002F) - An experimental release of ROS1 for Windows.\n* [live-share](https:\u002F\u002Fgithub.com\u002FMicrosoftDocs\u002Flive-share) - Real-time collaborative development from the comfort of your favorite tools.\n* [cocalc](https:\u002F\u002Fgithub.com\u002Fsagemathinc\u002Fcocalc) - Collaborative Calculation in the Cloud.\n* [EasyClangComplete](https:\u002F\u002Fgithub.com\u002Fniosus\u002FEasyClangComplete) - Robust C\u002FC++ code completion for Sublime Text 3.\n* [vscode-ros](https:\u002F\u002Fgithub.com\u002Fms-iot\u002Fvscode-ros) - Visual Studio Code extension for Robot Operating System (ROS) development.\n* [awesome-hpp](https:\u002F\u002Fgithub.com\u002Fp-ranav\u002Fawesome-hpp) - A curated list of awesome header-only C++ libraries.\n* [Gitpod](https:\u002F\u002Fgithub.com\u002Fgitpod-io\u002Fgitpod) - An open source developer platform that automates the provisioning of ready-to-code development environments.\n\n### Template\n* [ROS](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fros_best_practices\u002Ftree\u002Fmaster\u002Fros_package_template) - Template for ROS node standardization in C++.\n* [Launch](https:\u002F\u002Fwiki.ros.org\u002Froslaunch\u002FTutorials\u002FRoslaunch%20tips%20for%20larger%20projects) - Templates on how to create launch files for larger projects.\n* [Bash](https:\u002F\u002Fgithub.com\u002Fralish\u002Fbash-script-template) - A bash scripting template incorporating best practices & several useful functions.\n* [URDF](https:\u002F\u002Fwiki.ros.org\u002Furdf\u002FExamples) - Examples on how to create Unified Robot Description Format (URDF) for different kinds of robots.\n* [Python](http:\u002F\u002Fwiki.ros.org\u002FPyStyleGuide) - Style guide to be followed in writing Python code for ROS.\n* [Docker](https:\u002F\u002Fade-cli.readthedocs.io\u002Fen\u002Flatest\u002Fcreate-custom-base-image.html) - The Dockerfile in the minimal-ade project shows a minimal example of how to create a custom base image.\n* [VS Code ROS2 Workspace Template](https:\u002F\u002Fgithub.com\u002Fathackst\u002Fvscode_ros2_workspace) -  Template for using VSCode as an IDE for ROS2 development.\n\n### Build and Deploy\n* [qemu-user-static](https:\u002F\u002Fgithub.com\u002Fmultiarch\u002Fqemu-user-static) - Enable an execution of different multi-architecture containers by QEMU and binfmt_misc.\n* [Cross compile ROS 2 on QNX](https:\u002F\u002Fgitlab.apex.ai\u002Fsnippets\u002F97) -  Introduces how to cross compile ROS 2 on QNX.\n* [bloom](https:\u002F\u002Fgithub.com\u002Fros-infrastructure\u002Fbloom) - A release automation tool which makes releasing catkin packages easier.\n* [superflore](https:\u002F\u002Fgithub.com\u002Fros-infrastructure\u002Fsuperflore) - An extended platform release manager for Robot Operating System.\n* [catkin_tools](https:\u002F\u002Fgithub.com\u002Fcatkin\u002Fcatkin_tools) - Command line tools for working with catkin.\n* [industrial_ci](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Findustrial_ci) - Easy continuous integration repository for ROS repositories.\n* [ros_gitlab_ci](https:\u002F\u002Fgitlab.com\u002FVictorLamoine\u002Fros_gitlab_ci) - Contains helper scripts and instructions on how to use Continuous Integration (CI) for ROS projects hosted on a GitLab instance.\n* [gitlab-runner](https:\u002F\u002Fgitlab.com\u002Fgitlab-org\u002Fgitlab-runner) -  Runs tests and sends the results to GitLab.\n* [colcon-core](https:\u002F\u002Fgithub.com\u002Fcolcon\u002Fcolcon-core) - Command line tool to improve the workflow of building, testing and using multiple software packages.\n* [gitlab-release](https:\u002F\u002Fgitlab.com\u002Falelec\u002Fgitlab-release) - Simple python3 script to upload files (from ci) to the current projects release (tag).\n* [clang](https:\u002F\u002Fgithub.com\u002Fllvm-mirror\u002Fclang) -  This is a compiler front-end for the C family of languages (C, C++, Objective-C, and Objective-C++) which is built as part of the LLVM compiler infrastructure project.\n* [catkin_virtualenv](https:\u002F\u002Fgithub.com\u002Flocusrobotics\u002Fcatkin_virtualenv) - Bundle python requirements in a catkin package via virtualenv.\n* [pyenv](https:\u002F\u002Fgithub.com\u002Fpyenv\u002Fpyenv) - Simple Python version management.\n* [aptly](https:\u002F\u002Fgithub.com\u002Faptly-dev\u002Faptly) - Debian repository management tool.\n* [cross_compile](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Fcross_compile) - Assets used for ROS2 cross-compilation.\n* [docker_images](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fdocker_images) - Official Docker images maintained by OSRF on ROS(2) and Gazebo.\n* [robot_upstart](https:\u002F\u002Fgithub.com\u002Fclearpathrobotics\u002Frobot_upstart) - Presents a suite of scripts to assist with launching background ROS processes on Ubuntu Linux PCs.\n* [robot_systemd](http:\u002F\u002Fdocs.ros.org\u002Fkinetic\u002Fapi\u002Frobot_systemd\u002Fhtml\u002F#) - Units for managing startup and shutdown of roscore and roslaunch.\n* [ryo-iso](https:\u002F\u002Fryo-iso.readthedocs.io\u002Fen\u002Flatest\u002F) - A modern ISO builder that streamlines the process of deploying a complete robot operating system from a yaml config file.\n* [network_autoconfig](http:\u002F\u002Fdocs.ros.org\u002Fkinetic\u002Fapi\u002Fnetwork_autoconfig\u002Fhtml\u002F) - Automatic configuration of ROS networking for most use cases without impacting usage that require manual configuration.\n* [rosbuild](https:\u002F\u002Froscon.ros.org\u002F2016\u002Fpresentations\u002FROSCon2016%20Build%20Farm.pdf) - The ROS build farm.\n* [cros](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Fcros) - A single thread pure C implementation of the ROS framework.\n\n\n### Unit and Integration Test\n* [setup-ros](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Fsetup-ros) - This action sets up a ROS and ROS 2 environment for use in GitHub actions.\n* [UnitTesting](https:\u002F\u002Fwiki.ros.org\u002FQuality\u002FTutorials\u002FUnitTesting) - This page lays out the rationale, best practices, and policies for writing and running unit tests and integration tests for ROS.\n* [googletest](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fgoogletest) - Google's C++ test framework.\n* [pytest](https:\u002F\u002Fgithub.com\u002Fpytest-dev\u002Fpytest\u002F) - The pytest framework makes it easy to write small tests, yet scales to support complex functional testing.\n* [doctest](https:\u002F\u002Fgithub.com\u002Fonqtam\u002Fdoctest) - The fastest feature-rich C++11\u002F14\u002F17\u002F20 single-header testing framework for unit tests and TDD.\n* [osrf_testing_tools_cpp](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fosrf_testing_tools_cpp) - Contains testing tools for C++, and is used in OSRF projects.\n* [code_coverage](https:\u002F\u002Fgithub.com\u002Fmikeferguson\u002Fcode_coverage) - ROS package to run coverage testing.\n* [action-ros-ci](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Faction-ros-ci) - GitHub Action to build and test ROS 2 packages using colcon.\n\n### Lint and Format\n* [action-ros-lint](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Faction-ros-lint) - GitHub action to run linters on ROS 2 packages.\n* [cppcheck](https:\u002F\u002Fgithub.com\u002Fdanmar\u002Fcppcheck) - Static analysis of C\u002FC++ code.\n* [hadolint](https:\u002F\u002Fgithub.com\u002Fhadolint\u002Fhadolint) - Dockerfile linter, validate inline bash, written in Haskell.\n* [shellcheck](https:\u002F\u002Fgithub.com\u002Fkoalaman\u002Fshellcheck) - A static analysis tool for shell scripts.\n* [catkin_lint](https:\u002F\u002Fgithub.com\u002Ffkie\u002Fcatkin_lint) - Checks package configurations for the catkin build system of ROS.\n* [pylint](https:\u002F\u002Fgithub.com\u002FPyCQA\u002Fpylint\u002F) - Pylint is a Python static code analysis tool which looks for programming errors, helps enforcing a coding standard, sniffs for code smells and offers simple refactoring suggestions.\n* [black](https:\u002F\u002Fgithub.com\u002Fpsf\u002Fblack) - The uncompromising Python code formatter.\n* [pydocstyle](https:\u002F\u002Fgithub.com\u002FPyCQA\u002Fpydocstyle) - A static analysis tool for checking compliance with Python docstring conventions.\n* [haros](https:\u002F\u002Fgithub.com\u002Fgit-afsantos\u002Fharos) - Static analysis of ROS application code.\n* [pydantic](https:\u002F\u002Fgithub.com\u002Fsamuelcolvin\u002Fpydantic) - Data parsing and validation using Python type hints.\n\n\n### Debugging and Tracing\n* [heaptrack](https:\u002F\u002Fgithub.com\u002FKDE\u002Fheaptrack) - Traces all memory allocations and annotates these events with stack traces.\n* [ros2_tracing](https:\u002F\u002Fgitlab.com\u002Fros-tracing\u002Fros2_tracing) - Tracing tools for ROS 2.\n* [Linuxperf](http:\u002F\u002Fwww.brendangregg.com\u002Flinuxperf.html) - Various Linux performance material.\n* [lptrace](https:\u002F\u002Fgithub.com\u002Fkhamidou\u002Flptrace) - It lets you see in real-time what functions a Python program is running.\n* [pyre-check](https:\u002F\u002Fgithub.com\u002Ffacebook\u002Fpyre-check) - Performant type-checking for python.\n* [FlameGraph](https:\u002F\u002Fgithub.com\u002Fbrendangregg\u002FFlameGraph) - Visualize profiled code.\n* [gpuvis](https:\u002F\u002Fgithub.com\u002Fmikesart\u002Fgpuvis) - GPU Trace Visualizer.\n* [sanitizer](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fsanitizers) - AddressSanitizer, ThreadSanitizer, MemorySanitizer.\n* [cppinsights](https:\u002F\u002Fgithub.com\u002Fandreasfertig\u002Fcppinsights) - C++ Insights - See your source code with the eyes of a compiler.\n* [inspect](https:\u002F\u002Fpymotw.com\u002F2\u002Finspect\u002F) - The inspect module provides functions for learning about live objects, including modules, classes, instances, functions, and methods.\n* [Roslaunch Nodes in Valgrind or GDB](https:\u002F\u002Fwiki.ros.org\u002Froslaunch\u002FTutorials\u002FRoslaunch%20Nodes%20in%20Valgrind%20or%20GDB) - When debugging roscpp nodes that you are launching with roslaunch, you may wish to launch the node in a debugging program like gdb or valgrind instead.\n* [pyperformance](https:\u002F\u002Fgithub.com\u002Fpython\u002Fpyperformance) - Python Performance Benchmark Suite.\n* [qira](https:\u002F\u002Fgithub.com\u002Fgeohot\u002Fqira) - QIRA is a competitor to strace and gdb.\n* [gdb-frontend](https:\u002F\u002Fgithub.com\u002Frohanrhu\u002Fgdb-frontend) - GDBFrontend is an easy, flexible and extensionable gui debugger.\n* [lttng](https:\u002F\u002Flttng.org\u002Fdocs\u002F) - An open source software toolkit which you can use to simultaneously trace the Linux kernel, user applications, and user libraries.\n* [ros2-performance](https:\u002F\u002Fgithub.com\u002Firobot-ros\u002Fros2-performance) - Allows to easily create arbitrary ROS2 systems and then measures their performance.\n* [bcc](https:\u002F\u002Fgithub.com\u002Fiovisor\u002Fbcc) - Tools for BPF-based Linux IO analysis, networking, monitoring, and more.\n* [tracy](https:\u002F\u002Fgithub.com\u002Fwolfpld\u002Ftracy) - A real time, nanosecond resolution, remote telemetry frame profiler for games and other applications.\n* [bpftrace](https:\u002F\u002Fgithub.com\u002Fiovisor\u002Fbpftrace) - High-level tracing language for Linux eBPF.\n* [pudb](https:\u002F\u002Fgithub.com\u002Finducer\u002Fpudb) - Full-screen console debugger for Python.\n* [backward-cpp](https:\u002F\u002Fgithub.com\u002Fbombela\u002Fbackward-cpp) - A beautiful stack trace pretty printer for C++.\n* [gdb-dashboard](https:\u002F\u002Fgithub.com\u002Fcyrus-and\u002Fgdb-dashboard) - GDB dashboard is a standalone .gdbinit file written using the Python API that enables a modular interface showing relevant information about the program being debugged.\n* [hotspot](https:\u002F\u002Fgithub.com\u002FKDAB\u002Fhotspot) - The Linux perf GUI for performance analysis.\n* [memory_profiler](https:\u002F\u002Fgithub.com\u002Fpythonprofilers\u002Fmemory_profiler) - A python module for monitoring memory consumption of a process as well as line-by-line analysis of memory consumption for python programs.\n* [ros1_fuzzer](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002Fros1_fuzzer) - This fuzzer aims to help developers and researchers to find bugs and vulnerabilities in ROS nodes by performing fuzz tests over topics that the target nodes process.\n* [vscode-debug-visualizer](https:\u002F\u002Fgithub.com\u002Fhediet\u002Fvscode-debug-visualizer) - An extension for VS Code that visualizes data during debugging.\n* [action-tmate](https:\u002F\u002Fgithub.com\u002Fmxschmitt\u002Faction-tmate) - Debug your GitHub Actions via SSH by using tmate to get access to the runner system itself.\n* [libstatistics_collector](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Flibstatistics_collector) - ROS 2 library providing classes to collect measurements and calculate statistics across them.\n* [system_metrics_collector](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Fsystem_metrics_collector) - Lightweight, real-time system metrics collector for ROS2 systems.\n\n\n### Version Control\n* [git-fuzzy](https:\u002F\u002Fgithub.com\u002FbigH\u002Fgit-fuzzy) - A CLI interface to git that relies heavily on fzf.\n* [meld](https:\u002F\u002Fgithub.com\u002FGNOME\u002Fmeld) - Meld is a visual diff and merge tool that helps you compare files, directories, and version controlled projects.\n* [tig](https:\u002F\u002Fgithub.com\u002Fjonas\u002Ftig) - Text-mode interface for git.\n* [gitg](https:\u002F\u002Fgithub.com\u002FGNOME\u002Fgitg) - A graphical user interface for git.\n* [git-cola](https:\u002F\u002Fgithub.com\u002Fgit-cola\u002Fgit-cola) - The highly caffeinated Git GUI.\n* [python-gitlab](https:\u002F\u002Fgithub.com\u002Fpython-gitlab\u002Fpython-gitlab) - A Python package providing access to the GitLab server API.\n* [bfg-repo-cleaner](https:\u002F\u002Fgithub.com\u002Frtyley\u002Fbfg-repo-cleaner) - Removes large or troublesome blobs like git-filter-branch does, but faster.\n* [nbdime](https:\u002F\u002Fgithub.com\u002Fjupyter\u002Fnbdime) - Tools for diffing and merging of Jupyter notebooks.\n* [semantic-release](https:\u002F\u002Fgithub.com\u002Fsemantic-release\u002Fsemantic-release) - Fully automated version management and package publishing.\n* [go-semrel-gitab](https:\u002F\u002Fgitlab.com\u002Fjuhani\u002Fgo-semrel-gitlab) - Automate version management for Gitlab.\n* [Git-repo](https:\u002F\u002Fgerrit.googlesource.com\u002Fgit-repo\u002F) - Git-Repo helps manage many Git repositories, does the uploads to revision control systems, and automates parts of the development workflow.\n* [dive](https:\u002F\u002Fgithub.com\u002Fwagoodman\u002Fdive) - A tool for exploring each layer in a docker image.\n* [dvc](https:\u002F\u002Fgithub.com\u002Fiterative\u002Fdvc) - Management and versioning of datasets and machine learning models.\n* [learnGitBranching](https:\u002F\u002Fgithub.com\u002Fpcottle\u002FlearnGitBranching) - A git repository visualizer, sandbox, and a series of educational tutorials and challenges.\n* [gitfs](https:\u002F\u002Fgithub.com\u002FPresslabs\u002Fgitfs) - You can mount a remote repository's branch locally, and any subsequent changes made to the files will be automatically committed to the remote.\n* [git-secret](https:\u002F\u002Fgithub.com\u002Fsobolevn\u002Fgit-secret) - Encrypts files with permitted users' public keys, allowing users you trust to access encrypted data using pgp and their secret keys.\n* [git-sweep](https:\u002F\u002Fgithub.com\u002Farc90\u002Fgit-sweep) - A command-line tool that helps you clean up Git branches that have been merged into master.\n* [lazygit](https:\u002F\u002Fgithub.com\u002Fjesseduffield\u002Flazygit) - A simple terminal UI for git commands, written in Go with the gocui library.\n* [glab](https:\u002F\u002Fgithub.com\u002Fprofclems\u002Fglab) - An open-source GitLab command line tool.\n\n\n## Simulation\n* [AI2-THOR](https:\u002F\u002Fgithub.com\u002Fallenai\u002Fai2thor) - Python framework with a Unity backend providing interaction, navigation, and manipulation support for household based robotic agents, consisting of 200+ of custom scenes, 1500+ custom annotated objects, and 200+ actions.\n* [Drake](https:\u002F\u002Fgithub.com\u002FRobotLocomotion\u002Fdrake) - Drake aims to simulate even very complex dynamics of robots.\n* [Webots](https:\u002F\u002Fgithub.com\u002Fcyberbotics\u002Fwebots) - Webots is an open source robot simulator compatible (among others) with [ROS](http:\u002F\u002Fwiki.ros.org\u002Fwebots_ros) and [ROS2](http:\u002F\u002Fwiki.ros.org\u002Fwebots_ros2).\n* [lgsv](https:\u002F\u002Fgithub.com\u002Flgsvl\u002Fsimulator) - LG Electronics America R&D Center has developed an HDRP Unity-based multi-robot simulator for autonomous vehicle developers.\n* [carla](https:\u002F\u002Fgithub.com\u002Fcarla-simulator\u002Fcarla) - Open-source simulator for autonomous driving research.\n* [awesome-CARLA](https:\u002F\u002Fgithub.com\u002FAmin-Tgz\u002Fawesome-CARLA) - A curated list of awesome CARLA tutorials, blogs, and related projects.\n* [ros-bridge](https:\u002F\u002Fgithub.com\u002Fcarla-simulator\u002Fros-bridge) - ROS bridge for CARLA Simulator.\n* [scenario_runner](https:\u002F\u002Fgithub.com\u002Fcarla-simulator\u002Fscenario_runner) - Traffic scenario definition and execution engine.\n* [deepdive](https:\u002F\u002Fgithub.com\u002Fdeepdrive\u002Fdeepdrive) - End-to-end simulation for self-driving cars.\n* [uuv_simulator](https:\u002F\u002Fgithub.com\u002Fuuvsimulator\u002Fuuv_simulator) - Gazebo\u002FROS packages for underwater robotics simulation.\n* [AirSim](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAirSim) - Open source simulator for autonomous vehicles built on Unreal Engine.\n* [self-driving-car-sim](https:\u002F\u002Fgithub.com\u002Fudacity\u002Fself-driving-car-sim) - A self-driving car simulator built with Unity.\n* [ROSIntegration](https:\u002F\u002Fgithub.com\u002Fcode-iai\u002FROSIntegration) - Unreal Engine Plugin to enable ROS Support.\n* [gym-gazebo](https:\u002F\u002Fgithub.com\u002Ferlerobot\u002Fgym-gazebo) - An OpenAI gym extension for using Gazebo known as gym-gazebo.\n* [gym-pybullet-drones](https:\u002F\u002Fgithub.com\u002FutiasDSL\u002Fgym-pybullet-drones) - PyBullet-based Gym environments for single and multi-agent reinforcement learning of quadcopter control.\n* [safe-control-gym](https:\u002F\u002Fgithub.com\u002FutiasDSL\u002Fsafe-control-gym) - PyBullet-based CartPole and Quadrotor environments—with CasADi symbolic dynamics and constraints—for safe and robust learning-based control.\n* [highway-env](https:\u002F\u002Fgithub.com\u002Feleurent\u002Fhighway-env) - A collection of environments for autonomous driving and tactical decision-making tasks.\n* [VREP Interface](http:\u002F\u002Fwww.coppeliarobotics.com\u002FhelpFiles\u002Fen\u002FrosInterf.htm) - ROS Bridge for the VREP simulator.\n* [car_demo](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fcar_demo) - This is a simulation of a Prius in gazebo 9 with sensor data being published using ROS kinetic.\n* [sumo](https:\u002F\u002Fgithub.com\u002Feclipse\u002Fsumo) - Eclipse SUMO is an open source, highly portable, microscopic and continuous road traffic simulation package designed to handle large road networks.\n* [open-simulation-interface](https:\u002F\u002Fgithub.com\u002FOpenSimulationInterface\u002Fopen-simulation-interface) - A generic interface for the environmental perception of automated driving functions in virtual scenarios.\n* [ESIM](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Frpg_esim\u002F) - An Open Event Camera Simulator.\n* [Menge](https:\u002F\u002Fgithub.com\u002FMengeCrowdSim\u002FMenge) - Crowd Simulation Framework.\n* [pedsim_ros](https:\u002F\u002Fgithub.com\u002Fsrl-freiburg\u002Fpedsim_ros) - Pedestrian simulator powered by the social force model for Gazebo.\n* [opencrg](http:\u002F\u002Fwww.opencrg.org\u002Fdownload.html) -  Open file formats and open source tools for the detailed description, creation and evaluation of road surfaces.\n* [esmini](https:\u002F\u002Fgithub.com\u002Fesmini\u002Fesmini) -  A basic OpenSCENARIO player.\n* [OpenSceneGraph](https:\u002F\u002Fgithub.com\u002Fopenscenegraph\u002FOpenSceneGraph) - An open source high performance 3D graphics toolkit, used by application developers in fields such as visual simulation, games, virtual reality, scientific visualization and modelling.\n* [morse](https:\u002F\u002Fgithub.com\u002Fmorse-simulator) - An academic robotic simulator, based on the Blender Game Engine and the Bullet Physics engine.\n* [ROSIntegrationVision](https:\u002F\u002Fgithub.com\u002Fcode-iai\u002FROSIntegrationVision) - Support for ROS-enabled RGBD data acquisition in Unreal Engine Projects.\n* [fetch_gazebo](https:\u002F\u002Fgithub.com\u002Ffetchrobotics\u002Ffetch_gazebo) - Contains the Gazebo simulation for Fetch Robotics Fetch and Freight Research Edition Robots.\n* [rotors_simulator](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Frotors_simulator) - Provides some multirotor models.\n* [flow](https:\u002F\u002Fgithub.com\u002Fflow-project\u002Fflow) - A computational framework for deep RL and control experiments for traffic microsimulation.\n* [gnss-ins-sim](https:\u002F\u002Fgithub.com\u002FAceinna\u002Fgnss-ins-sim) - GNSS + inertial navigation, sensor fusion simulator. Motion trajectory generator, sensor models, and navigation.\n* [Ignition Robotics](https:\u002F\u002Fignitionrobotics.org) -  Test control strategies in safety, and take advantage of simulation in continuous integration tests.\n* [simulation assets for the SubT](https:\u002F\u002Fsubtchallenge.world\u002Fopenrobotics\u002Ffuel\u002Fcollections\u002FSubT%20Tech%20Repo) - This collection contains simulation assets for the SubT Challenge Virtual Competition in Gazebo.\n* [gazebo_ros_motors](https:\u002F\u002Fgithub.com\u002Fnilseuropa\u002Fgazebo_ros_motors) - Contains currently two motor plugins for Gazebo, one with an ideal speed controller and one without a controller that models a DC motor.\n* [map2gazebo](https:\u002F\u002Fgithub.com\u002Fshilohc\u002Fmap2gazebo) - ROS package for creating Gazebo environments from 2D maps.\n* [sim_vehicle_dynamics](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fsim_vehicle_dynamics) - Vehicle Dynamics Simulation Software of TUM Roborace Team.\n* [gym-carla](https:\u002F\u002Fgithub.com\u002Fcjy1992\u002Fgym-carla) - An OpenAI gym wrapper for CARLA simulator.\n* [simbody](https:\u002F\u002Fgithub.com\u002Fsimbody\u002Fsimbody) - High-performance C++ multibody dynamics\u002Fphysics library for simulating articulated biomechanical and mechanical systems like vehicles, robots, and the human skeleton.\n* [gazebo_models](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fgazebo_models) - This repository holds the Gazebo model database.\n* [pylot](https:\u002F\u002Fgithub.com\u002Ferdos-project\u002Fpylot) - Autonomous driving platform running on the CARLA simulator.\n* [flightmare](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Fflightmare) - Flightmare is composed of two main components: a configurable rendering engine built on Unity and a flexible physics engine for dynamics simulation.\n* [champ](https:\u002F\u002Fgithub.com\u002Fchvmp\u002Fchamp) - ROS Packages for CHAMP Quadruped Controller.\n* [rex-gym](https:\u002F\u002Fgithub.com\u002Fnicrusso7\u002Frex-gym) - OpenAI Gym environments for an open-source quadruped robot (SpotMicro).\n* [Trick](https:\u002F\u002Fgithub.com\u002Fnasa\u002FTrick) - Developed at the NASA Johnson Space Center, is a powerful simulation development framework that enables users to build applications for all phases of space vehicle development.\n* [usv_sim_lsa](https:\u002F\u002Fgithub.com\u002Fdisaster-robotics-proalertas\u002Fusv_sim_lsa) - Unmanned Surface Vehicle simulation on Gazebo with water current and winds.\n* [42](https:\u002F\u002Fgithub.com\u002Fericstoneking\u002F42) - Simulation for spacecraft attitude control system analysis and design.\n* [Complete_Street_Rule](https:\u002F\u002Fgithub.com\u002Fd-wasserman\u002FComplete_Street_Rule) - A scenario oriented design tool intended to enable users to quickly create procedurally generated multimodal streets in ArcGIS CityEngine.\n* [AutoCore simulation](https:\u002F\u002Fgithub.com\u002Fautowarefoundation\u002F) - Provides test environment for Autoware and still during early development, contents below may changed during updates.\n* [fields-ignition](https:\u002F\u002Fgithub.com\u002Fazazdeaz\u002Ffields-ignition) - Generate random crop fields for Ignition Gazebo.\n* [Unity-Robotics-Hub](https:\u002F\u002Fgithub.com\u002FUnity-Technologies\u002FUnity-Robotics-Hub) - Central repository for tools, tutorials, resources, and documentation for robotic simulation in Unity.\n* [BlueSky](https:\u002F\u002Fgithub.com\u002FTUDelft-CNS-ATM\u002Fbluesky) - The goal of BlueSky is to provide everybody who wants to visualize, analyze or simulate air traffic with a tool to do so without any restrictions, licenses or limitations.\n* [Cloe](https:\u002F\u002Fgithub.com\u002Feclipse\u002Fcloe) - Empowers developers of automated-driving software components by providing a unified interface to closed-loop simulation.\n* [Dynamic_logistics_Warehouse](https:\u002F\u002Fgithub.com\u002Fbelal-ibrahim\u002Fdynamic_logistics_warehouse) - Gazebo simulation of dynamics environment in warehouses.\n* [OpenCDA](https:\u002F\u002Fgithub.com\u002Fucla-mobility\u002FOpenCDA) - A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.\n\n\n## Electronics and Mechanics\n* [HRIM](https:\u002F\u002Fgithub.com\u002FAcutronicRobotics\u002FHRIM) - An information model for robot hardware.\n* [URDF](https:\u002F\u002Fgithub.com\u002Fros\u002Furdf) - Repository for Unified Robot Description Format (URDF) parsing code.\n* [phobos](https:\u002F\u002Fgithub.com\u002Fdfki-ric\u002Fphobos) - An add-on for Blender allowing to create URDF, SDF and SMURF robot models in a WYSIWYG environment.\n* [urdf-viz](https:\u002F\u002Fgithub.com\u002FOTL\u002Furdf-viz) - Visualize URDF\u002FXACRO file, URDF Viewer works on Windows\u002FmacOS\u002FLinux.\n* [solidworks_urdf_exporter](https:\u002F\u002Fgithub.com\u002Fros\u002Fsolidworks_urdf_exporter) - SolidWorks to URDF Exporter.\n* [FreeCAD](https:\u002F\u002Fgithub.com\u002FFreeCAD\u002FFreeCAD) - Your own 3D parametric modeler.\n* [kicad](http:\u002F\u002Fwww.kicad.org\u002F) - A Cross Platform and Open Source Electronics Design Automation Suite.\n* [PcbDraw](https:\u002F\u002Fgithub.com\u002Fyaqwsx\u002FPcbDraw) - Convert your KiCAD board into a nice looking 2D drawing suitable for pinout diagrams.\n* [kicad-3rd-party-tools](https:\u002F\u002Fgithub.com\u002Fxesscorp\u002Fkicad-3rd-party-tools) - Tools made by others to augment the KiCad PCB EDA suite.\n* [PandaPower](http:\u002F\u002Fwww.pandapower.org) - An easy to use open source tool for power system modeling, analysis and optimization with a high degree of automation.\n* [LibrePCB](https:\u002F\u002Fgithub.com\u002FLibrePCB\u002FLibrePCB) - A powerful, innovative and intuitive EDA tool for everyone.\n* [openscad](https:\u002F\u002Fgithub.com\u002Fopenscad\u002Fopenscad) -  A software for creating solid 3D CAD models.\n* [ngspice](http:\u002F\u002Fngspice.sourceforge.net\u002F) - A open source spice simulator for electric and electronic circuits.\n* [GNSS-SDR](https:\u002F\u002Fgithub.com\u002Fgnss-sdr\u002Fgnss-sdr) - GNSS-SDR provides interfaces for a wide range of radio frequency front-ends and raw sample file formats, generates processing outputs in standard formats.\n* [riscv](https:\u002F\u002Friscv.org) - The Free and Open RISC Instruction Set Architecture.\n* [urdfpy](https:\u002F\u002Fgithub.com\u002Fmmatl\u002Furdfpy) - A simple and easy-to-use library for loading, manipulating, saving, and visualizing URDF files.\n* [FMPy](https:\u002F\u002Fgithub.com\u002FCATIA-Systems\u002FFMPy) - Simulate Functional Mockup Units (FMUs) in Python.\n* [FMIKit-Simulink](https:\u002F\u002Fgithub.com\u002FCATIA-Systems\u002FFMIKit-Simulink) - Import and export Functional Mock-up Units with Simulink.\n* [oemof-solph](https:\u002F\u002Fgithub.com\u002Foemof\u002Foemof-solph) - A modular open source framework to model energy supply systems.\n* [NASA-3D-Resources](https:\u002F\u002Fgithub.com\u002Fnasa\u002FNASA-3D-Resources) - Here you'll find a growing collection of 3D models, textures, and images from inside NASA.\n* [SUAVE](https:\u002F\u002Fgithub.com\u002Fsuavecode\u002FSUAVE) - An Aircraft Design Toolbox.\n* [opem](https:\u002F\u002Fgithub.com\u002FECSIM\u002Fopem) - The Open-Source PEMFC Simulation Tool (OPEM) is a modeling tool for evaluating the performance of proton exchange membrane fuel cells.\n* [pvlib-python](https:\u002F\u002Fgithub.com\u002Fpvlib\u002Fpvlib-python) - A community supported tool that provides a set of functions and classes for simulating the performance of photovoltaic energy systems.\n* [WireViz](https:\u002F\u002Fgithub.com\u002Fformatc1702\u002FWireViz) - A tool for easily documenting cables, wiring harnesses and connector pinouts.\n* [Horizon](https:\u002F\u002Fgithub.com\u002Fhorizon-eda\u002Fhorizon) - EDA is an Electronic Design Automation package supporting an integrated end-to-end workflow for printed circuit board design including parts management and schematic entry.\n* [tigl](https:\u002F\u002Fgithub.com\u002FDLR-SC\u002Ftigl) - The TiGL Geometry Library can be used for the computation and processing of aircraft geometries stored inside CPACS files.\n* [foxBMS](https:\u002F\u002Fgithub.com\u002FfoxBMS\u002Ffoxbms) - A free, open and flexible development environment to design battery management systems.\n* [cadCAD](https:\u002F\u002Fgithub.com\u002FcadCAD-org\u002FcadCAD) - A Python package that assists in the processes of designing, testing and validating complex systems through simulation, with support for Monte Carlo methods, A\u002FB testing and parameter sweeping.\n* [OpenMDAO](https:\u002F\u002Fgithub.com\u002FOpenMDAO\u002FOpenMDAO) - An open-source framework for efficient multidisciplinary optimization.\n* [ODrive](https:\u002F\u002Fgithub.com\u002Fmadcowswe\u002FODrive) - The aim is to make it possible to use inexpensive brushless motors in high performance robotics projects.\n* [OpenTirePython](https:\u002F\u002Fgithub.com\u002FOpenTire\u002FOpenTirePython) - An open-source mathematical tire modelling library.\n* [Inkscape Ray Optics](https:\u002F\u002Fgithub.com\u002FdamienBloch\u002Finkscape-raytracing) - An extension for Inkscape that makes it easier to draw optical diagrams.\n* [OpenAeroStruct](https:\u002F\u002Fgithub.com\u002Fmdolab\u002FOpenAeroStruct) -  A lightweight tool that performs aerostructural optimization using OpenMDAO.\n\n## Sensor Processing\n### Calibration and Transformation\n* [tf2](http:\u002F\u002Fwiki.ros.org\u002Ftf2) - Transform library, which lets the user keep track of multiple coordinate frames over time.\n* [TriP](https:\u002F\u002Fgithub.com\u002FTriPed-Robot\u002FTriP) - A Inverse Kinematics library for serial robots, parallel robots and hybrids of both.\n* [lidar_align](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Flidar_align) - A simple method for finding the extrinsic calibration between a 3D lidar and a 6-dof pose sensor.\n* [kalibr](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fkalibr) - The Kalibr visual-inertial calibration toolbox.\n* [Calibnet](https:\u002F\u002Fgithub.com\u002Fepiception\u002FCalibNet) - Self-Supervised Extrinsic Calibration using 3D Spatial Transformer Networks.\n* [lidar_camera_calibration](https:\u002F\u002Fgithub.com\u002Fankitdhall\u002Flidar_camera_calibration) - ROS package to find a rigid-body transformation between a LiDAR and a camera.\n* [ILCC](https:\u002F\u002Fgithub.com\u002Fmfxox\u002FILCC) - Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR.\n* [easy_handeye](https:\u002F\u002Fgithub.com\u002FIFL-CAMP\u002Feasy_handeye) - Simple, straighforward ROS library for hand-eye calibration.\n* [imu_utils](https:\u002F\u002Fgithub.com\u002Fgaowenliang\u002Fimu_utils) - A ROS package tool to analyze the IMU performance.\n* [kalibr_allan](https:\u002F\u002Fgithub.com\u002Frpng\u002Fkalibr_allan) - IMU Allan standard deviation charts for use with Kalibr and inertial kalman filters.\n* [pyquaternion](https:\u002F\u002Fgithub.com\u002FKieranWynn\u002Fpyquaternion) - A full-featured Python module for representing and using quaternions.\n* [robot_calibration](https:\u002F\u002Fgithub.com\u002Fmikeferguson\u002Frobot_calibration\u002F) - This package offers calibration of a number of parameters of a robot, such as: 3D Camera intrinsics, extrinsics Joint angle offsets and robot frame offsets.\n* [multi_sensor_calibration](https:\u002F\u002Fgithub.com\u002Ftudelft-iv\u002Fmulti_sensor_calibration\u002F) - Contains a calibration tool to calibrate a sensor setup consisting of lidars, radars and cameras.\n* [LiDARTag](https:\u002F\u002Fgithub.com\u002FUMich-BipedLab\u002FLiDARTag) - A Real-Time Fiducial Tag using Point Clouds Lidar Data.\n* [multicam_calibration](https:\u002F\u002Fgithub.com\u002FKumarRobotics\u002Fmulticam_calibration) - Extrinsic and intrinsic calbration of cameras.\n* [ikpy](https:\u002F\u002Fgithub.com\u002FPhylliade\u002Fikpy) - An Inverse Kinematics library aiming performance and modularity.\n* [livox_camera_lidar_calibration](https:\u002F\u002Fgithub.com\u002FLivox-SDK\u002Flivox_camera_lidar_calibration) - Calibrate the extrinsic parameters between Livox LiDAR and camera.\n* [lidar_camera_calibration](https:\u002F\u002Fgithub.com\u002Fheethesh\u002Flidar_camera_calibration) - Camera LiDAR Calibration using ROS, OpenCV, and PCL.\n* [e2calib](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Fe2calib) - Contains code that implements video reconstruction from event data for calibration.\n\n\n### Perception Pipeline\n* [SARosPerceptionKitti](https:\u002F\u002Fgithub.com\u002Fappinho\u002FSARosPerceptionKitti) - ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite.\n* [multiple-object-tracking-lidar](https:\u002F\u002Fgithub.com\u002Fpraveen-palanisamy\u002Fmultiple-object-tracking-lidar) - C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud.\n* [cadrl_ros](https:\u002F\u002Fgithub.com\u002Fmfe7\u002Fcadrl_ros) - ROS package for dynamic obstacle avoidance for ground robots trained with deep RL.\n* [AugmentedAutoencoder](https:\u002F\u002Fgithub.com\u002FDLR-RM\u002FAugmentedAutoencoder) - RGB-based pipeline for object detection and 6D pose estimation.\n* [jsk_recognition](https:\u002F\u002Fgithub.com\u002Fjsk-ros-pkg\u002Fjsk_recognition) - A stack for the perception packages which are used in JSK lab.\n* [GibsonEnv](https:\u002F\u002Fgithub.com\u002FStanfordVL\u002FGibsonEnv) - Gibson Environments: Real-World Perception for Embodied Agents.\n* [morefusion](https:\u002F\u002Fgithub.com\u002Fwkentaro\u002Fmorefusion) - Multi-object Reasoning for 6D Pose Estimation from Volumetric Fusion.\n* [se(3)-TrackNet](https:\u002F\u002Fgithub.com\u002Fwenbowen123\u002Firos20-6d-pose-tracking) - A package for 6D pose tracking of dynamic objects when object's CAD model is available.\n\n### Machine Learning\n* [DLIB](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib) - A toolkit for making real world machine learning and data analysis applications in C++.\n* [fastai](https:\u002F\u002Fgithub.com\u002Ffastai\u002Ffastai) - The fastai library simplifies training fast and accurate neural nets using modern best practices.\n* [tpot](https:\u002F\u002Fgithub.com\u002FEpistasisLab\u002Ftpot) - A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.\n* [deap](https:\u002F\u002Fgithub.com\u002FDEAP\u002Fdeap) - Distributed Evolutionary Algorithms in Python.\n* [gym](https:\u002F\u002Fgithub.com\u002Fopenai\u002Fgym) - A toolkit for developing and comparing reinforcement learning algorithms.\n* [tensorflow_ros_cpp](https:\u002F\u002Fgithub.com\u002Ftradr-project\u002Ftensorflow_ros_cpp) - A ROS package that allows to do Tensorflow inference in C++ without the need to compile TF yourself.\n* [Tensorflow Federated](https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Ffederated) - TensorFlow Federated (TFF) is an open-source framework for machine learning and other computations on decentralized data.\n* [finn](https:\u002F\u002Fgithub.com\u002FXilinx\u002Ffinn) - Fast, Scalable Quantized Neural Network Inference on FPGAs.\n* [neuropod](https:\u002F\u002Fgithub.com\u002Fuber\u002Fneuropod) - Neuropod is a library that provides a uniform interface to run deep learning models from multiple frameworks in C++ and Python.\n* [leela-zero](https:\u002F\u002Fgithub.com\u002Fleela-zero\u002Fleela-zero) - This is a fairly faithful reimplementation of the system described in the Alpha Go Zero paper \"Mastering the Game of Go without Human Knowledge\".\n* [Trax](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Ftrax) - A library for deep learning that focuses on sequence models and reinforcement learning.\n* [mlflow](https:\u002F\u002Fgithub.com\u002Fmlflow\u002Fmlflow) - A platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models.\n* [Netron](https:\u002F\u002Fgithub.com\u002Flutzroeder\u002FNetron) - Visualizer for neural network, deep learning and machine learning models.\n* [MNN](https:\u002F\u002Fgithub.com\u002Falibaba\u002FMNN) - A blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba.\n* [Tensorforce](https:\u002F\u002Fgithub.com\u002Ftensorforce\u002Ftensorforce) - An open-source deep reinforcement learning framework, with an emphasis on modularized flexible library design and straightforward usability for applications in research and practice.\n* [Dopamine](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fdopamine) - A research framework for fast prototyping of reinforcement learning algorithms.\n* [catalyst](https:\u002F\u002Fgithub.com\u002Fcatalyst-team\u002Fcatalyst) - Was developed with a focus on reproducibility, fast experimentation and code\u002Fideas reusing.\n* [ray](https:\u002F\u002Fgithub.com\u002Fray-project\u002Fray) - A fast and simple framework for building and running distributed applications.\n* [tf-agents](https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Fagents) - A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.\n* [ReAgent](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002FReAgent) - An open source end-to-end platform for applied reinforcement learning (RL) developed and used at Facebook.\n* [Awesome-Mobile-Machine-Learning](https:\u002F\u002Fgithub.com\u002Ffritzlabs\u002FAwesome-Mobile-Machine-Learning) - A curated list of awesome mobile machine learning resources for iOS, Android, and edge devices.\n* [cnn-explainer](https:\u002F\u002Fgithub.com\u002Fpoloclub\u002Fcnn-explainer) - Learning Convolutional Neural Networks with Interactive Visualization.\n* [modelzoo](https:\u002F\u002Fgithub.com\u002Fautowarefoundation\u002Fmodelzoo) - A collection of machine-learned models for use in autonomous driving applications.\n* [nnstreamer-ros](https:\u002F\u002Fgithub.com\u002Fnnstreamer\u002Fnnstreamer-ros) - A set of Gstreamer plugins and ROS examples that allow Gstreamer developers to adopt neural network models easily and efficiently and neural network developers to manage neural network pipelines and their filters easily and efficiently.\n\n\n### Parallel Processing\n* [dask](https:\u002F\u002Fgithub.com\u002Fdask\u002Fdask) - Parallel computing with task scheduling for Python.\n* [cupy](https:\u002F\u002Fgithub.com\u002Fcupy\u002Fcupy) - NumPy-like API accelerated with CUDA.\n* [Thrust](https:\u002F\u002Fgithub.com\u002Fthrust\u002Fthrust) - A C++ parallel programming library which resembles the C++ Standard Library.\n* [ArrayFire](https:\u002F\u002Fgithub.com\u002Farrayfire\u002Farrayfire) - A general purpose GPU library.\n* [OpenMP](https:\u002F\u002Fwww.openmp.org\u002F) - An application programming interface that supports multi-platform shared memory multiprocessing programming in C, C++, and Fortran.\n* [VexCL](https:\u002F\u002Fgithub.com\u002Fddemidov\u002Fvexcl) - VexCL is a C++ vector expression template library for OpenCL\u002FCUDA\u002FOpenMP.\n* [PYNQ](https:\u002F\u002Fgithub.com\u002FXilinx\u002FPYNQ) - An open-source project from Xilinx that makes it easy to design embedded systems with Zynq All Programmable Systems on Chips.\n* [numba](https:\u002F\u002Fgithub.com\u002Fnumba\u002Fnumba) - NumPy aware dynamic Python compiler using LLVM.\n* [TensorRT](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FTensorRT) - A C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.\n* [libcudacxx](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Flibcudacxx) - Provides a heterogeneous implementation of the C++ Standard Library that can be used in and between CPU and GPU code.\n\n\n### Image Processing\n* [CV-pretrained-model](https:\u002F\u002Fgithub.com\u002Fbalavenkatesh3322\u002FCV-pretrained-model) - A collection of computer vision pre-trained models.\n* [image_pipeline](https:\u002F\u002Fgithub.com\u002Fros-perception\u002Fimage_pipeline) - Fills the gap between getting raw images from a camera driver and higher-level vision processing.\n* [gstreamer](https:\u002F\u002Fgstreamer.freedesktop.org\u002F) - A pipeline-based multimedia framework that links together a wide variety of media processing systems to complete complex workflows.\n* [ros2_openvino_toolkit](https:\u002F\u002Fgithub.com\u002Fintel\u002Fros2_openvino_toolkit) -  Provides a ROS-adaptered runtime framework of neural network which quickly deploys applications and solutions for vision inference.\n* [vision_visp](https:\u002F\u002Fgithub.com\u002Flagadic\u002Fvision_visp) - Wraps the ViSP moving edge tracker provided by the ViSP visual servoing library into a ROS package.\n* [apriltag_ros](https:\u002F\u002Fgithub.com\u002FAprilRobotics\u002Fapriltag_ros) - A ROS wrapper of the AprilTag 3 visual fiducial detector.\n* [deep_object_pose](https:\u002F\u002Fgithub.com\u002FNVlabs\u002FDeep_Object_Pose) - Deep Object Pose Estimation.\n* [DetectAndTrack](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002FDetectAndTrack) - Detect-and-Track: Efficient Pose.\n* [SfMLearner](https:\u002F\u002Fgithub.com\u002Ftinghuiz\u002FSfMLearner) - An unsupervised learning framework for depth and ego-motion estimation.\n* [imgaug](https:\u002F\u002Fgithub.com\u002Faleju\u002Fimgaug) - Image augmentation for machine learning experiments.\n* [vision_opencv](https:\u002F\u002Fgithub.com\u002Fros-perception\u002Fvision_opencv) - Packages for interfacing ROS with OpenCV, a library of programming functions for real time computer vision.\n* [darknet_ros](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fdarknet_ros) - YOLO ROS: Real-Time Object Detection for ROS.\n* [ros_ncnn](https:\u002F\u002Fgithub.com\u002Fnilseuropa\u002Fros_ncnn) - YOLACT \u002F YOLO *( among other things )* on NCNN inference engine for ROS.\n* [tf-pose-estimation](https:\u002F\u002Fgithub.com\u002Fildoonet\u002Ftf-pose-estimation) - Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.\n* [find-object](https:\u002F\u002Fgithub.com\u002Fintrolab\u002Ffind-object) - Simple Qt interface to try OpenCV implementations of SIFT, SURF, FAST, BRIEF and other feature detectors and descriptors.\n* [yolact](https:\u002F\u002Fgithub.com\u002Fdbolya\u002Fyolact) - A simple, fully convolutional model for real-time instance segmentation.\n* [Kimera-Semantics](https:\u002F\u002Fgithub.com\u002FMIT-SPARK\u002FKimera-Semantics) - Real-Time 3D Semantic Reconstruction from 2D data.\n* [detectron2](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fdetectron2) - A next-generation research platform for object detection and segmentation.\n* [OpenVX](https:\u002F\u002Fwww.khronos.org\u002Fopenvx\u002F) -  Enables performance and power-optimized computer vision processing, especially important in embedded and real-time use cases.\n* [3d-vehicle-tracking](https:\u002F\u002Fgithub.com\u002Fucbdrive\u002F3d-vehicle-tracking) - Official implementation of Joint Monocular 3D Vehicle Detection and Tracking.\n* [pysot](https:\u002F\u002Fgithub.com\u002FSTVIR\u002Fpysot) - The goal of PySOT is to provide a high-quality, high-performance codebase for visual tracking research.\n* [semantic_slam](https:\u002F\u002Fgithub.com\u002Ffloatlazer\u002Fsemantic_slam) - Real time semantic slam in ROS with a hand held RGB-D camera.\n* [kitti_scan_unfolding](https:\u002F\u002Fgithub.com\u002Fltriess\u002Fkitti_scan_unfolding) - We propose KITTI scan unfolding in our paper Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study.\n* [packnet-sfm](https:\u002F\u002Fgithub.com\u002FTRI-ML\u002Fpacknet-sfm) - Official PyTorch implementation of self-supervised monocular depth estimation methods invented by the ML Team at Toyota Research Institute (TRI).\n* [AB3DMOT](https:\u002F\u002Fgithub.com\u002Fxinshuoweng\u002FAB3DMOT) - This work proposes a simple yet accurate real-time baseline 3D multi-object tracking system.\n* [monoloco](https:\u002F\u002Fgithub.com\u002Fvita-epfl\u002Fmonoloco) - Official implementation of \"MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation\" in PyTorch.\n* [Poly-YOLO](https:\u002F\u002Fgitlab.com\u002Firafm-ai\u002Fpoly-yolo) - Builds on the original ideas of YOLOv3 and removes two of its weaknesses: a large amount of rewritten labels and inefficient distribution of anchors.\n* [satellite-image-deep-learning](https:\u002F\u002Fgithub.com\u002Frobmarkcole\u002Fsatellite-image-deep-learning) - Resources for deep learning with satellite & aerial imagery.\n* [robosat](https:\u002F\u002Fgithub.com\u002Fmapbox\u002Frobosat) - Semantic segmentation on aerial and satellite imagery.\n* [big_transfer](https:\u002F\u002Fgithub.com\u002Fgoogle-research\u002Fbig_transfer) - Model for General Visual Representation Learning created by Google Research.\n* [LEDNet](https:\u002F\u002Fgithub.com\u002Fxiaoyufenfei\u002FLEDNet) - A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation.\n* [TorchSeg](https:\u002F\u002Fgithub.com\u002Fycszen\u002FTorchSeg) - This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch.\n* [simpledet](https:\u002F\u002Fgithub.com\u002Ftusimple\u002Fsimpledet) - A Simple and Versatile Framework for Object Detection and Instance Recognition.\n* [meshroom](https:\u002F\u002Fgithub.com\u002Falicevision\u002Fmeshroom) - Meshroom is a free, open-source 3D Reconstruction Software based on the AliceVision Photogrammetric Computer Vision framework.\n* [EasyOCR](https:\u002F\u002Fgithub.com\u002FJaidedAI\u002FEasyOCR) - Ready-to-use Optical character recognition (OCR) with 40+ languages supported including Chinese, Japanese, Korean and Thai.\n* [pytracking](https:\u002F\u002Fgithub.com\u002Fvisionml\u002Fpytracking) - A general python framework for visual object tracking and video object segmentation, based on PyTorch.\n* [ros_deep_learning](https:\u002F\u002Fgithub.com\u002Fdusty-nv\u002Fros_deep_learning) - Deep learning inference nodes for ROS with support for NVIDIA Jetson TX1\u002FTX2\u002FXavier and TensorRT.\n* [hyperpose](https:\u002F\u002Fgithub.com\u002Ftensorlayer\u002Fhyperpose) - HyperPose: A Flexible Library for Real-time Human Pose Estimation.\n* [fawkes](https:\u002F\u002Fgithub.com\u002FShawn-Shan\u002Ffawkes) - Privacy preserving tool against facial recognition systems.\n* [anonymizer](https:\u002F\u002Fgithub.com\u002Funderstand-ai\u002Fanonymizer) - An anonymizer to obfuscate faces and license plates.\n* [opendatacam](https:\u002F\u002Fgithub.com\u002Fopendatacam\u002Fopendatacam) - Only saves surveyed meta-data, in particular the path an object moved or number of counted objects at a certain point.\n* [Cam2BEV](https:\u002F\u002Fgithub.com\u002Fika-rwth-aachen\u002FCam2BEV) - TensorFlow Implementation for Computing a Semantically Segmented Bird's Eye View (BEV) Image Given the Images of Multiple Vehicle-Mounted Cameras.\n* [flownet2-pytorch](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fflownet2-pytorch) - Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks.\n* [Simd](https:\u002F\u002Fgithub.com\u002Fermig1979\u002FSimd) - C++ image processing and machine learning library with using of SIMD: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2, AVX-512, VMX(Altivec) and VSX(Power7), NEON for ARM.\n* [AliceVision](https:\u002F\u002Fgithub.com\u002Falicevision\u002FAliceVision) - A Photogrammetric Computer Vision Framework which provides a 3D Reconstruction and Camera Tracking algorithms.\n* [satpy](https:\u002F\u002Fgithub.com\u002Fpytroll\u002Fsatpy) - A python library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats.\n* [eo-learn](https:\u002F\u002Fgithub.com\u002Fsentinel-hub\u002Feo-learn) - A collection of open source Python packages that have been developed to seamlessly access and process spatio-temporal image sequences acquired by any satellite fleet in a timely and automatic manner.\n* [libvips](https:\u002F\u002Fgithub.com\u002Flibvips\u002Flibvips) - A fast image processing library with low memory needs.\n\n\n### Radar Processing\n* [pyroSAR](https:\u002F\u002Fgithub.com\u002Fjohntruckenbrodt\u002FpyroSAR) - Framework for large-scale SAR satellite data processing.\n* [CameraRadarFusionNet](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002FCameraRadarFusionNet) - TUM Roborace Team Software Stack - Path tracking control, velocity control, curvature control and state estimation.\n\n\n### Lidar and Point Cloud Processing\n* [cilantro](https:\u002F\u002Fgithub.com\u002Fkzampog\u002Fcilantro) - A lean C++ library for working with point cloud data.\n* [open3d](https:\u002F\u002Fgithub.com\u002Fintel-isl\u002FOpen3D) - Open3D: A Modern Library for 3D Data Processing.\n* [SqueezeSeg](https:\u002F\u002Fgithub.com\u002FBichenWuUCB\u002FSqueezeSeg) - Implementation of SqueezeSeg, convolutional neural networks for LiDAR point clout segmentation.\n* [point_cloud_io](https:\u002F\u002Fgithub.com\u002FANYbotics\u002Fpoint_cloud_io) - ROS nodes to read and write point clouds from and to files (e.g. ply, vtk).\n* [python-pcl](https:\u002F\u002Fgithub.com\u002Fstrawlab\u002Fpython-pcl) - Python bindings to the pointcloud library.\n* [libpointmatcher](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Flibpointmatcher) - An \"Iterative Closest Point\" library for 2-D\u002F3-D mapping in Robotics.\n* [depth_clustering](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fdepth_clustering) - Fast and robust clustering of point clouds generated with a Velodyne sensor.\n* [lidar-bonnetal](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Flidar-bonnetal) - Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving.\n* [CSF](https:\u002F\u002Fgithub.com\u002Fjianboqi\u002FCSF) - LiDAR point cloud ground filtering \u002F segmentation (bare earth extraction) method based on cloth simulation.\n* [robot_body_filter](https:\u002F\u002Fgithub.com\u002Fpeci1\u002Frobot_body_filter) - A highly configurable LaserScan\u002FPointCloud2 filter that allows to dynamically remove the 3D body of the robot from the measurements.\n* [grid_map](https:\u002F\u002Fgithub.com\u002FANYbotics\u002Fgrid_map) - Universal grid map library for mobile robotic mapping.\n* [elevation_mapping](https:\u002F\u002Fgithub.com\u002FANYbotics\u002Felevation_mapping) - Robot-centric elevation mapping for rough terrain navigation.\n* [rangenet_lib](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Frangenet_lib) - Contains simple usage explanations of how the RangeNet++ inference works with the TensorRT and C++ interface.\n* [pointcloud_to_laserscan](https:\u002F\u002Fgithub.com\u002Fros-perception\u002Fpointcloud_to_laserscan) - Converts a 3D Point Cloud into a 2D laser scan.\n* [octomap](https:\u002F\u002Fgithub.com\u002FOctoMap\u002Foctomap) - An Efficient Probabilistic 3D Mapping Framework Based on Octrees.\n* [pptk](https:\u002F\u002Fgithub.com\u002Fheremaps\u002Fpptk) - Point Processing Toolkit from HEREMaps.\n* [gpu-voxels](https:\u002F\u002Fwww.gpu-voxels.org\u002F) - GPU-Voxels is a CUDA based library which allows high resolution volumetric collision detection between animated 3D models and live pointclouds from 3D sensors of all kinds.\n* [spatio_temporal_voxel_layer](https:\u002F\u002Fgithub.com\u002FSteveMacenski\u002Fspatio_temporal_voxel_layer) - A new voxel layer leveraging modern 3D graphics tools to modernize navigation environmental representations.\n* [LAStools](https:\u002F\u002Fgithub.com\u002FLAStools\u002FLAStools) - Award-winning software for efficient LiDAR processing.\n* [PCDet](https:\u002F\u002Fgithub.com\u002Fsshaoshuai\u002FPCDet) - A general PyTorch-based codebase for 3D object detection from point cloud.\n* [PDAL](https:\u002F\u002Fgithub.com\u002FPDAL\u002FPDAL) - A C++ BSD library for translating and manipulating point cloud data.\n* [PotreeConverter](https:\u002F\u002Fgithub.com\u002Fpotree\u002FPotreeConverter) - Builds a potree octree from las, laz, binary ply, xyz or ptx files.\n* [fast_gicp](https:\u002F\u002Fgithub.com\u002FSMRT-AIST\u002Ffast_gicp) - A collection of GICP-based fast point cloud registration algorithms.\n* [ndt_omp](https:\u002F\u002Fgithub.com\u002Fkoide3\u002Fndt_omp) - Multi-threaded and SSE friendly NDT algorithm.\n* [laser_line_extraction](https:\u002F\u002Fgithub.com\u002Fkam3k\u002Flaser_line_extraction) - A ROS packages that extracts line segments from LaserScan messages.\n* [Go-ICP](https:\u002F\u002Fgithub.com\u002Fyangjiaolong\u002FGo-ICP) - Implementation of the Go-ICP algorithm for globally optimal 3D pointset registration.\n* [PointCNN](https:\u002F\u002Fgithub.com\u002Fyangyanli\u002FPointCNN) - A simple and general framework for feature learning from point clouds.\n* [segmenters_lib](https:\u002F\u002Fgithub.com\u002FLidarPerception\u002Fsegmenters_lib) - The LiDAR segmenters library, for segmentation-based detection.\n* [MotionNet](https:\u002F\u002Fgithub.com\u002Fpxiangwu\u002FMotionNet) - Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps.\n* [PolarSeg](https:\u002F\u002Fgithub.com\u002Fedwardzhou130\u002FPolarSeg) - An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation.\n* [traversability_mapping](https:\u002F\u002Fgithub.com\u002FTixiaoShan\u002Ftraversability_mapping) - Takes in point cloud from a Velodyne VLP-16 Lidar and outputs a traversability map for autonomous navigation in real-time.\n* [lidar_super_resolution](https:\u002F\u002Fgithub.com\u002FRobustFieldAutonomyLab\u002Flidar_super_resolution) - Simulation-based Lidar Super-resolution for Ground Vehicles.\n* [Cupoch](https:\u002F\u002Fgithub.com\u002Fneka-nat\u002Fcupoch) -  A library that implements rapid 3D data processing and robotics computation using CUDA.\n* [linefit_ground_segmentation](https:\u002F\u002Fgithub.com\u002Florenwel\u002Flinefit_ground_segmentation) - Implementation of the ground segmentation algorithm.\n* [Draco](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fdraco) - A library for compressing and decompressing 3D geometric meshes and point clouds.\n* [Votenet](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fvotenet) - Deep Hough Voting for 3D Object Detection in Point Clouds.\n* [lidar_undistortion](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Flidar_undistortion) - Provides lidar motion undistortion based on an external 6DoF pose estimation input.\n* [superpoint_graph](https:\u002F\u002Fgithub.com\u002Floicland\u002Fsuperpoint_graph) - Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs.\n* [RandLA-Net](https:\u002F\u002Fgithub.com\u002FQingyongHu\u002FRandLA-Net) - Efficient Semantic Segmentation of Large-Scale Point Clouds.\n* [Det3D](https:\u002F\u002Fgithub.com\u002Fpoodarchu\u002FDet3D) - A first 3D Object Detection toolbox which provides off the box implementations of many 3D object detection algorithms such as PointPillars, SECOND, PIXOR.\n* [OverlapNet](https:\u002F\u002Fgithub.com\u002FPRBonn\u002FOverlapNet) - A modified Siamese Network that predicts the overlap and relative yaw angle of a pair of range images generated by 3D LiDAR scans.\n* [mp2p_icp](https:\u002F\u002Fgithub.com\u002FMOLAorg\u002Fmp2p_icp) - A repertory of multi primitive-to-primitive (MP2P) ICP algorithms in C++.\n* [OpenPCDet](https:\u002F\u002Fgithub.com\u002Fopen-mmlab\u002FOpenPCDet) - A Toolbox for LiDAR-based 3D Object Detection.\n* [torch-points3d](https:\u002F\u002Fgithub.com\u002Fnicolas-chaulet\u002Ftorch-points3d) - Pytorch framework for doing deep learning on point clouds.\n* [PolyFit](https:\u002F\u002Fgithub.com\u002FLiangliangNan\u002FPolyFit) - Polygonal Surface Reconstruction from Point Clouds.\n* [mmdetection3d](https:\u002F\u002Fgithub.com\u002Fopen-mmlab\u002Fmmdetection3d) - Next-generation platform for general 3D object detection.\n* [gpd](https:\u002F\u002Fgithub.com\u002Fatenpas\u002Fgpd) - Takes a point cloud as input and produces pose estimates of viable grasps as output.\n* [SalsaNext](https:\u002F\u002Fgithub.com\u002FTiagoCortinhal\u002FSalsaNext) - Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving.\n* [Super-Fast-Accurate-3D-Object-Detection](https:\u002F\u002Fgithub.com\u002Fmaudzung\u002FSuper-Fast-Accurate-3D-Object-Detection) - Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation).\n* [kaolin](https:\u002F\u002Fgithub.com\u002FNVIDIAGameWorks\u002Fkaolin) - A PyTorch Library for Accelerating 3D Deep Learning Research.\n* [CamVox](https:\u002F\u002Fgithub.com\u002FISEE-Technology\u002FCamVox) - A low-cost SLAM system based on camera and Livox lidar.\n* [SA-SSD](https:\u002F\u002Fgithub.com\u002Fskyhehe123\u002FSA-SSD) - Structure Aware Single-stage 3D Object Detection from Point Cloud.\n* [cuda-pcl](https:\u002F\u002Fgithub.com\u002FNVIDIA-AI-IOT\u002Fcuda-pcl) - Accelerating Lidar for Robotics with NVIDIA CUDA-based PCL.\n* [urban_road_filter](https:\u002F\u002Fgithub.com\u002Fjkk-research\u002Furban_road_filter) - Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles.\n* [Removert](https:\u002F\u002Fgithub.com\u002Firapkaist\u002Fremovert) - Remove then revert. Static map construction in the wild and dynamic points removing tool by constructing a static map.\n* [KISS-ICP](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fkiss-icp) - A LiDAR Odometry pipeline that just works on most of the cases without tunning any parameter.\n\n## Localization and State Estimation\n* [evo](https:\u002F\u002Fgithub.com\u002FMichaelGrupp\u002Fevo) - Python package for the evaluation of odometry and SLAM.\n* [robot_localization](https:\u002F\u002Fgithub.com\u002Fcra-ros-pkg\u002Frobot_localization) - A package of nonlinear state estimation nodes.\n* [fuse](https:\u002F\u002Fgithub.com\u002Flocusrobotics\u002Ffuse) - General architecture for performing sensor fusion live on a robot.\n* [GeographicLib](https:\u002F\u002Fgithub.com\u002FSciumo\u002FGeographicLib) - A C++ library for geographic projections.\n* [ntripbrowser](https:\u002F\u002Fgithub.com\u002Femlid\u002Fntripbrowser) - A Python API for browsing NTRIP (Networked Transport of RTCM via Internet Protocol).\n* [imu_tools](https:\u002F\u002Fgithub.com\u002Fccny-ros-pkg\u002Fimu_tools) - IMU-related filters and visualizers.\n* [RTKLIB](https:\u002F\u002Fgithub.com\u002Frtklibexplorer\u002FRTKLIB) - A version of RTKLIB optimized for single and dual frequency low cost GPS receivers, especially u-blox receivers.\n* [gLAB](https:\u002F\u002Fgage.upc.edu\u002FgLAB\u002F) - Performs precise modeling of GNSS observables (pseudorange and carrier phase) at the centimetre level, allowing standalone GPS positioning, PPP, SBAS and DGNSS.\n* [ai-imu-dr](https:\u002F\u002Fgithub.com\u002Fmbrossar\u002Fai-imu-dr) - Contains the code of our novel accurate method for dead reckoning of wheeled vehicles based only on an IMU.\n* [Kalman-and-Bayesian-Filters-in-Python](https:\u002F\u002Fgithub.com\u002Frlabbe\u002FKalman-and-Bayesian-Filters-in-Python) - Kalman Filter book using Jupyter Notebook.\n* [mcl_3dl](https:\u002F\u002Fgithub.com\u002Fat-wat\u002Fmcl_3dl) - A ROS node to perform a probabilistic 3-D\u002F6-DOF localization system for mobile robots with 3-D LIDAR(s).\n* [se2lam](https:\u002F\u002Fgithub.com\u002Fizhengfan\u002Fse2lam) - On-SE(2) Localization and Mapping for Ground Vehicles by Fusing Odometry and Vision.\n* [mmWave-localization-learning](https:\u002F\u002Fgithub.com\u002Fgante\u002FmmWave-localization-learning) - ML-based positioning method from mmWave transmissions - with high accuracy and energy efficiency.\n* [dynamic_robot_localization](https:\u002F\u002Fgithub.com\u002Fcarlosmccosta\u002Fdynamic_robot_localization) - A ROS package that offers 3 DoF and 6 DoF localization using PCL and allows dynamic map update using OctoMap.\n* [eagleye](https:\u002F\u002Fgithub.com\u002FMapIV\u002Feagleye) -  An open-source software for vehicle localization utilizing GNSS and IMU.\n* [python-sgp4](https:\u002F\u002Fgithub.com\u002Fbrandon-rhodes\u002Fpython-sgp4) - Python version of the SGP4 satellite position library.\n* [PROJ](https:\u002F\u002Fgithub.com\u002FOSGeo\u002FPROJ) - Cartographic Projections and Coordinate Transformations Library.\n* [rpg_trajectory_evaluation](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Frpg_trajectory_evaluation) -  Implements common used trajectory evaluation methods for visual(-inertial) odometry.\n* [pymap3d](https:\u002F\u002Fgithub.com\u002Fgeospace-code\u002Fpymap3d) - Pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef enu eci.\n* [libRSF](https:\u002F\u002Fgithub.com\u002FTUC-ProAut\u002FlibRSF) - A robust sensor fusion library for online localization.\n\n## Simultaneous Localization and Mapping\n### Lidar\n* [KISS-ICP](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fkiss-icp) - A LiDAR Odometry pipeline that just works on most of the cases without tunning any parameter.\n* [loam_velodyne](https:\u002F\u002Fgithub.com\u002Flaboshinl\u002Floam_velodyne) - Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.\n* [lio-mapping](https:\u002F\u002Fgithub.com\u002Fhyye\u002Flio-mapping) - Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping).\n* [A-LOAM](https:\u002F\u002Fgithub.com\u002FHKUST-Aerial-Robotics\u002FA-LOAM) - Advanced implementation of LOAM.\n* [Fast LOAM](https:\u002F\u002Fgithub.com\u002Fwh200720041\u002Ffloam) - Fast and Optimized Lidar Odometry And Mapping.\n* [LIO_SAM](https:\u002F\u002Fgithub.com\u002FTixiaoShan\u002FLIO-SAM) - Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping.\n* [cartographer_ros](https:\u002F\u002Fgithub.com\u002Fgooglecartographer\u002Fcartographer_ros) - Provides ROS integration for Cartographer.\n* [loam_livox](https:\u002F\u002Fgithub.com\u002Fhku-mars\u002Floam_livox) - A robust LiDAR Odometry and Mapping (LOAM) package for Livox-LiDAR.\n* [StaticMapping](https:\u002F\u002Fgithub.com\u002FEdwardLiuyc\u002FStaticMapping) - Use LiDAR to map the static world.\n* [semantic_suma](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fsemantic_suma\u002F) - Semantic Mapping using Surfel Mapping and Semantic Segmentation.\n* [slam_toolbox](https:\u002F\u002Fgithub.com\u002FSteveMacenski\u002Fslam_toolbox) - Slam Toolbox for lifelong mapping and localization in potentially massive maps with ROS .\n* [maplab](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fmaplab) - An open visual-inertial mapping framework.\n* [hdl_graph_slam](https:\u002F\u002Fgithub.com\u002Fkoide3\u002Fhdl_graph_slam) - An open source ROS package for real-time 6DOF SLAM using a 3D LIDAR.\n* [interactive_slam](https:\u002F\u002Fgithub.com\u002FSMRT-AIST\u002Finteractive_slam) -  In contrast to existing automatic SLAM packages, we with minimal human effort.\n* [LeGO-LOAM](https:\u002F\u002Fgithub.com\u002FRobustFieldAutonomyLab\u002FLeGO-LOAM) - Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain.\n* [pyslam](https:\u002F\u002Fgithub.com\u002Fluigifreda\u002Fpyslam) - Contains a monocular Visual Odometry (VO) pipeline in Python.\n* [Kitware SLAM](https:\u002F\u002Fgitlab.kitware.com\u002Fkeu-computervision\u002Fslam\u002F) -  LiDAR-only visual SLAM developped by Kitware, as well as ROS and ParaView wrappings for easier use.\n* [horizon_highway_slam](https:\u002F\u002Fgithub.com\u002FLivox-SDK\u002Fhorizon_highway_slam) - A robust, low drift, and real time highway SLAM package suitable for Livox Horizon lidar.\n* [mola](https:\u002F\u002Fgithub.com\u002FMOLAorg\u002Fmola) - A Modular System for Localization and Mapping.\n* [DH3D](https:\u002F\u002Fgithub.com\u002FJuanDuGit\u002FDH3D) - Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DOF Relocalization.\n* [LaMa](https:\u002F\u002Fgithub.com\u002Firis-ua\u002Firis_lama) - LaMa is a C++11 software library for robotic localization and mapping.\n* [Scan Context](https:\u002F\u002Fgithub.com\u002Firapkaist\u002Fscancontext) - Global LiDAR descriptor for place recognition and long-term localization.\n* [M-LOAM](https:\u002F\u002Fgithub.com\u002Fgogojjh\u002FM-LOAM) - Robust Odometry and Mapping for Multi-LiDAR Systems with Online Extrinsic Calibration.\n\n\n### Visual\n* [orb_slam_2_ros](https:\u002F\u002Fgithub.com\u002FappliedAI-Initiative\u002Forb_slam_2_ros) - A ROS implementation of ORB_SLAM2.\n* [orbslam-map-saving-extension](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Forbslam-map-saving-extension) - In this extensions the map of ORB-features be saved to the disk as a reference for future runs along the same track.\n* [dso](https:\u002F\u002Fgithub.com\u002FJakobEngel\u002Fdso\u002F) - Direct Sparse Odometry.\n* [viso2](https:\u002F\u002Fgithub.com\u002Fsrv\u002Fviso2) - A ROS wrapper for libviso2, a library for visual odometry.\n* [xivo](https:\u002F\u002Fgithub.com\u002Fucla-vision\u002Fxivo) - X Inertial-aided Visual Odometry.\n* [rovio](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Frovio) - Robust Visual Inertial Odometry Framework.\n* [LSD-SLAM](https:\u002F\u002Fgithub.com\u002Ftum-vision\u002Flsd_slam) - Large-Scale Direct Monocular SLAM is a real-time monocular SLAM.\n* [CubeSLAM and ORB SLAM](https:\u002F\u002Fgithub.com\u002Fshichaoy\u002Fcube_slam) - Monocular 3D Object Detection and SLAM Package of CubeSLAM and ORB SLAM.\n* [VINS-Fusion](https:\u002F\u002Fgithub.com\u002FHKUST-Aerial-Robotics\u002FVINS-Fusion) - A Robust and Versatile Multi-Sensor Visual-Inertial State Estimator.\n* [openvslam](https:\u002F\u002Fgithub.com\u002Fxdspacelab\u002Fopenvslam) - OpenVSLAM: A Versatile Visual SLAM Framework.\n* [basalt](https:\u002F\u002Fgitlab.com\u002FVladyslavUsenko\u002Fbasalt) - Visual-Inertial Mapping with Non-Linear Factor Recovery.\n* [Kimera](https:\u002F\u002Fgithub.com\u002FMIT-SPARK\u002FKimera) - A C++ library for real-time metric-semantic simultaneous localization and mapping, which uses camera images and inertial data to build a semantically annotated 3D mesh of the environment.\n* [tagslam](https:\u002F\u002Fgithub.com\u002Fberndpfrommer\u002Ftagslam) - A ROS-based package for Simultaneous Localization and Mapping using AprilTag fiducial markers.\n* [LARVIO](https:\u002F\u002Fgithub.com\u002FPetWorm\u002FLARVIO) - A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.\n* [fiducials](https:\u002F\u002Fgithub.com\u002FUbiquityRobotics\u002Ffiducials) - Simultaneous localization and mapping using fiducial markers.\n* [open_vins](https:\u002F\u002Fgithub.com\u002Frpng\u002Fopen_vins) - An open source platform for visual-inertial navigation research.\n* [ORB_SLAM3](https:\u002F\u002Fgithub.com\u002FUZ-SLAMLab\u002FORB_SLAM3) - ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM.\n* [Atlas](https:\u002F\u002Fgithub.com\u002Fmagicleap\u002FAtlas) - End-to-End 3D Scene Reconstruction from Posed Images.\n* [vilib](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Fvilib) - This library focuses on the front-end of VIO pipelines with CUDA.\n* [hloc](https:\u002F\u002Fgithub.com\u002Fcvg\u002FHierarchical-Localization) - A modular toolbox for state-of-the-art 6-DoF visual localization. It implements Hierarchical Localization, leveraging image retrieval and feature matching, and is fast, accurate, and scalable.\n* [ESVO](https:\u002F\u002Fgithub.com\u002FHKUST-Aerial-Robotics\u002FESVO) - A novel pipeline for real-time visual odometry using a stereo event-based camera.\n* [gradslam](https:\u002F\u002Fgithub.com\u002Fgradslam\u002Fgradslam) - An open source differentiable dense SLAM library for PyTorch.\n\n\n### Vector Map\n* [OpenDRIVE](http:\u002F\u002Fwww.opendrive.org\u002Findex.html) - An open file format for the logical description of road networks.\n* [MapsModelsImporter](https:\u002F\u002Fgithub.com\u002Feliemichel\u002FMapsModelsImporter) - A Blender add-on to import models from google maps.\n* [Lanelet2](https:\u002F\u002Fgithub.com\u002Ffzi-forschungszentrum-informatik\u002FLanelet2) - Map handling framework for automated driving.\n* [barefoot](https:\u002F\u002Fgithub.com\u002Fbmwcarit\u002Fbarefoot) -  Online and Offline map matching that can be used stand-alone and in the cloud.\n* [iD](https:\u002F\u002Fgithub.com\u002Fopenstreetmap\u002FiD) - The easy-to-use OpenStreetMap editor in JavaScript.\n* [RapiD](https:\u002F\u002Fgithub.com\u002Ffacebookincubator\u002FRapiD) - An enhanced version of iD for mapping with AI created by Facebook.\n* [segmap](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fsegmap) - A map representation based on 3D segments.\n* [Mapbox](https:\u002F\u002Fgithub.com\u002Fmapbox\u002Fmapbox-gl-js) - A JavaScript library for interactive, customizable vector maps on the web.\n* [osrm-backend](https:\u002F\u002Fgithub.com\u002FProject-OSRM\u002Fosrm-backend) - Open Source Routing Machine - C++ backend.\n* [assuremapingtools](https:\u002F\u002Fgithub.com\u002Fhatem-darweesh\u002Fassuremapingtools) -  Desktop based tool for viewing, editing and saving road network maps for autonomous vehicle platforms such as Autoware.\n* [geopandas](https:\u002F\u002Fgithub.com\u002Fgeopandas\u002Fgeopandas) - A project to add support for geographic data to pandas objects.\n* [MapToolbox](https:\u002F\u002Fgithub.com\u002Fautocore-ai\u002FMapToolbox) - Plugins to make Autoware vector maps in Unity.\n* [imagery-index](https:\u002F\u002Fgithub.com\u002Fideditor\u002Fimagery-index) - An index of aerial and satellite imagery useful for mapping.\n* [mapillary_tools](https:\u002F\u002Fgithub.com\u002Fmapillary\u002Fmapillary_tools) - A library for processing and uploading images to Mapillary.\n* [mapnik](https:\u002F\u002Fgithub.com\u002Fmapnik\u002Fmapnik) - Combines pixel-perfect image output with lightning-fast cartographic algorithms, and exposes interfaces in C++, Python, and Node.\n* [gdal](https:\u002F\u002Fgithub.com\u002FOSGeo\u002Fgdal) - GDAL is an open source X\u002FMIT licensed translator library for raster and vector geospatial data formats.\n* [grass](https:\u002F\u002Fgithub.com\u002FOSGeo\u002Fgrass) - GRASS GIS - free and open source Geographic Information System (GIS).\n* [3d-tiles](https:\u002F\u002Fgithub.com\u002FCesiumGS\u002F3d-tiles) - Specification for streaming massive heterogeneous 3D geospatial datasets.\n* [osmnx](https:\u002F\u002Fgithub.com\u002Fgboeing\u002Fosmnx) - Python for street networks. Retrieve, model, analyze, and visualize street networks and other spatial data from OpenStreetMap.\n\n## Prediction\n* [Awesome-Interaction-aware-Trajectory-Prediction](https:\u002F\u002Fgithub.com\u002Fjiachenli94\u002FAwesome-Interaction-aware-Trajectory-Prediction) - A selection of state-of-the-art research materials on trajectory prediction.\n* [sgan](https:\u002F\u002Fgithub.com\u002Fagrimgupta92\u002Fsgan) -  Socially Acceptable Trajectories with Generative Adversarial Networks.\n\n## Behavior and Decision\n* [Groot](https:\u002F\u002Fgithub.com\u002FBehaviorTree\u002FGroot) - Graphical Editor to create BehaviorTrees. Compliant with BehaviorTree.CPP.\n* [BehaviorTree.CPP](https:\u002F\u002Fgithub.com\u002FBehaviorTree\u002FBehaviorTree.CPP) - Behavior Trees Library in C++.\n* [RAFCON](https:\u002F\u002Fgithub.com\u002FDLR-RM\u002FRAFCON) - Uses hierarchical state machines, featuring concurrent state execution, to represent robot programs.\n* [ROSPlan](https:\u002F\u002Fgithub.com\u002FKCL-Planning\u002FROSPlan) - Generic framework for task planning in a ROS system.\n* [ad-rss-lib](https:\u002F\u002Fgithub.com\u002Fintel\u002Fad-rss-lib) - Library implementing the Responsibility Sensitive Safety model (RSS) for Autonomous Vehicles.\n* [FlexBE](https:\u002F\u002Fflexbe.github.io\u002F) - Graphical editor for hierarchical state machines, based on ROS's smach.\n* [sts_bt_library](https:\u002F\u002Fgithub.com\u002FAutonomous-Logistics\u002Fsts_bt_library) - This library provides the functionality to set up your own behavior tree logic by using the defined tree structures like Fallback, Sequence or Parallel Nodes.\n* [SMACC](https:\u002F\u002Fgithub.com\u002Freelrbtx\u002FSMACC) - An Event-Driven, Asynchronous, Behavioral State Machine Library for real-time ROS (Robotic Operating System) applications written in C++ .\n* [py_trees_ros](https:\u002F\u002Fgithub.com\u002Fsplintered-reality\u002Fpy_trees_ros) - Behaviours, trees and utilities that extend py_trees for use with ROS.\n\n## Planning and Control\n* [pacmod](https:\u002F\u002Fgithub.com\u002Fastuff\u002Fpacmod) -  Designed to allow the user to control a vehicle with the PACMod drive-by-wire system.\n* [mpcc](https:\u002F\u002Fgithub.com\u002Falexliniger\u002FMPCC) - Model Predictive Contouring Controller for Autonomous Racing.\n* [rrt](https:\u002F\u002Fgithub.com\u002FRoboJackets\u002Frrt) - C++ RRT (Rapidly-exploring Random Tree) implementation.\n* [HypridAStarTrailer](https:\u002F\u002Fgithub.com\u002FAtsushiSakai\u002FHybridAStarTrailer) - A path planning algorithm based on Hybrid A* for trailer truck.\n* [path_planner](https:\u002F\u002Fgithub.com\u002Fkarlkurzer\u002Fpath_planner) - Hybrid A* Path Planner for the KTH Research Concept Vehicle.\n* [open_street_map](https:\u002F\u002Fgithub.com\u002Fros-geographic-info\u002Fopen_street_map) - ROS packages for working with Open Street Map geographic information.\n* [Open Source Car Control](https:\u002F\u002Fgithub.com\u002FPolySync\u002Foscc) -  An assemblage of software and hardware designs that enable computer control of modern cars in order to facilitate the development of autonomous vehicle technology.\n* [fastrack](https:\u002F\u002Fgithub.com\u002FHJReachability\u002Ffastrack) - A ROS implementation of Fast and Safe Tracking (FaSTrack).\n* [commonroad](https:\u002F\u002Fcommonroad.in.tum.de\u002F) - Composable benchmarks for motion planning on roads.\n* [traffic-editor](https:\u002F\u002Fgithub.com\u002Fosrf\u002Ftraffic-editor) - A graphical editor for robot traffic flows.\n* [steering_functions](https:\u002F\u002Fgithub.com\u002Fhbanzhaf\u002Fsteering_functions) - Contains a C++ library that implements steering functions for car-like robots with limited turning radius.\n* [moveit](https:\u002F\u002Fmoveit.ros.org\u002F) - Easy-to-use robotics manipulation platform for developing applications, evaluating designs, and building integrated products.\n* [flexible-collision-library](https:\u002F\u002Fgithub.com\u002Fflexible-collision-library\u002Ffcl) - A library for performing three types of proximity queries on a pair of geometric models composed of triangles.\n* [aikido](https:\u002F\u002Fgithub.com\u002Fpersonalrobotics\u002Faikido) - Artificial Intelligence for Kinematics, Dynamics, and Optimization.\n* [casADi](https:\u002F\u002Fgithub.com\u002Fcasadi\u002Fcasadi) - A symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs.\n* [ACADO Toolkit](https:\u002F\u002Fgithub.com\u002Facado\u002Facado) - A software environment and algorithm collection for automatic control and dynamic optimization.\n* [control-toolbox](https:\u002F\u002Fgithub.com\u002Fethz-adrl\u002Fcontrol-toolbox) - An efficient C++ library for control, estimation, optimization and motion planning in robotics.\n* [CrowdNav](https:\u002F\u002Fgithub.com\u002Fvita-epfl\u002FCrowdNav) - Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning.\n* [ompl](https:\u002F\u002Fgithub.com\u002Fompl\u002Fompl) - Consists of many state-of-the-art sampling-based motion planning algorithms.\n* [openrave](https:\u002F\u002Fgithub.com\u002Frdiankov\u002Fopenrave) - Open Robotics Automation Virtual Environment: An environment for testing, developing, and deploying robotics motion planning algorithms.\n* [teb_local_planner](https:\u002F\u002Fgithub.com\u002Frst-tu-dortmund\u002Fteb_local_planner) - An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands.\n* [pinocchio](https:\u002F\u002Fgithub.com\u002Fstack-of-tasks\u002Fpinocchio) - A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives.\n* [rmf_core](https:\u002F\u002Fgithub.com\u002Fosrf\u002Frmf_core) - The rmf_core packages provide the centralized functions of the Robotics Middleware Framework (RMF).\n* [OpEn](https:\u002F\u002Fgithub.com\u002Falphaville\u002Foptimization-engine) - A solver for Fast & Accurate Embedded Optimization for next-generation Robotics and Autonomous Systems.\n* [autogenu-jupyter](https:\u002F\u002Fgithub.com\u002Fmayataka\u002Fautogenu-jupyter) - This project provides the continuation\u002FGMRES method (C\u002FGMRES method) based solvers for nonlinear model predictive control (NMPC) and an automatic code generator for NMPC.\n* [global_racetrajectory_optimization](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fglobal_racetrajectory_optimization) - This repository contains multiple approaches for generating global racetrajectories.\n* [toppra](https:\u002F\u002Fgithub.com\u002Fhungpham2511\u002Ftoppra) - A library for computing the time-optimal path parametrization for robots subject to kinematic and dynamic constraints.\n* [tinyspline](https:\u002F\u002Fgithub.com\u002Fmsteinbeck\u002Ftinyspline) - TinySpline is a small, yet powerful library for interpolating, transforming, and querying arbitrary NURBS, B-Splines, and Bézier curves.\n* [dual quaternions ros](https:\u002F\u002Fgithub.com\u002FAchllle\u002Fdual_quaternions_ros) - ROS python package for dual quaternion SLERP.\n* [mb planner](https:\u002F\u002Fgithub.com\u002Funr-arl\u002Fmbplanner_ros) - Aerial vehicle planner for tight spaces. Used in DARPA SubT Challenge.\n* [ilqr](https:\u002F\u002Fgithub.com\u002Fanassinator\u002Filqr) - Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models.\n* [EGO-Planner](https:\u002F\u002Fgithub.com\u002FZJU-FAST-Lab\u002Fego-planner) - A lightweight gradient-based local planner without ESDF construction, which significantly reduces computation time compared to some state-of-the-art methods.\n* [pykep](https:\u002F\u002Fgithub.com\u002Fesa\u002Fpykep) - A scientific library providing basic tools for research in interplanetary trajectory design.\n* [am_traj](https:\u002F\u002Fgithub.com\u002FZJU-FAST-Lab\u002Fam_traj) - Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight.\n* [GraphBasedLocalTrajectoryPlanner](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002FGraphBasedLocalTrajectoryPlanner) - Was used on a real race vehicle during the Roborace Season Alpha and achieved speeds above 200km\u002Fh.\n* [se2_navigation](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fse2_navigation) - Pure pursuit controller and Reeds-Shepp sampling based planner for navigation in SE(2) space.\n* [Ruckig](https:\u002F\u002Fruckig.com) - Instantaneous Motion Generation. Real-time. Jerk-constrained. Time-optimal.\n\n\n## User Interaction\n### Graphical User Interface\n* [imgui](https:\u002F\u002Fgithub.com\u002Focornut\u002Fimgui) - Designed to enable fast iterations and to empower programmers to create content creation tools and visualization \u002F debug tools.\n* [qtpy](https:\u002F\u002Fgithub.com\u002Fspyder-ide\u002Fqtpy) - Provides an uniform layer to support PyQt5, PySide2, PyQt4 and PySide with a single codebase.\n* [mir](https:\u002F\u002Fgithub.com\u002FMirServer\u002Fmir) - Mir is set of libraries for building Wayland based shells.\n* [rqt](https:\u002F\u002Fwiki.ros.org\u002Frqt) - A Qt-based framework for GUI development for ROS. It consists of three parts\u002Fmetapackages.\n* [cage](https:\u002F\u002Fgithub.com\u002FHjdskes\u002Fcage) - This is Cage, a Wayland kiosk. A kiosk runs a single, maximized application.\n* [chilipie](https:\u002F\u002Fgithub.com\u002Ffuturice\u002Fchilipie-kiosk) - Easy-to-use Raspberry Pi image for booting directly into full-screen Chrome.\n* [pencil](https:\u002F\u002Fgithub.com\u002Fevolus\u002Fpencil) - A tool for making diagrams and GUI prototyping that everyone can use.\n* [dynamic_reconfigure](https:\u002F\u002Fwiki.ros.org\u002Fdynamic_reconfigure) - The focus of dynamic_reconfigure is on providing a standard way to expose a subset of a node's parameters to external reconfiguration.\n* [ddynamic_reconfigure](https:\u002F\u002Fgithub.com\u002Fpal-robotics\u002Fddynamic_reconfigure) - Allows modifying parameters of a ROS node using the dynamic_reconfigure framework without having to write cfg files.\n* [elements](https:\u002F\u002Fgithub.com\u002Fcycfi\u002Felements) - A lightweight, fine-grained, resolution independent, modular GUI library.\n* [NanoGUI](https:\u002F\u002Fgithub.com\u002Fwjakob\u002Fnanogui) - A minimalistic cross-platform widget library for OpenGL 3.x or higher.\n\n\n### Acoustic User Interface\n* [pyo](https:\u002F\u002Fgithub.com\u002Fbelangeo\u002Fpyo) - A Python module written in C containing classes for a wide variety of audio signal processing types.\n* [rhasspy](https:\u002F\u002Fgithub.com\u002Fsynesthesiam\u002Frhasspy) - Rhasspy (pronounced RAH-SPEE) is an offline, multilingual voice assistant toolkit inspired by Jasper that works well with Home Assistant, Hass.io, and Node-RED.\n* [mycroft-core](https:\u002F\u002Fgithub.com\u002FMycroftAI\u002Fmycroft-core) - Mycroft is a hackable open source voice assistant.\n* [DDSP](https:\u002F\u002Fgithub.com\u002Fmagenta\u002Fddsp) - A library of differentiable versions of common DSP functions (such as synthesizers, waveshapers, and filters).\n* [NoiseTorch](https:\u002F\u002Fgithub.com\u002Flawl\u002FNoiseTorch) - Creates a virtual microphone that suppresses noise, in any application.\n* [DeepSpeech](https:\u002F\u002Fgithub.com\u002Fmozilla\u002FDeepSpeech) - An open source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper.\n* [waveglow](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fwaveglow) - A Flow-based Generative Network for Speech Synthesis.\n* [TTS](https:\u002F\u002Fgithub.com\u002Fcoqui-ai\u002FTTS) - A deep learning toolkit for Text-to-Speech, battle-tested in research and production.\n\n\n### Command Line Interface\n* [the-art-of-command-line](https:\u002F\u002Fgithub.com\u002Fjlevy\u002Fthe-art-of-command-line) - Master the command line, in one page.\n* [dotfiles of cornerman](https:\u002F\u002Fgithub.com\u002Fcornerman\u002Fdotfiles) - Powerful zsh and vim dotfiles.\n* [dotbot](https:\u002F\u002Fgithub.com\u002Fanishathalye\u002Fdotbot) - A tool that bootstraps your dotfiles.\n* [prompt-hjem](https:\u002F\u002Fgithub.com\u002Fcornerman\u002Fprompt-hjem) - A beautiful zsh prompt.\n* [ag](https:\u002F\u002Fgithub.com\u002Fggreer\u002Fthe_silver_searcher) - A code-searching tool similar to ack, but faster.\n* [fzf](https:\u002F\u002Fgithub.com\u002Fjunegunn\u002Ffzf) - A command-line fuzzy finder.\n* [pkgtop](https:\u002F\u002Fgithub.com\u002Forhun\u002Fpkgtop) - Interactive package manager and resource monitor designed for the GNU\u002FLinux.\n* [asciimatics](https:\u002F\u002Fgithub.com\u002Fpeterbrittain\u002Fasciimatics) - A cross platform package to do curses-like operations, plus higher level APIs and widgets to create text UIs and ASCII art animations.\n* [gocui](https:\u002F\u002Fgithub.com\u002Fjroimartin\u002Fgocui) - Minimalist Go package aimed at creating Console User Interfaces.\n* [TerminalImageViewer](https:\u002F\u002Fgithub.com\u002Fstefanhaustein\u002FTerminalImageViewer) - Small C++ program to display images in a (modern) terminal using RGB ANSI codes and unicode block graphics characters.\n* [rosshow](https:\u002F\u002Fgithub.com\u002Fdheera\u002Frosshow) - Visualize ROS topics inside a terminal with Unicode\u002FASCII art.\n* [python-prompt-toolkit](https:\u002F\u002Fgithub.com\u002Fprompt-toolkit\u002Fpython-prompt-toolkit) - Library for building powerful interactive command line applications in Python.\n* [guake](https:\u002F\u002Fgithub.com\u002FGuake\u002Fguake) - Drop-down terminal for GNOME.\n* [wemux](https:\u002F\u002Fgithub.com\u002Fzolrath\u002Fwemux) - Multi-User Tmux Made Easy.\n* [tmuxp](https:\u002F\u002Fgithub.com\u002Ftmux-python\u002Ftmuxp) -  A session manager built on libtmux.\n* [mapscii](https:\u002F\u002Fgithub.com\u002Frastapasta\u002Fmapscii) - World map renderer for your console.\n* [terminator](https:\u002F\u002Flaunchpad.net\u002Fterminator) - The goal of this project is to produce a useful tool for arranging terminals.\n* [bat](https:\u002F\u002Fgithub.com\u002Fsharkdp\u002Fbat) - A cat(1) clone with wings.\n* [fx](https:\u002F\u002Fgithub.com\u002Fantonmedv\u002Ffx) - Command-line tool and terminal JSON viewer.\n* [tmate](https:\u002F\u002Fgithub.com\u002Ftmate-io\u002Ftmate) - Instant terminal sharing.\n\n## Data Visualization and Mission Control\n* [xdot](https:\u002F\u002Fgithub.com\u002Fjrfonseca\u002Fxdot.py) - Interactive viewer for graphs written in Graphviz's dot language.\n* [guacamole](https:\u002F\u002Fguacamole.apache.org\u002F) - Clientless remote desktop gateway. It supports standard protocols like VNC, RDP, and SSH.\n* [ros3djs](https:\u002F\u002Fgithub.com\u002FRobotWebTools\u002Fros3djs) - 3D Visualization Library for use with the ROS JavaScript Libraries.\n* [webviz](https:\u002F\u002Fgithub.com\u002Fcruise-automation\u002Fwebviz) - Web-based visualization libraries like rviz.\n* [plotly.py](https:\u002F\u002Fgithub.com\u002Fplotly\u002Fplotly.py) - An open-source, interactive graphing library for Python.\n* [PlotJuggler](https:\u002F\u002Fgithub.com\u002Ffacontidavide\u002FPlotJuggler) - The timeseries visualization tool that you deserve.\n* [bokeh](https:\u002F\u002Fgithub.com\u002Fbokeh\u002Fbokeh) - Interactive Data Visualization in the browser, from Python.\n* [voila](https:\u002F\u002Fgithub.com\u002Fvoila-dashboards\u002Fvoila) - From Jupyter notebooks to standalone web applications and dashboards.\n* [Pangolin](https:\u002F\u002Fgithub.com\u002Fstevenlovegrove\u002FPangolin) - Pangolin is a lightweight portable rapid development library for managing OpenGL display \u002F interaction and abstracting video input.\n* [rqt_bag](http:\u002F\u002Fwiki.ros.org\u002Frqt_bag) - Provides a GUI plugin for displaying and replaying ROS bag files.\n* [kepler.gl](https:\u002F\u002Fgithub.com\u002Fkeplergl\u002Fkepler.gl) - Kepler.gl is a powerful open source geospatial analysis tool for large-scale data sets.\n* [qgis_ros](https:\u002F\u002Fgithub.com\u002Flocusrobotics\u002Fqgis_ros) - Access bagged and live topic data in a highly featured GIS environment.\n* [openmct](https:\u002F\u002Fgithub.com\u002Fnasa\u002Fopenmct) - A web based mission control framework.\n* [web_video_server](https:\u002F\u002Fgithub.com\u002FRobotWebTools\u002Fweb_video_server) - HTTP Streaming of ROS Image Topics in Multiple Formats.\n* [RVizWeb](https:\u002F\u002Fgithub.com\u002Fosrf\u002Frvizweb) - Provides a convenient way of building and launching a web application with features similar to RViz.\n* [marvros](https:\u002F\u002Fgithub.com\u002Fmavlink\u002Fmavros) - MAVLink to ROS gateway with proxy for Ground Control Station.\n* [octave](https:\u002F\u002Fwww.gnu.org\u002Fsoftware\u002Foctave\u002F) - Provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab.\n* [streetscape.gl](https:\u002F\u002Fgithub.com\u002Fuber\u002Fstreetscape.gl) - Streetscape.gl is a toolkit for visualizing autonomous and robotics data in the XVIZ protocol.\n* [urdf-loaders](https:\u002F\u002Fgithub.com\u002Fgkjohnson\u002Furdf-loaders) - URDF Loaders for Unity and THREE.js with example ATHLETE URDF File.\n* [obs-studio](https:\u002F\u002Fgithub.com\u002Fobsproject\u002Fobs-studio) - Free and open source software for live streaming and screen recording.\n* [K3D-tools](https:\u002F\u002Fgithub.com\u002FK3D-tools) - Jupyter notebook extension for 3D visualization.\n* [PyQtGraph](https:\u002F\u002Fgithub.com\u002Fpyqtgraph\u002Fpyqtgraph) - Fast data visualization and GUI tools for scientific \u002F engineering applications.\n* [ipygany](https:\u002F\u002Fgithub.com\u002FQuantStack\u002Fipygany) - 3-D Scientific Visualization in the Jupyter Notebook.\n* [Foxglove Studio](https:\u002F\u002Fgithub.com\u002Ffoxglove\u002Fstudio) - Web and desktop app for robotics visualization and debugging; actively maintained fork of webviz.\n* [ROS-Mobile](https:\u002F\u002Fgithub.com\u002FROS-Mobile\u002FROS-Mobile-Android) - Visualization and controlling application for Android.\n\n\n### Annotation\n* [labelbox](https:\u002F\u002Fgithub.com\u002FLabelbox\u002Flabelbox) - The fastest way to annotate data to build and ship artificial intelligence applications.\n* [PixelAnnotationTool](https:\u002F\u002Fgithub.com\u002Fabreheret\u002FPixelAnnotationTool) - Annotate quickly images.\n* [LabelImg](https:\u002F\u002Fgithub.com\u002Ftzutalin\u002FlabelImg) - A graphical image annotation tool and label object bounding boxes in images.\n* [cvat](https:\u002F\u002Fgithub.com\u002Fopencv\u002Fcvat) - Powerful and efficient Computer Vision Annotation Tool (CVAT).\n* [point_labeler](https:\u002F\u002Fgithub.com\u002Fjbehley\u002Fpoint_labeler) - Tool for labeling of a single point clouds or a stream of point clouds.\n* [label-studio](https:\u002F\u002Fgithub.com\u002Fheartexlabs\u002Flabel-studio) - Label Studio is a multi-type data labeling and annotation tool with standardized output format.\n* [napari](https:\u002F\u002Fgithub.com\u002Fnapari\u002Fnapari) -  A fast, interactive, multi-dimensional image viewer for python.\n* [semantic-segmentation-editor](https:\u002F\u002Fgithub.com\u002FHitachi-Automotive-And-Industry-Lab\u002Fsemantic-segmentation-editor) - A web based labeling tool for creating AI training data sets (2D and 3D).\n* [3d-bat](https:\u002F\u002Fgithub.com\u002Fwalzimmer\u002F3d-bat) - 3D Bounding Box Annotation Tool for Point cloud and Image Labeling.\n* [labelme](https:\u002F\u002Fgithub.com\u002Fwkentaro\u002Flabelme) - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).\n* [universal-data-tool](https:\u002F\u002Fgithub.com\u002FUniversalDataTool\u002Funiversal-data-tool) - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.\n* [BMW-Labeltool-Lite](https:\u002F\u002Fgithub.com\u002FBMW-InnovationLab\u002FBMW-Labeltool-Lite) - Provides you with a easy to use labeling tool for State-of-the-art Deep Learning training purposes.\n* [3d-annotation-tool](https:\u002F\u002Fgithub.com\u002FStrayRobots\u002F3d-annotation-tool) - Lightweight tool to annotate point clouds with bounding boxes, rectangles, keypoints and more.\n\n\n### Point Cloud\n* [CloudCompare](https:\u002F\u002Fgithub.com\u002FCloudCompare\u002FCloudCompare) - CloudCompare is a 3D point cloud (and triangular mesh) processing software.\n* [Potree](https:\u002F\u002Fgithub.com\u002Fpotree\u002Fpotree) - WebGL point cloud viewer for large datasets.\n* [point_cloud_viewer](https:\u002F\u002Fgithub.com\u002Fgooglecartographer\u002Fpoint_cloud_viewer) - Makes viewing massive point clouds easy and convenient.\n* [LidarView](https:\u002F\u002Fgithub.com\u002FKitware\u002FLidarView) - Performs real-time visualization and easy processing of live captured 3D LiDAR data from Lidar sensors.\n* [VeloView](https:\u002F\u002Fgithub.com\u002FKitware\u002FVeloView) - Performs real-time visualization of live captured 3D LiDAR data from Velodyne's HDL sensors.\n* [entwine](https:\u002F\u002Fgithub.com\u002Fconnormanning\u002Fentwine\u002F) - A data organization library for massive point clouds, designed to conquer datasets of trillions of points as well as desktop-scale point clouds.\n* [polyscope](https:\u002F\u002Fgithub.com\u002Fnmwsharp\u002Fpolyscope) - A C++ & Python viewer for 3D data like meshes and point clouds.\n* [Pcx](https:\u002F\u002Fgithub.com\u002Fkeijiro\u002FPcx) - Point cloud importer & renderer for Unity.\n* [ImmersivePoints](https:\u002F\u002Fgithub.com\u002Frmeertens\u002FImmersivePoints) - A web-application for virtual reality devices to explore 3D data in the most natural way possible.\n\n\n### RViz\n* [mapviz](https:\u002F\u002Fgithub.com\u002Fswri-robotics\u002Fmapviz) - Modular ROS visualization tool for 2D data.\n* [rviz_cinematographer](https:\u002F\u002Fgithub.com\u002FAIS-Bonn\u002Frviz_cinematographer) - Easy to use tools to create and edit trajectories for the rviz camera.\n* [rviz_satellite](https:\u002F\u002Fgithub.com\u002Fgareth-cross\u002Frviz_satellite) - Display internet satellite imagery in RViz.\n* [rviz_visual_tools](https:\u002F\u002Fgithub.com\u002FPickNikRobotics\u002Frviz_visual_tools) - C++ API wrapper for displaying shapes and meshes in Rviz.\n\u003C!--lint ignore double-link-->\n* [xpp](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fxpp) - Visualization of motion-plans for legged robots.\n* [rviz stereo](http:\u002F\u002Fwiki.ros.org\u002Frviz\u002FTutorials\u002FRviz%20in%20Stereo) - 3D stereo rendering displays a different view to each eye so that the scene appears to have depth.\n* [jsk_visualization](https:\u002F\u002Fgithub.com\u002Fjsk-ros-pkg\u002Fjsk_visualization) - Jsk visualization ros packages for rviz and rqt.\n* [moveit_visual_tools](https:\u002F\u002Fgithub.com\u002Fros-planning\u002Fmoveit_visual_tools) - Helper functions for displaying and debugging MoveIt! data in Rviz via published markers.\n\n\n## Operation System\n### Monitoring\n* [rosmon](https:\u002F\u002Fgithub.com\u002Fxqms\u002Frosmon) - ROS node launcher & monitoring daemon.\n* [multimaster_fkie](https:\u002F\u002Fgithub.com\u002Ffkie\u002Fmultimaster_fkie) - GUI-based management environment that is very useful to manage ROS-launch configurations and control running nodes.\n* [collectd](https:\u002F\u002Fgithub.com\u002Fcollectd\u002Fcollectd\u002F) - A small daemon which collects system information periodically and provides mechanisms to store and monitor the values in a variety of ways.\n* [lnav](http:\u002F\u002Flnav.org\u002F) - An enhanced log file viewer that takes advantage of any semantic information that can be gleaned from the files being viewed, such as timestamps and log levels.\n* [htop](https:\u002F\u002Fgithub.com\u002Fhishamhm\u002Fhtop) - An interactive text-mode process viewer for Unix systems. It aims to be a better 'top'.\n* [atop](https:\u002F\u002Fgithub.com\u002FAtoptool\u002Fatop) - System and process monitor for Linux with logging and replay function.\n* [psutil](https:\u002F\u002Fgithub.com\u002Fgiampaolo\u002Fpsutil) - Cross-platform lib for process and system monitoring in Python.\n* [gputil](https:\u002F\u002Fgithub.com\u002Fanderskm\u002Fgputil) - A Python module for getting the GPU status from NVIDA GPUs using nvidia-smi programmically in Python.\n* [gpustat](https:\u002F\u002Fgithub.com\u002Fwookayin\u002Fgpustat) -  A simple command-line utility for querying and monitoring GPU status.\n* [nvtop](https:\u002F\u002Fgithub.com\u002FSyllo\u002Fnvtop) - NVIDIA GPUs htop like monitoring tool.\n* [ShellHub](https:\u002F\u002Fwww.shellhub.io) - ShellHub is a modern SSH server for remotely accessing linux devices via command line (using any SSH client) or web-based user interface, designed as an alternative to sshd. Think ShellHub as centralized SSH for the the edge and cloud computing.\n* [Sshwifty](https:\u002F\u002Fgithub.com\u002Fnirui\u002Fsshwifty) - Sshwifty is a SSH and Telnet connector made for the Web.\n* [spdlog](https:\u002F\u002Fgithub.com\u002Fgabime\u002Fspdlog) - Very fast, header-only\u002Fcompiled, C++ logging library.\n* [ctop](https:\u002F\u002Fgithub.com\u002Fbcicen\u002Fctop) -  Top-like interface for container metrics.\n* [ntop](https:\u002F\u002Fgithub.com\u002Fntop\u002Fntopng) - Web-based Traffic and Security Network Traffic Monitoring.\n* [jupyterlab-nvdashboard](https:\u002F\u002Fgithub.com\u002Frapidsai\u002Fjupyterlab-nvdashboard) - A JupyterLab extension for displaying dashboards of GPU usage.\n\n### Database and Record\n* [ncdu](https:\u002F\u002Fdev.yorhel.nl\u002Fncdu) - Ncdu is a disk usage analyzer with an ncurses interface.\n* [borg](https:\u002F\u002Fgithub.com\u002Fborgbackup\u002Fborg) - Deduplicating archiver with compression and authenticated encryption.\n* [bag-database](https:\u002F\u002Fgithub.com\u002Fswri-robotics\u002Fbag-database) - A server that catalogs bag files and provides a web-based UI for accessing them.\n* [marv-robotics](https:\u002F\u002Fgitlab.com\u002Fternaris\u002Fmarv-robotics) - MARV Robotics is a powerful and extensible data management platform.\n* [kitti2bag](https:\u002F\u002Fgithub.com\u002Ftomas789\u002Fkitti2bag) - Convert KITTI dataset to ROS bag file the easy way.\n* [pykitti](https:\u002F\u002Fgithub.com\u002FutiasSTARS\u002Fpykitti) - Python tools for working with KITTI data.\n* [rosbag_editor](https:\u002F\u002Fgithub.com\u002Ffacontidavide\u002Frosbag_editor) - Create a rosbag from a given one, using a simple GUI.\n* [nextcloud](https:\u002F\u002Fgithub.com\u002Fnextcloud\u002Fserver) - Nextcloud is a suite of client-server software for creating and using file hosting services.\n* [ros_type_introspection](https:\u002F\u002Fgithub.com\u002Ffacontidavide\u002Fros_type_introspection) - Deserialize ROS messages that are unknown at compilation time.\n* [syncthing](https:\u002F\u002Fgithub.com\u002Fsyncthing\u002Fsyncthing) - A continuous file synchronization program.\n* [rqt_bag_exporter](https:\u002F\u002Fgitlab.com\u002FInstitutMaupertuis\u002Frqt_bag_exporter) - Qt GUI to export ROS bag topics to files (CSV and\u002For video).\n* [xviz](https:\u002F\u002Fgithub.com\u002Fuber\u002Fxviz) - A protocol for real-time transfer and visualization of autonomy data.\n* [kitti_to_rosbag](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fkitti_to_rosbag) - A Dataset tools for working with the KITTI dataset raw data and converting it to a ROS bag. Also allows a library for direct access to poses, velodyne scans, and images.\n* [ros_numpy](https:\u002F\u002Fgithub.com\u002Feric-wieser\u002Fros_numpy) - Tools for converting ROS messages to and from numpy arrays.\n* [kitti_ros](https:\u002F\u002Fgithub.com\u002FLidarPerception\u002Fkitti_ros) - A ROS-based player to replay KiTTI dataset.\n* [DuckDB](https:\u002F\u002Fgithub.com\u002Fcwida\u002Fduckdb) - An embeddable SQL OLAP Database Management System.\n\n### Network Distributed File System\n* [sshfs](https:\u002F\u002Fgithub.com\u002Fosxfuse\u002Fsshfs) - File system based on the SSH File Transfer Protocol.\n* [moosefs](https:\u002F\u002Fgithub.com\u002Fmoosefs\u002Fmoosefs) -  A scalable distributed storage system.\n* [ceph](https:\u002F\u002Fgithub.com\u002Fceph\u002Fceph) - A distributed object, block, and file storage platform.\n* [nfs](https:\u002F\u002Fgithub.com\u002Fsahlberg\u002Flibnfs) - A distributed file system protocol originally developed by Sun Microsystems.\n* [ansible-role-nfs](https:\u002F\u002Fgithub.com\u002Fgeerlingguy\u002Fansible-role-nfs) - Installs NFS utilities on RedHat\u002FCentOS or Debian\u002FUbuntu.\n\n\n### Server Infrastructure and High Performance Computing\n* [mass](https:\u002F\u002Fgithub.com\u002Fmaas\u002Fmaas) - Self-service, remote installation of Windows, CentOS, ESXi and Ubuntu on real servers turns your data centre into a bare metal cloud.\n* [polyaxon](https:\u002F\u002Fgithub.com\u002Fpolyaxon\u002Fpolyaxon) - A platform for reproducing and managing the whole life cycle of machine learning and deep learning applications.\n* [localstack](https:\u002F\u002Fgithub.com\u002Flocalstack\u002Flocalstack) - A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline.\n* [nvidia-docker](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fnvidia-docker) - Build and run Docker containers leveraging NVIDIA GPUs.\n* [kubeflow](https:\u002F\u002Fgithub.com\u002Fkubeflow\u002Fkubeflow) - Machine Learning Toolkit for Kubernetes.\n* [log-pilot](https:\u002F\u002Fgithub.com\u002FAliyunContainerService\u002Flog-pilot) - Collect logs for docker containers.\n* [traefik](https:\u002F\u002Fgithub.com\u002Fcontainous\u002Ftraefik) - The Cloud Native Edge Router.\n* [graylog2-server](https:\u002F\u002Fgithub.com\u002FGraylog2\u002Fgraylog2-server) - Free and open source log management.\n* [ansible](https:\u002F\u002Fgithub.com\u002Fansible\u002Fansible) - Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy.\n* [pyinfra](https:\u002F\u002Fgithub.com\u002FFizzadar\u002Fpyinfra) - It can be used for ad-hoc command execution, service deployment, configuration management and more.\n* [docker-py](https:\u002F\u002Fgithub.com\u002Fdocker\u002Fdocker-py) - A Python library for the Docker Engine API.\n* [noVNC](https:\u002F\u002Fgithub.com\u002Fnovnc\u002FnoVNC) - VNC client using HTML5.\n* [Slurm](https:\u002F\u002Fgithub.com\u002FSchedMD\u002Fslurm) - Slurm: A Highly Scalable Workload Manager.\n* [jupyterhub](https:\u002F\u002Fgithub.com\u002Fjupyterhub\u002Fjupyterhub) - Multi-user server for Jupyter notebooks.\n* [Portainer](https:\u002F\u002Fgithub.com\u002Fportainer\u002Fportainer) - Making Docker management easy.\n* [enroot](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fenroot) - A simple, yet powerful tool to turn traditional container\u002FOS images into unprivileged sandboxes.\n* [docker-firefox](https:\u002F\u002Fgithub.com\u002Fjlesage\u002Fdocker-firefox) - Run a Docker Container with Firefox and noVNC for remote access to headless servers.\n* [luigi](https:\u002F\u002Fgithub.com\u002Fspotify\u002Fluigi) - A Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.\n* [triton-inference-server](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Ftriton-inference-server) - NVIDIA Triton Inference Server provides a cloud inferencing solution optimized for NVIDIA GPUs.\n* [cudf](https:\u002F\u002Fgithub.com\u002Frapidsai\u002Fcudf) - Provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming.\n\n\n### Embedded Operation System\n* [vxworks7-ros2-build](https:\u002F\u002Fgithub.com\u002FWind-River\u002Fvxworks7-ros2-build) - Build system to automate the build of VxWorks 7 and ROS2.\n* [Yocto](https:\u002F\u002Fgit.yoctoproject.org\u002F) - Produce tools and processes that enable the creation of Linux distributions for embedded software that are independent of the underlying architecture of the embedded hardware.\n* [Automotive Graded Linux](https:\u002F\u002Fwww.automotivelinux.org\u002Fsoftware) - A collaborative open source project that is bringing together automakers, suppliers and technology companies to build a Linux-based, open software platform for automotive applications that can serve as the de facto industry standard.\n* [bitbake](https:\u002F\u002Fgithub.com\u002Fopenembedded\u002Fbitbake) - A generic task execution engine that allows shell and Python tasks to be run efficiently and in parallel while working within complex inter-task dependency constraints.\n* [Jailhouse](https:\u002F\u002Fgithub.com\u002Fsiemens\u002Fjailhouse) - Jailhouse is a partitioning Hypervisor based on Linux.\n* [Xen](https:\u002F\u002Fwiki.debian.org\u002FXen) - An open-source (GPL) type-1 or baremetal hypervisor.\n* [QEMU](https:\u002F\u002Fwww.qemu.org\u002F) - A generic and open source machine emulator and virtualizer.\n* [qemu-xilinx](https:\u002F\u002Fgithub.com\u002FXilinx\u002Fqemu) - A fork of Quick EMUlator (QEMU) with improved support and modelling for the Xilinx platforms.\n* [rosserial](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Frosserial) - A ROS client library for small, embedded devices, such as Arduino.\n* [meta-ros](https:\u002F\u002Fgithub.com\u002Fros\u002Fmeta-ros\u002Ftree\u002Fthud-draft) - OpenEmbedded Layer for ROS Applications.\n* [meta-balena](https:\u002F\u002Fgithub.com\u002Fbalena-os\u002Fmeta-balena) - Run Docker containers on embedded devices.\n* [micro-ros](https:\u002F\u002Fmicro-ros.github.io\u002F) - The major changes compared to \"regular\" ROS 2 is that micro-ROS uses a Real-Time Operating System (RTOS) instead of Linux, and DDS for eXtremely Resource Constrained Environments.\n* [nvidia-container-runtime](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fnvidia-container-runtime\u002F) - NVIDIA Container Runtime is a GPU aware container runtime, compatible with the Open Containers Initiative (OCI) specification used by Docker, CRI-O, and other popular container technologie.\n* [fusesoc](https:\u002F\u002Fgithub.com\u002Folofk\u002Ffusesoc) - Package manager and build abstraction tool for FPGA\u002FASIC development.\n* [jetson_easy](https:\u002F\u002Fgithub.com\u002Frbonghi\u002Fjetson_easy) - Automatically script to setup and configure your NVIDIA Jetson.\n* [docker-jetpack-sdk](https:\u002F\u002Fgithub.com\u002Ftrn84\u002Fdocker-jetpack-sdk) -  Allows for usage of the NVIDIA JetPack SDK within a docker container for download, flashing, and install.\n* [Pressed](https:\u002F\u002Fwiki.debian.org\u002FDebianInstaller\u002FPreseed) - Provides a way to set answers to questions asked during the installation process of debian, without having to manually enter the answers while the installation is running.\n* [jetson_stats](https:\u002F\u002Fgithub.com\u002Frbonghi\u002Fjetson_stats) - A package to monitoring and control your NVIDIA Jetson (Xavier NX, Nano, AGX Xavier, TX1, TX2) Works with all NVIDIA Jetson ecosystem.\n* [ros_jetson_stats](https:\u002F\u002Fgithub.com\u002Frbonghi\u002Fros_jetson_stats) - The ROS jetson-stats wrapper. The status of your NVIDIA jetson in diagnostic messages.\n* [OpenCR](https:\u002F\u002Fgithub.com\u002FROBOTIS-GIT\u002FOpenCR) - Open-source Control Module for ROS.\n* [acrn-hypervisor](https:\u002F\u002Fgithub.com\u002Fprojectacrn\u002Facrn-hypervisor) - Defines a device hypervisor reference stack and an architecture for running multiple software subsystems, managed securely, on a consolidated system by means of a virtual machine manager.\n* [jetson-containers](https:\u002F\u002Fgithub.com\u002Fdusty-nv\u002Fjetson-containers) - Machine Learning Containers for Jetson and JetPack 4.4.\n\n\n### Real-Time Kernel\n* [ELISA](https:\u002F\u002Felisa.tech\u002F) -  Project is to make it easier for companies to build and certify Linux-based safety-critical applications – systems whose failure could result in loss of human life, significant property damage or environmental damage.\n* [PREEMPT_RT kernel patch](https:\u002F\u002Fwiki.linuxfoundation.org\u002Frealtime\u002Fdocumentation\u002Fstart) - Aim of the PREEMPT_RT kernel patch is to minimize the amount of kernel code that is non-preemptible.\n\n## Network and Middleware\n* [performance_test](https:\u002F\u002Fgithub.com\u002FApexAI\u002Fperformance_test) - Tool to test the performance of pub\u002Fsub based communication frameworks.\n* [realtime_support](https:\u002F\u002Fgithub.com\u002Fros2\u002Frealtime_support) - Minimal real-time testing utility for measuring jitter and latency.\n* [ros1_bridge](https:\u002F\u002Fgithub.com\u002Fros2\u002Fros1_bridge) - ROS 2 package that provides bidirectional communication between ROS 1 and ROS 2.\n* [Fast-RTPS](https:\u002F\u002Fgithub.com\u002FeProsima\u002FFast-RTPS) - A Protocol, which provides publisher-subscriber communications over unreliable transports such as UDP, as defined and maintained by the Object Management Group (OMG) consortium.\n* [protobuf](https:\u002F\u002Fgithub.com\u002Fprotocolbuffers\u002Fprotobuf) - Google's data interchange format.\n* [opensplice](https:\u002F\u002Fgithub.com\u002FADLINK-IST\u002Fopensplice) - Vortex OpenSplice Community Edition.\n* [cyclonedds](https:\u002F\u002Fgithub.com\u002Feclipse-cyclonedds\u002Fcyclonedds) - Eclipse Cyclone DDS is a very performant and robust open-source DDS implementation.\n* [iceoryx](https:\u002F\u002Fgithub.com\u002Feclipse\u002Ficeoryx) - An IPC middleware for POSIX-based systems.\n* [rosbridge_suite](https:\u002F\u002Fgithub.com\u002FRobotWebTools\u002Frosbridge_suite) - Provides a JSON interface to ROS, allowing any client to send JSON to publish or subscribe to ROS topics, call ROS services, and more.\n* [ros2arduino](https:\u002F\u002Fgithub.com\u002FROBOTIS-GIT\u002Fros2arduino) - This library helps the Arduino board communicate with the ROS2 using XRCE-DDS.\n* [eCAL](https:\u002F\u002Fgithub.com\u002Fcontinental\u002F) - The enhanced communication abstraction layer (eCAL) is a middleware that enables scalable, high performance interprocess communication on a single computer node or between different nodes in a computer network.\n* [AUTOSAR-Adaptive](https:\u002F\u002Fgithub.com\u002FUmlautSoftwareDevelopmentAccount\u002FAUTOSAR-Adaptive) - The implementation of AUTOSAR Adaptive Platform based on the R19-11.\n* [ocpp](https:\u002F\u002Fgithub.com\u002FNewMotion\u002Focpp) - The Open Charge Point Protocol (OCPP) is a network protocol for communication between electric vehicle chargers and a central backoffice system.\n* [micro-ROS for Arduino](https:\u002F\u002Fgithub.com\u002Fmicro-ROS\u002Fmicro_ros_arduino) - A experimental micro-ROS library for baremetal projects based on Arduino IDE or Arduino CLI.\n* [mqtt_bridge](https:\u002F\u002Fgithub.com\u002Fgroove-x\u002Fmqtt_bridge) - Provides a functionality to bridge between ROS and MQTT in bidirectional.\n\n\n### Ethernet and Wireless Networking\n* [SOES](https:\u002F\u002Fgithub.com\u002FOpenEtherCATsociety\u002FSOES) - SOES is an EtherCAT slave stack written in C.\n* [netplan](https:\u002F\u002Fnetplan.io\u002F) - Simply create a YAML description of the required network interfaces and what each should be configured to do.\n* [airalab](https:\u002F\u002Fgithub.com\u002Fairalab) -  AIRA is reference Robonomics network client for ROS-enabled cyber-physical systems.\n* [rdbox](https:\u002F\u002Fgithub.com\u002Frdbox-intec\u002Frdbox) - RDBOX is a IT infrastructure for ROS robots.\n* [ros_ethercat](https:\u002F\u002Fgithub.com\u002Fshadow-robot\u002Fros_ethercat) - This is a reimplementation of the main loop of pr2_ethercat without dependencies on PR2 software.\n* [wavemon](https:\u002F\u002Fgithub.com\u002Fuoaerg\u002Fwavemon) - An ncurses-based monitoring application for wireless network devices.\n* [wireless](https:\u002F\u002Fgithub.com\u002Fclearpathrobotics\u002Fwireless) - Making info about wireless networks available to ROS.\n* [ptpd](https:\u002F\u002Fgithub.com\u002Fptpd\u002Fptpd) - PTP daemon (PTPd) is an implementation the Precision Time Protocol (PTP) version 2 as defined by 'IEEE Std 1588-2008'. PTP provides precise time coordination of Ethernet LAN connected computers.\n* [iperf](https:\u002F\u002Fgithub.com\u002Fesnet\u002Fiperf) - A TCP, UDP, and SCTP network bandwidth measurement tool.\n* [tcpreplay](https:\u002F\u002Fgithub.com\u002Fappneta\u002Ftcpreplay) - Pcap editing and replay tools.\n* [nethogs](https:\u002F\u002Fgithub.com\u002Fraboof\u002Fnethogs) - It groups bandwidth by process.\n* [pyshark](https:\u002F\u002Fgithub.com\u002FKimiNewt\u002Fpyshark) - Python wrapper for tshark, allowing python packet parsing using wireshark dissectors.\n* [pingtop](https:\u002F\u002Fgithub.com\u002Flaixintao\u002Fpingtop) - Ping multiple servers and show results in a top-like terminal UI.\n* [termshark](https:\u002F\u002Fgithub.com\u002Fgcla\u002Ftermshark) - A terminal UI for tshark, inspired by Wireshark.\n* [udpreplay](https:\u002F\u002Fgithub.com\u002Frigtorp\u002Fudpreplay) - Replay UDP packets from a pcap file.\n* [openwifi](https:\u002F\u002Fgithub.com\u002Fopen-sdr\u002Fopenwifi) - Linux mac80211 compatible full-stack IEEE802.11\u002FWi-Fi design based on Software Defined Radio.\n\n### Controller Area Network\n* [awesome CAN](https:\u002F\u002Fgithub.com\u002FiDoka\u002Fawesome-canbus) -  A curated list of awesome CAN bus tools, hardware and resources.\n* [AndrOBD](https:\u002F\u002Fgithub.com\u002Ffr3ts0n\u002FAndrOBD) - Android OBD diagnostics with any ELM327 adapter.\n* [ddt4all](https:\u002F\u002Fgithub.com\u002Fcedricp\u002Fddt4all) - DDT4All is a tool to create your own ECU parameters screens and connect to a CAN network with a cheap ELM327 interface.\n* [cabana](https:\u002F\u002Fgithub.com\u002Fcommaai\u002Fcabana) - CAN visualizer and DBC maker.\n* [opendbc](https:\u002F\u002Fgithub.com\u002Fcommaai\u002Fopendbc) - The project to democratize access to the decoder ring of your car.\n* [libuavcan](https:\u002F\u002Fgithub.com\u002FUAVCAN\u002Flibuavcan) - An open lightweight protocol designed for reliable communication in aerospace and robotic applications over robust vehicular networks such as CAN bus.\n* [python-can](https:\u002F\u002Fgithub.com\u002Fhardbyte\u002Fpython-can) - The can package provides controller area network support for Python developers.\n* [CANopenNode](https:\u002F\u002Fgithub.com\u002FCANopenNode\u002FCANopenNode) - The internationally standardized (EN 50325-4) (CiA301) CAN-based higher-layer protocol for embedded control system.\n* [python-udsoncan](https:\u002F\u002Fgithub.com\u002Fpylessard\u002Fpython-udsoncan) - Python implementation of UDS (ISO-14229) standard.\n* [uds-c](https:\u002F\u002Fgithub.com\u002Fopenxc\u002Fuds-c) - Unified Diagnostics Service (UDS) and OBD-II (On Board Diagnostics for Vehicles) C Library.\n* [cantools](https:\u002F\u002Fgithub.com\u002Feerimoq\u002Fcantools) - CAN BUS tools in Python 3.\n* [CANdevStudio](https:\u002F\u002Fgithub.com\u002FGENIVI\u002FCANdevStudio) -  CANdevStudio aims to be cost-effective replacement for CAN simulation software. It can work with variety of CAN hardware interfaces.\n* [can-utils](https:\u002F\u002Fgithub.com\u002Flinux-can\u002Fcan-utils) - Linux-CAN \u002F SocketCAN user space applications.\n* [ros_canopen](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Fros_canopen) - CANopen driver framework for ROS.\n* [decanstructor](https:\u002F\u002Fgithub.com\u002FJWhitleyAStuff\u002Fdecanstructor) - The definitive ROS CAN analysis tool.\n* [kvaser_interface](https:\u002F\u002Fgithub.com\u002Fastuff\u002Fkvaser_interface) - This package was developed as a standardized way to access Kvaser CAN devices from ROS.\n* [canmatrix](https:\u002F\u002Fgithub.com\u002Febroecker\u002Fcanmatrix) - Converting CAN Database Formats .arxml .dbc .dbf .kcd.\n* [autosar](https:\u002F\u002Fgithub.com\u002Fcogu\u002Fautosar) - A set of python modules for working with AUTOSAR XML files.\n* [canopen](https:\u002F\u002Fgithub.com\u002Fchristiansandberg\u002Fcanopen) - A Python implementation of the CANopen standard. The aim of the project is to support the most common parts of the CiA 301 standard in a Pythonic interface.\n* [SavvyCAN](https:\u002F\u002Fgithub.com\u002Fcollin80\u002FSavvyCAN) - A Qt5 based cross platform tool which can be used to load, save, and capture canbus frames.\n* [Open-Vehicle-Monitoring-System-3](https:\u002F\u002Fgithub.com\u002Fopenvehicles\u002FOpen-Vehicle-Monitoring-System-3) - The system provides live monitoring of vehicle metrics like state of charge, temperatures, tyre pressures and diagnostic fault conditions.\n\n\n### Sensor and Acuator Interfaces\n* [Tesla-API](https:\u002F\u002Fgithub.com\u002Ftimdorr\u002Ftesla-api) - Provides functionality to monitor and control the Model S (and future Tesla vehicles) remotely.\n* [flirpy](https:\u002F\u002Fgithub.com\u002FLJMUAstroecology\u002Fflirpy) - A Python library to interact with FLIR thermal imaging cameras and images.\n* [nerian_stereo](https:\u002F\u002Fgithub.com\u002Fnerian-vision\u002Fnerian_stereo) - ROS node for Nerian's SceneScan and SP1 stereo vision sensors.\n* [pymmw](https:\u002F\u002Fgithub.com\u002Fm6c7l\u002Fpymmw) - This is a toolbox composed of Python scripts to interact with TI's evaluation module (BoosterPack) for the IWR1443 mmWave sensing device.\n* [ti_mmwave_rospkg](https:\u002F\u002Fgithub.com\u002Fradar-lab\u002Fti_mmwave_rospkg) - TI mmWave radar ROS driver (with sensor fusion and hybrid).\n* [pacmod3](https:\u002F\u002Fgithub.com\u002Fastuff\u002Fpacmod3) - This ROS node is designed to allow the user to control a vehicle with the PACMod drive-by-wire system, board revision 3.\n* [ros2_intel_realsense](https:\u002F\u002Fgithub.com\u002Fintel\u002Fros2_intel_realsense) - These are packages for using Intel RealSense cameras (D400 series) with ROS2.\n* [sick_scan](https:\u002F\u002Fgithub.com\u002FSICKAG\u002Fsick_scan) - This stack provides a ROS2 driver for the SICK TiM series of laser scanners.\n* [ouster_example](https:\u002F\u002Fgithub.com\u002Fouster-lidar\u002Fouster_example) - Sample code for connecting to and configuring the OS1, reading and visualizing data, and interfacing with ROS.\n* [ros2_ouster_drivers](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Fros2_ouster_drivers) - These are an implementation of ROS2 drivers for the Ouster OS-1 3D lidars.\n* [livox_ros_driver](https:\u002F\u002Fgithub.com\u002FLivox-SDK\u002Flivox_ros_driver) - A new ROS package, specially used to connect LiDAR products produced by Livox.\n* [velodyne](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Fvelodyne) - A collection of ROS packages supporting Velodyne high definition 3D LIDARs.\n* [ublox](https:\u002F\u002Fgithub.com\u002FKumarRobotics\u002Fublox) - Provides support for u-blox GPS receivers.\n* [crazyflie_ros](https:\u002F\u002Fgithub.com\u002Fwhoenig\u002Fcrazyflie_ros) - ROS Driver for Bitcraze Crazyflie.\n* [pointgrey_camera_driver](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Fpointgrey_camera_driver) - ROS driver for Pt. Grey cameras, based on the official FlyCapture2 SDK.\n* [novatel_gps_driver](https:\u002F\u002Fgithub.com\u002Fswri-robotics\u002Fnovatel_gps_driver) - ROS driver for NovAtel GPS \u002F GNSS receivers.\n* [pylon-ros-camera](https:\u002F\u002Fgithub.com\u002Fbasler\u002Fpylon-ros-camera) - The official pylon ROS driver for Basler GigE Vision and USB3 Vision cameras.\n* [ethz_piksi_ros](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fethz_piksi_ros) -  Contains (python) ROS drivers, tools, launch files, and wikis about how to use Piksi Real Time Kinematic (RTK) GPS device in ROS.\n* [sick_safetyscanners](https:\u002F\u002Fgithub.com\u002FSICKAG\u002Fsick_safetyscanners) - A ROS Driver which reads the raw data from the SICK Safety Scanners and publishes the data as a laser_scan msg.\n* [bosch_imu_driver](https:\u002F\u002Fgithub.com\u002Fmdrwiega\u002Fbosch_imu_driver) - A driver for the sensor IMU Bosch BNO055. It was implemented only the UART communication interface (correct sensor mode should be selected).\n* [oxford_gps_eth](https:\u002F\u002Fbitbucket.org\u002FDataspeedInc\u002Foxford_gps_eth\u002F) - Ethernet interface to OxTS GPS receivers using the NCOM packet structure.\n* [ifm3d](https:\u002F\u002Fgithub.com\u002Fifm\u002Fifm3d) - Library and Utilities for working with ifm pmd-based 3D ToF Cameras.\n* [cepton_sdk_redist](https:\u002F\u002Fgithub.com\u002Fceptontech\u002Fcepton_sdk_redist\u002F) - Provides ROS support for Cepton LiDAR.\n* [jetson_csi_cam](https:\u002F\u002Fgithub.com\u002Fpeter-moran\u002Fjetson_csi_cam) - A ROS package making it simple to use CSI cameras on the Nvidia Jetson TK1, TX1, or TX2 with ROS.\n* [ros_astra_camera](https:\u002F\u002Fgithub.com\u002Forbbec\u002Fros_astra_camera) - A ROS driver for Orbbec 3D cameras.\n* [spot_ros](https:\u002F\u002Fgithub.com\u002Fclearpathrobotics\u002Fspot_ros) - ROS Driver for Spot.\n* [blickfeld-scanner-lib](https:\u002F\u002Fgithub.com\u002FBlickfeld\u002Fblickfeld-scanner-lib) - Cross-platform library to communicate with LiDAR devices of the Blickfeld GmbH.\n* [TauLidarCamera](https:\u002F\u002Fgithub.com\u002FOnionIoT\u002Ftau-LiDAR-camera) - The host-side API for building applications with the Tau LiDAR Camera.\n\n\n## Security\n* [owasp-threat-dragon-desktop](https:\u002F\u002Fgithub.com\u002Fmike-goodwin\u002Fowasp-threat-dragon-desktop) - Threat Dragon is a free, open-source, cross-platform threat modeling application including system diagramming and a rule engine to auto-generate threats\u002Fmitigations.\n* [launch_ros_sandbox](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Flaunch_ros_sandbox) - Can define launch files running nodes in restrained environments, such as Docker containers or separate user accounts with limited privileges.\n* [wolfssl](https:\u002F\u002Fgithub.com\u002FwolfSSL\u002Fwolfssl) - A small, fast, portable implementation of TLS\u002FSSL for embedded devices to the cloud.\n* [CANalyzat0r](https:\u002F\u002Fgithub.com\u002Fschutzwerk\u002FCANalyzat0r) - Security analysis toolkit for proprietary car protocols.\n* [RSF](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002FRSF) - Robot Security Framework (RSF) is a standardized methodology to perform security assessments in robotics.\n* [How-to-Secure-A-Linux-Server](https:\u002F\u002Fgithub.com\u002Fimthenachoman\u002FHow-To-Secure-A-Linux-Server) - An evolving how-to guide for securing a Linux server.\n* [lynis](https:\u002F\u002Fgithub.com\u002FCISOfy\u002Flynis) - Security auditing tool for Linux, macOS, and UNIX-based systems. Assists with compliance testing (HIPAA\u002FISO27001\u002FPCI DSS) and system hardening.\n* [OpenVPN](https:\u002F\u002Fgithub.com\u002FOpenVPN\u002Fopenvpn) - An open source VPN daemon.\n* [openfortivpn](https:\u002F\u002Fgithub.com\u002Fadrienverge\u002Fopenfortivpn) - A client for PPP+SSL VPN tunnel services and compatible with Fortinet VPNs.\n* [WireGuard](https:\u002F\u002Fgithub.com\u002FWireGuard\u002FWireGuard) - WireGuard is a novel VPN that runs inside the Linux Kernel and utilizes state-of-the-art cryptography.\n* [ssh-auditor](https:\u002F\u002Fgithub.com\u002Fncsa\u002Fssh-auditor) - Scans for weak ssh passwords on your network.\n* [vulscan](https:\u002F\u002Fgithub.com\u002Fscipag\u002Fvulscan) - Advanced vulnerability scanning with Nmap NSE.\n* [nmap-vulners](https:\u002F\u002Fgithub.com\u002FvulnersCom\u002Fnmap-vulners) - NSE script based on Vulners.com API.\n* [brutespray](https:\u002F\u002Fgithub.com\u002Fx90skysn3k\u002Fbrutespray) - Automatically attempts default creds on found services.\n* [fail2ban](https:\u002F\u002Fgithub.com\u002Ffail2ban\u002Ffail2ban) - Daemon to ban hosts that cause multiple authentication errors.\n* [DependencyCheck](https:\u002F\u002Fgithub.com\u002Fjeremylong\u002FDependencyCheck) - A software composition analysis utility that detects publicly disclosed vulnerabilities in application dependencies.\n* [Firejail](https:\u002F\u002Fgithub.com\u002Fnetblue30\u002Ffirejail) - A SUID sandbox program that reduces the risk of security breaches by restricting the running environment of untrusted applications using Linux namespaces, seccomp-bpf and Linux capabilities.\n* [RVD](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002FRVD) - Robot Vulnerability Database. Community-contributed archive of robot vulnerabilities and weaknesses.\n* [ros2_dds_security](http:\u002F\u002Fdesign.ros2.org\u002Farticles\u002Fros2_dds_security.html) - Adding security enhancements by defining a Service Plugin Interface (SPI) architecture, a set of builtin implementations of the SPIs, and the security model enforced by the SPIs.\n* [Security-Enhanced Linux](https:\u002F\u002Fgithub.com\u002FSELinuxProject\u002Fselinux) - A Linux kernel security module that provides a mechanism for supporting access control security policies, including mandatory access controls (MAC).\n* [OpenTitan](https:\u002F\u002Fgithub.com\u002FlowRISC\u002Fopentitan) - Will make the silicon Root of Trust design and implementation more transparent, trustworthy, and secure for enterprises, platform providers, and chip manufacturers. OpenTitan is administered by lowRISC CIC as a collaborative project to produce high quality, open IP for instantiation as a full-featured product.\n* [bandit](https:\u002F\u002Fgithub.com\u002FPyCQA\u002Fbandit) - A tool designed to find common security issues in Python code.\n* [hardening](https:\u002F\u002Fgithub.com\u002Fkonstruktoid\u002Fhardening) - A quick way to make a Ubuntu server a bit more secure.\n* [Passbolt](https:\u002F\u002Fgithub.com\u002Fpassbolt\u002Fpassbolt_docker) - Passbolt is a free and open source password manager that allows team members to store and share credentials securely.\n* [gopass](https:\u002F\u002Fgithub.com\u002Fgopasspw\u002Fgopass) - A password manager for the command line written in Go.\n* [pass](https:\u002F\u002Fwww.passwordstore.org\u002F) - The standard unix password manager.\n* [Vault](https:\u002F\u002Fgithub.com\u002Fhashicorp\u002Fvault) - A tool for securely accessing secrets. A secret is anything that you want to tightly control access to, such as API keys, passwords, certificates, and more.\n* [legion](https:\u002F\u002Fgithub.com\u002FGoVanguard\u002Flegion) - An open source, easy-to-use, super-extensible and semi-automated network penetration testing framework that aids in discovery, reconnaissance and exploitation of information systems.\n* [openscap](https:\u002F\u002Fgithub.com\u002FOpenSCAP\u002Fopenscap) - The oscap program is a command line tool that allows users to load, scan, validate, edit, and export SCAP documents.\n\n\n## Datasets\n* [Papers With Code](https:\u002F\u002Fwww.paperswithcode.com\u002Fdatasets) - Thousands of machine learning datasets provided by Papers With Code.\n* [KITTI-360](https:\u002F\u002Fgithub.com\u002Fautonomousvision\u002Fkitti360Scripts) -  This large-scale dataset contains 320k images and 100k laser scans in a driving distance of 73.7km.\n* [waymo_ros](https:\u002F\u002Fgithub.com\u002FYonoHub\u002Fwaymo_ros) - This is a ROS package to connect Waymo open dataset to ROS.\n* [waymo-open-dataset](https:\u002F\u002Fgithub.com\u002Fwaymo-research\u002Fwaymo-open-dataset) - The Waymo Open Dataset is comprised of high-resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions.\n* [Ford Autonomous Vehicle Dataset](https:\u002F\u002Favdata.ford.com\u002Fhome\u002Fdefault.aspx) - Ford presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles at different days and times.\n* [awesome-robotics-datasets](https:\u002F\u002Fgithub.com\u002Fsunglok\u002Fawesome-robotics-datasets) - A collection of useful datasets for robotics and computer vision.\n* [nuscenes-devkit](https:\u002F\u002Fgithub.com\u002Fnutonomy\u002Fnuscenes-devkit) - The devkit of the nuScenes dataset.\n* [dataset-api](https:\u002F\u002Fgithub.com\u002FApolloScapeAuto\u002Fdataset-api) - This is a repo of toolkit for ApolloScape Dataset, CVPR 2019 Workshop on Autonomous Driving Challenge and ECCV 2018 challenge.\n* [utbm_robocar_dataset](https:\u002F\u002Fgithub.com\u002Fepan-utbm\u002Futbm_robocar_dataset) - EU Long-term Dataset with Multiple Sensors for Autonomous Driving.\n* [DBNet](https:\u002F\u002Fgithub.com\u002Fdriving-behavior\u002FDBNet) - A Large-Scale Dataset for Driving Behavior Learning.\n* [argoverse-api](https:\u002F\u002Fgithub.com\u002Fargoai\u002Fargoverse-api) - Official GitHub repository for Argoverse dataset.\n* [DDAD](https:\u002F\u002Fgithub.com\u002FTRI-ML\u002FDDAD) - A new autonomous driving benchmark from TRI (Toyota Research Institute) for long range (up to 250m) and dense depth estimation in challenging and diverse urban conditions.\n* [pandaset-devkit](https:\u002F\u002Fgithub.com\u002Fscaleapi\u002Fpandaset-devkit) - Public large-scale dataset for autonomous driving provided by Hesai & Scale.\n* [a2d2_to_ros](https:\u002F\u002Fgitlab.com\u002FMaplessAI\u002Fexternal\u002Fa2d2_to_ros) - Utilities for converting A2D2 data sets to ROS bags.\n* [awesome-satellite-imagery-datasets](https:\u002F\u002Fgithub.com\u002Fchrieke\u002Fawesome-satellite-imagery-datasets) - List of satellite image training datasets with annotations for computer vision and deep learning.\n* [sentinelsat](https:\u002F\u002Fgithub.com\u002Fsentinelsat\u002Fsentinelsat) - Search and download Copernicus Sentinel satellite images.\n* [adas-dataset-form](https:\u002F\u002Fwww.flir.com\u002Foem\u002Fadas\u002Fadas-dataset-form\u002F) - Thermal Dataset for Algorithm Training.\n* [h3d](https:\u002F\u002Fusa.honda-ri.com\u002Fh3d) - The H3D is a large scale full-surround 3D multi-object detection and tracking dataset from Honda.\n* [Mapillary Vistas Dataset](https:\u002F\u002Fwww.mapillary.com\u002Fdataset\u002Fvistas) - A diverse street-level imagery dataset with pixel‑accurate and instance‑specific human annotations for understanding street scenes around the world.\n* [TensorFlow Datasets](https:\u002F\u002Fwww.tensorflow.org\u002Fdatasets\u002Fcatalog\u002Foverview) - TensorFlow Datasets provides many public datasets as tf.data.Datasets.\n* [racetrack-database](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fracetrack-database) - Contains center lines (x- and y-coordinates), track widths and race lines for over 20 race tracks (mainly F1 and DTM) all over the world.\n* [BlenderProc](https:\u002F\u002Fgithub.com\u002FDLR-RM\u002FBlenderProc) - A procedural Blender pipeline for photorealistic training image generation.\n* [Atlatec Sample Map Data](https:\u002F\u002Fwww.atlatec.de\u002Fgetsampledata.html) - 3D map for autonomous driving and simulation created from nothing but two cameras and GPS in downtown San Francisco.\n* [Lyft Level 5 Dataset](https:\u002F\u002Fself-driving.lyft.com\u002Flevel5\u002Fdata\u002F) - Level 5 is developing a self-driving system for the Lyft network. We're collecting and processing data from our autonomous fleet and sharing it with you.\n* [holicity](https:\u002F\u002Fgithub.com\u002Fzhou13\u002Fholicity) - A City-Scale Data Platform for Learning Holistic 3D Structures.\n* [UTD19](https:\u002F\u002Futd19.ethz.ch\u002F) - Largest multi-city traffic dataset publically available.\n* [ASTYX HIRES2019 DATASET](http:\u002F\u002Fwww.pinchofintelligence.com\u002Fvisualising-lidar-and-radar-in-virtual-reality\u002F) - Automotive Radar Dataset for Deep Learning Based 3D Object Detection.\n* [Objectron](https:\u002F\u002Fgithub.com\u002Fgoogle-research-datasets\u002FObjectron\u002F) - A collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment.\n* [ONCE dataset](https:\u002F\u002Fonce-for-auto-driving.github.io\u002Findex.html) - A large-scale autonomous driving dataset with 2D&3D object annotations.\n\n## Footnotes\n\nThanks to the team of [xpp](http:\u002F\u002Fwiki.ros.org\u002Fxpp) for creating this awesome GIF we use.\n","# 令人惊叹的机器人工具集 [![Awesome](https:\u002F\u002Fawesome.re\u002Fbadge.svg)](https:\u002F\u002Fawesome.re)\n\n**一份精心整理的、用于专业机器人开发的工具列表，涵盖 C++ 和 Python，同时涉及 ROS、自动驾驶和航空航天领域**\n\n> 要避免重复造轮子，首先得了解“轮子”是什么。这份列表旨在展示软件和硬件开发中丰富多样的开源免费工具，这些工具在专业机器人开发中非常有用。\n\n为了使这份列表保持活力、提升质量并不断扩展，您的贡献至关重要。您可以在[贡献指南](CONTRIBUTING.md)以及相关的[博客文章](https:\u002F\u002Frosindustrial.org\u002Fnews\u002F2020\u002F5\u002F11\u002Fguest-article-on-the-story-of-the-autonomous-logistics)中了解更多关于其起源及参与方式。所有新加入的项目条目都将由[protontypes](https:\u002F\u002Ftwitter.com\u002Fprotontypes)发布一条推文。\n\n\u003C!--lint ignore double-link-->\n[\u003Cimg src=\"https:\u002F\u002Fi.imgur.com\u002FqI1Jfyl.gif\" align=\"right\" width=\"60%\" \u002F>](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fxpp)\n\u003C!--lint ignore double-link-->\n[![](https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Ffollow\u002Fprotontypes?style=social)](https:\u002F\u002Ftwitter.com\u002Fintent\u002Ffollow?screen_name=protontypes) [![加入 https:\u002F\u002Fgitter.im\u002Fprotontypes\u002Fcommunity 的聊天室](https:\u002F\u002Fbadges.gitter.im\u002Fprotontypes\u002Fcommunity.svg)](https:\u002F\u002Fgitter.im\u002Fprotontypes\u002Fcommunity?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n\n\u003C!--toc-->\n\n## 目录\n\n* [通信与协调](#communication-and-coordination)\n* [文档与演示](#documentation-and-presentation)\n* [需求与安全](#requirements-and-safety)\n* [架构与设计](#architecture-and-design)\n* [框架与栈](#frameworks-and-stacks)\n* [开发环境](#development-environment)\n  * [代码编写与运行](#code-and-run)\n  * [模板](#template)\n  * [构建与部署](#build-and-deploy)\n  * [单元测试与集成测试](#unit-and-integration-test)\n  * [代码检查与格式化](#lint-and-format)\n  * [调试与追踪](#debugging-and-tracing)\n  * [版本控制](#version-control)\n* [仿真](#simulation)\n* [电子与机械](#electronics-and-mechanics)\n* [传感器处理](#sensor-processing)\n  * [标定与变换](#calibration-and-transformation)\n  * [感知流水线](#perception-pipeline)\n  * [机器学习](#machine-learning)\n  * [并行处理](#parallel-processing)\n  * [图像处理](#image-processing)\n  * [雷达处理](#radar-processing)\n  * [激光雷达与点云处理](#lidar-and-point-cloud-processing)\n* [定位与状态估计](#localization-and-state-estimation)\n* [同步定位与地图构建](#simultaneous-localization-and-mapping)\n  * [激光雷达](#lidar)\n  * [视觉](#visual)\n  * [矢量地图](#vector-map)\n* [预测](#prediction)\n* [行为与决策](#behavior-and-decision)\n* [规划与控制](#planning-and-control)\n* [用户交互](#user-interaction)\n  * [图形用户界面](#graphical-user-interface)\n  * [声学用户界面](#acoustic-user-interface)\n  * [命令行界面](#command-line-interface)\n* [数据可视化与任务控制](#data-visualization-and-mission-control)\n  * [标注](#annotation)\n  * [点云](#point-cloud)\n  * [RViz](#rviz)\n* [操作系统](#operation-system)\n  * [监控](#monitoring)\n  * [数据库与记录](#database-and-record)\n  * [网络分布式文件系统](#network-distributed-file-system)\n  * [服务器基础设施与高性能计算](#server-infrastructure-and-high-performance-computing)\n  * [嵌入式操作系统](#embedded-operation-system)\n  * [实时内核](#real-time-kernel)\n* [网络与中间件](#network-and-middleware)\n  * [以太网与无线网络](#ethernet-and-wireless-networking)\n  * [控制器局域网](#controller-area-network)\n  * [传感器与执行器接口](#sensor-and-acuator-interfaces)\n* [安全性](#security)\n* [数据集](#datasets)\n\n\u003C!--toc_end-->\n\n## 通信与协调\n* [敏捷开发](https:\u002F\u002Fagilemanifesto.org\u002F) - 敏捷软件开发宣言。\n* [Gitflow](https:\u002F\u002Fgithub.com\u002Fnvie\u002Fgitflow) - 通过将新开发与已完成工作隔离，使并行开发变得非常容易。\n* [DeepL](https:\u002F\u002Fgithub.com\u002Fuinput\u002Fdeeplator) - 一款在线翻译工具，性能超越 Google、Microsoft 和 Facebook。\n* [Taiga](https:\u002F\u002Fgithub.com\u002Fbenhutchins\u002Fdocker-taiga) - 敏捷项目管理工具。\n* [Kanboard](https:\u002F\u002Fgithub.com\u002Fkanboard\u002Fkanboard) - 极简主义看板。\n* [kanban](https:\u002F\u002Fgitlab.com\u002Fleanlabsio\u002Fkanban) - 针对 GitLab 问题的免费、开源、自托管看板。\n* [Gitlab](https:\u002F\u002Fgithub.com\u002Fsameersbn\u002Fdocker-gitlab) - 使用 Docker 搭建的简单自托管 GitLab 服务器。\n* [Gogs](https:\u002F\u002Fgithub.com\u002Fgogs\u002Fgogs) - 构建一个简单、稳定且可扩展的自托管 Git 服务，设置过程极为便捷。\n* [Wekan](https:\u002F\u002Fgithub.com\u002Fwekan\u002Fwekan) - 基于 Meteor 的看板。\n* [JIRA API](https:\u002F\u002Fgithub.com\u002Fpycontribs\u002Fjira) - Jira REST API 的 Python 库。\n* [Taiga API](https:\u002F\u002Fgithub.com\u002Fnephila\u002Fpython-taiga) - Taiga REST API 的 Python 库。\n* [Chronos-Timetracker](https:\u002F\u002Fgithub.com\u002Fweb-pal\u002Fchronos-timetracker) - JIRA 的桌面客户端。轻松跟踪时间、上传工作日志。\n* [Grge](https:\u002F\u002Fgitlab.com\u002FApexAI\u002Fgrge) - Grge 是一个守护进程和命令行工具，用于增强 GitLab 功能。\n* [gitlab-triage](https:\u002F\u002Fgitlab.com\u002Fgitlab-org\u002Fgitlab-triage) - 自动化处理 GitLab 的问题和合并请求分类。\n* [Helpy](https:\u002F\u002Fgithub.com\u002Fhelpyio\u002Fhelpy) - 一款现代化、开源的帮助台客户支持应用。\n* [ONLYOFFICE](https:\u002F\u002Fgithub.com\u002FONLYOFFICE\u002FCommunityServer) - 一个免费的开源协作系统，用于在一个平台上管理文档、项目、客户关系和电子邮件往来。\n* [discourse](https:\u002F\u002Fgithub.com\u002Fdiscourse\u002Fdiscourse) - 社区讨论平台。免费、开放、简单。\n* [Gerrit](https:\u002F\u002Fgerrit.googlesource.com\u002Fgerrit\u002F) - 一个基于 Git 的代码审查和项目管理工具。\n* [jitsi-meet](https:\u002F\u002Fgithub.com\u002Fjitsi\u002Fjitsi-meet) - 安全、简单且可扩展的视频会议，可作为独立应用使用，也可嵌入到您的 Web 应用程序中。\n* [mattermost](https:\u002F\u002Fgithub.com\u002Fmattermost\u002Fmattermost-server) - 一款开源、私有云部署的 Slack 替代品。\n* [openproject](https:\u002F\u002Fgithub.com\u002Fopf\u002Fopenproject) - 领先的开源项目管理软件。\n* [leantime](https:\u002F\u002Fgithub.com\u002FLeantime\u002Fleantime) - Leantime 是面向创新者的精益项目管理系统。\n* [gitter](https:\u002F\u002Fgitlab.com\u002Fgitlab-org\u002Fgitter\u002Fwebapp) - Gitter 是一个聊天和社交平台，通过消息、内容和发现功能帮助管理、发展和连接社区。\n\n## 文档与演示\n* [Typora](https:\u002F\u002Ftypora.io\u002F) - 极简主义 Markdown 编辑器。\n* [Markor](https:\u002F\u002Fgithub.com\u002Fgsantner\u002Fmarkor) - 适用于 Android 设备的简单 Markdown 编辑器。\n* [Pandoc](https:\u002F\u002Fgithub.com\u002Fjgm\u002Fpandoc) - 通用标记转换工具。\n* [Yaspeller](https:\u002F\u002Fgithub.com\u002Fhcodes\u002Fyaspeller) - 命令行拼写检查工具。\n* [ReadtheDocs](https:\u002F\u002Fdocs.readthedocs.io\u002Fen\u002Fstable\u002Fdevelopment\u002Fbuildenvironments.html) - 搭建本地 ReadtheDocs 服务器。\n* [Doxygen](https:\u002F\u002Fgithub.com\u002Fdoxygen\u002Fdoxygen) - Doxygen 是从带注释的 C++ 源代码生成文档的事实标准工具。\n* [Sphinx](https:\u002F\u002Fgithub.com\u002Fsphinx-doc\u002Fsphinx\u002F) - 一款易于为 Python 项目创建智能且美观文档的工具。\n* [Word-to-Markdown](https:\u002F\u002Fgithub.com\u002Fbenbalter\u002Fword-to-markdown) - 一个 Ruby gem，用于从 Microsoft Word 文档中提取内容。\n* [paperless](https:\u002F\u002Fgithub.com\u002Fthe-paperless-project\u002Fpaperless) - 索引并归档所有扫描的纸质文档。\n* [carbon](https:\u002F\u002Fgithub.com\u002Fcarbon-app\u002Fcarbon) - 分享精美的源代码图片。\n* [undraw](https:\u002F\u002Fundraw.co\u002Fillustrations) - 免费的专业商务 SVG 图形，易于自定义。\n* [asciinema](https:\u002F\u002Fgithub.com\u002Fasciinema\u002Fasciinema) - 可轻松录制终端会话，并在终端及网页浏览器中回放。\n* [inkscape](https:\u002F\u002Finkscape.org\u002F) - Inkscape 是适用于 Linux、Windows 和 macOS 的专业矢量图形编辑器。\n* [Reveal-Hugo](https:\u002F\u002Fgithub.com\u002Fdzello\u002Freveal-hugo) - 一款基于 Reveal.js 的 Hugo 主题，使创作和定制变得轻而易举。借助它，您可以将任何格式正确的 Hugo 内容转换为 HTML 演示文稿。\n* [Hugo-Webslides](https:\u002F\u002Fgithub.com\u002FRCJacH\u002Fhugo-webslides) - 这是一个使用 markdown 创建 WebSlides 演示文稿的 Hugo 模板。\n* [jupyter2slides](https:\u002F\u002Fgithub.com\u002Fdatitran\u002Fjupyter2slides) - 基于 Jupyter Notebook + Reveal.js 的云原生演示文稿。\n* [patat](https:\u002F\u002Fgithub.com\u002Fjaspervdj\u002Fpatat) - 使用 Pandoc 进行基于终端的演示。\n* [github-changelog-generator](https:\u002F\u002Fgithub.com\u002Fgithub-changelog-generator\u002Fgithub-changelog-generator) - 自动从 GitHub 上的标签、问题、标签和拉取请求生成变更日志。\n* [GitLab-Release-Note-Generator](https:\u002F\u002Fgithub.com\u002Fjk1z\u002FGitLab-Release-Note-Generator) - 一款 GitLab 发布说明生成器，可基于最新标签生成发布说明。\n* [OCRmyPDF](https:\u002F\u002Fgithub.com\u002Fjbarlow83\u002FOCRmyPDF) - 为扫描的 PDF 文件添加 OCR 文本层，使其可被搜索。\n* [papermill](https:\u002F\u002Fgithub.com\u002Fnteract\u002Fpapermill) - 用于参数化、执行和分析 Jupyter Notebooks 的工具。\n* [docsy](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fdocsy-example) - 使用 Docsy Hugo 主题的示例文档网站。\n* [actions-hugo](https:\u002F\u002Fgithub.com\u002Fpeaceiris\u002F) - 将基于 Hugo 的网站部署到 GitHub Pages。\n* [overleaf](https:\u002F\u002Fgithub.com\u002Foverleaf\u002Foverleaf) - 开源在线实时协作 LaTeX 编辑器。\n* [landslide](https:\u002F\u002Fgithub.com\u002Fadamzap\u002Flandslide) - 从 markdown、ReST 或 textile 生成 HTML5 幻灯片。\n* [libreoffice-impress-templates](https:\u002F\u002Fgithub.com\u002Fdohliam\u002Flibreoffice-impress-templates) - 免费授权的 LibreOffice Impress 模板。\n* [opensourcedesign](https:\u002F\u002Fopensourcedesign.net\u002Fresources\u002F) - 免费设计与 Logo 创作的社区及资源。\n* [olive](https:\u002F\u002Fwww.olivevideoeditor.org\u002F) - 一款免费的非线性视频编辑器，旨在提供功能齐全的高端专业视频编辑软件替代方案。\n* [buku](https:\u002F\u002Fgithub.com\u002Fjarun\u002Fbuku) - 独立于浏览器的书签管理器。\n* [swiftlatex](https:\u002F\u002Fwww.swiftlatex.com\u002F) - 一款所见即所得的基于浏览器的 LaTeX 编辑器。\n* [ReLaXed](https:\u002F\u002Fgithub.com\u002FRelaxedJS\u002FReLaXed) - 允许使用 CSS 和 JavaScript 定义复杂的 PDF 布局，同时以接近 Markdown 或 LaTeX 的友好、极简语法编写内容。\n* [foam](https:\u002F\u002Fgithub.com\u002Ffoambubble\u002Ffoam) - Foam 是一款受 Roam Research 启发的个人知识管理和共享系统，基于 Visual Studio Code 和 GitHub 构建。\n* [CodiMD](https:\u002F\u002Fgithub.com\u002Fcodimd\u002Fserver) - 开源在线实时协作团队文档的 markdown 工具。\n* [jupyter-book](https:\u002F\u002Fgithub.com\u002Fexecutablebooks\u002Fjupyter-book) - 从 Jupyter Notebooks 构建交互式、出版质量的文档。\n* [InvoiceNet](https:\u002F\u002Fgithub.com\u002FnaiveHobo\u002FInvoiceNet) - 用于从发票文档中提取智能信息的深度神经网络。\n* [tesseract](https:\u002F\u002Fgithub.com\u002Ftesseract-ocr\u002Ftesseract) - 开源 OCR 引擎。\n* [mkdocs](https:\u002F\u002Fgithub.com\u002Fmkdocs\u002Fmkdocs\u002F) - 一款快速、简单且美观的静态站点生成器，专为构建项目文档而设计。\n* [PlotNeuralNet](https:\u002F\u002Fgithub.com\u002FHarisIqbal88\u002FPlotNeuralNet) - 用于报告和演示文稿绘制神经网络的 LaTeX 代码。\n* [Excalidraw](https:\u002F\u002Fgithub.com\u002Fexcalidraw\u002Fexcalidraw) - 用于绘制手绘风格图表的虚拟白板。\n* [SVGrepo](https:\u002F\u002Fwww.svgrepo.com\u002F) - 下载可用于商业用途的免费 SVG 矢量图。\n* [gollum](https:\u002F\u002Fgithub.com\u002Fgollum\u002Fgollum) - 一款简单的 Git 驱动维基，具有友好的 API 和本地前端。\n* [GanttLab](https:\u002F\u002Fgitlab.com\u002Fganttlab\u002Fganttlab) - 易于使用、功能完善的 Gantt 图表，适用于 GitLab 和 GitHub。\n* [Zotero](https:\u002F\u002Fgithub.com\u002Fzotero\u002Fzotero) - 一款免费、易于使用的工具，可帮助您收集、组织、引用和分享研究资料。\n\n## 需求与安全\n* [awesome-safety-critical](https:\u002F\u002Fgithub.com\u002Fstanislaw\u002Fawesome-safety-critical) - 关于编写安全关键型软件的编程实践资源列表。\n* [open-autonomous-safety](https:\u002F\u002Fgithub.com\u002Fvoyage\u002Fopen-autonomous-safety) - OAS 是 Voyage 全开源的安全流程与测试规程库，旨在补充全球自动驾驶初创企业的现有安全体系。\n* [CarND-Functional-Safety-Project](https:\u002F\u002Fgithub.com\u002Fudacity\u002FCarND-Functional-Safety-Project) - 在这个 Udacity 项目中创建功能安全文档。\n* [Automated Valet Parking Safety Documents](https:\u002F\u002Favp-project.uk\u002Fpublication-of-safety-documents) - 为支持在停车场内使用 StreetDrone 测试车辆安全测试自动代客泊车功能而创建。\n* [safe_numerics](https:\u002F\u002Fgithub.com\u002Fboostorg\u002Fsafe_numerics) - 替代标准数值类型的库，在发生错误时会抛出异常。\n* [Air Vehicle C++ development coding standards](http:\u002F\u002Fwww.stroustrup.com\u002FJSF-AV-rules.pdf) - 为 C++ 程序员提供指导，帮助他们采用良好的编程风格和成熟的编程实践，从而编写出安全、可靠、可测试且易于维护的代码。\n* [AUTOSAR Coding Standard](https:\u002F\u002Fwww.autosar.org\u002Ffileadmin\u002Fuser_upload\u002Fstandards\u002Fadaptive\u002F17-10\u002FAUTOSAR_RS_CPP14Guidelines.pdf) - 关于在关键及安全相关系统中使用 C++14 语言的指南。\n* [The W-Model and Lean Scaled Agility for Engineering](https:\u002F\u002Fassets.vector.com\u002Fcms\u002Fcontent\u002Fconsulting\u002Fpublications\u002FAgileSystemsEngineering_Vector_Ford.pdf) - 福特采用了 Vector 提供的敏捷 V 模型方法，可用于安全相关的项目管理。\n* [doorstop](https:\u002F\u002Fgithub.com\u002Fdoorstop-dev\u002Fdoorstop) - 使用版本控制进行需求管理。\n* [capella](https:\u002F\u002Fwww.eclipse.org\u002Fcapella\u002F) - 功能全面、可扩展且经过现场验证的 MBSE 工具与方法，用于成功设计系统架构。\n* [robmosys](https:\u002F\u002Frobmosys.eu\u002F) - RobMoSys 倡导一种集成式方法，基于当前以代码为中心的机器人平台，通过应用模型驱动的方法和工具来实现。\n* [Papyrus for Robotics](https:\u002F\u002Fwww.eclipse.org\u002Fpapyrus\u002Fcomponents\u002Frobotics\u002F) - 一款符合 RobMoSys 方法论的图形化编辑工具，专用于机器人应用。\n* [fossology](https:\u002F\u002Fgithub.com\u002Ffossology\u002Ffossology) - 一个可在命令行运行许可证、版权及出口管制扫描的工具包。\n* [ScenarioArchitect](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002FScenarioArchitect) - Scenario Architect 是一款基础 Python 工具，用于生成、导入和导出简短的场景快照。\n\n\n## 架构与设计\n* [Guidelines](https:\u002F\u002Fgithub.com\u002FS2-group\u002Ficse-seip-2020-replication-package\u002Fblob\u002Fmaster\u002FICSE_SEIP_2020.pdf) - 如何构建基于 ROS 的系统架构。\n* [yEd](https:\u002F\u002Fwww.yworks.com\u002Fproducts\u002Fyed) - 一款功能强大的桌面应用程序，可用于快速高效地生成高质量的图表。\n* [yed_py](https:\u002F\u002Fgithub.com\u002Ftrue-grue\u002Fyed_py) - 生成可在 yEd 中打开的 graphML 文件。\n* [Plantuml](https:\u002F\u002Fgithub.com\u002Fplantuml\u002Fplantuml-server) - 一个 Web 应用程序，可在实时文档中动态生成 UML 图。\n* [rqt_graph](https:\u002F\u002Fwiki.ros.org\u002Frqt_graph) - 提供用于可视化 ROS 计算图的 GUI 插件。\n* [rqt_launchtree](https:\u002F\u002Fgithub.com\u002Fpschillinger\u002Frqt_launchtree) - 一个用于层次化 launchfile 配置 introspection 的 RQT 插件。\n* [cpp-dependencies](https:\u002F\u002Fgithub.com\u002Ftomtom-international\u002Fcpp-dependencies) - 用于检查 C++ #include 依赖关系的工具（生成 .dot 格式的依赖关系图）。\n* [pydeps](https:\u002F\u002Fgithub.com\u002Fthebjorn\u002Fpydeps) - 用于生成 Python 模块依赖关系图。\n* [aztarna](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002Faztarna) - 一款用于机器人足迹分析的工具。\n* [draw.io](https:\u002F\u002Fwww.draw.io\u002F) - 一款免费的在线绘图软件，可用于制作流程图、过程图、组织结构图、UML、ER 及网络图。\n* [vscode-drawio](https:\u002F\u002Fgithub.com\u002Fhediet\u002Fvscode-drawio) - 此扩展将 Draw.io 集成到 VS Code 中。\n* [Architecture_Decision_Record](https:\u002F\u002Fgithub.com\u002Fjoelparkerhenderson\u002Farchitecture_decision_record) - 一份记录重要架构决策及其背景和影响的文档。\n\n## 框架与栈\n* [ROS](https:\u002F\u002Fgithub.com\u002Fros) - （机器人操作系统）提供库和工具，帮助软件开发者构建机器人应用。\n* [awesome-ros2](https:\u002F\u002Fgithub.com\u002Ffkromer\u002Fawesome-ros2) - 精选的优秀机器人操作系统版本2.0（ROS 2）资源和库列表。\n* [Autoware.Auto](https:\u002F\u002Fgitlab.com\u002Fautowarefoundation\u002Fautoware.auto) - Autoware.Auto 将一流的软件工程应用于自动驾驶领域。\n* [Autoware.ai](https:\u002F\u002Fgithub.com\u002FAutoware-AI) - Autoware.AI 是全球首个面向自动驾驶技术的“一体化”开源软件。\n* [OpenPilot](https:\u002F\u002Fgithub.com\u002Fcommaai\u002Fopenpilot) - 开源自适应巡航控制（ACC）和车道保持辅助系统（LKAS）。\n* [Apollo](https:\u002F\u002Fgithub.com\u002FApolloAuto\u002Fapollo) - 高性能、灵活的架构，可加速自动驾驶车辆的开发、测试和部署。\n* [PythonRobotics](https:\u002F\u002Fgithub.com\u002FAtsushiSakai\u002FPythonRobotics\u002F) - 这是一个包含机器人算法的 Python 代码集合，尤其适用于自主导航。\n* [Stanford Self Driving Car Code](https:\u002F\u002Fgithub.com\u002Femmjaykay\u002Fstanford_self_driving_car_code) - 斯坦福大学参与 DARPA 大挑战赛车辆的相关代码。\n* [astrobee](https:\u002F\u002Fgithub.com\u002Fnasa\u002Fastrobee) - Astrobee 是一款自由飞行机器人，设计用于在国际空间站（ISS）内部作为有效载荷运行。\n* [CARMAPlatform](https:\u002F\u002Fgithub.com\u002Fusdot-fhwa-stol\u002FCARMAPlatform) - 支持协同式自动驾驶插件。\n* [Automotive Grade Linux](https:\u002F\u002Fwww.automotivelinux.org\u002F) - Automotive Grade Linux 是一个协作性的开源项目，汇聚汽车制造商、供应商和技术公司，以加速开发和采用面向互联汽车的完全开放的软件栈。\n* [PX4](https:\u002F\u002Fgithub.com\u002FPX4\u002FFirmware) - 用于无人机及其他无人飞行器的开源飞控软件。\n* [KubOS](https:\u002F\u002Fgithub.com\u002Fkubos\u002Fkubos) - 用于卫星的开源软件栈。\n* [mod_vehicle_dynamics_control](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fmod_vehicle_dynamics_control) - TUM Roborace 团队软件栈——路径跟踪控制、速度控制、曲率控制及状态估计。\n* [Aslan](https:\u002F\u002Fgithub.com\u002Fproject-aslan\u002FAslan) - 适用于低速环境的开源自动驾驶软件。\n* [open-source-rover](https:\u002F\u002Fgithub.com\u002Fnasa-jpl\u002Fopen-source-rover) - 基于 JPL 火星探测车的可自行组装六轮火星车。\n* [pybotics](https:\u002F\u002Fgithub.com\u002Fengnadeau\u002Fpybotics) - 一个开源且经过同行评审的 Python 工具箱，用于机器人运动学和校准。\n* [makani](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fmakani) - 包含可用的 Makani 飞行模拟器、控制器（自动驾驶仪）、可视化工具以及指挥中心飞行监控工具。\n* [mir_robot](https:\u002F\u002Fgithub.com\u002Fdfki-ric\u002Fmir_robot) - 这是一个社区项目，旨在将 MiR 机器人与 ROS 集成使用。\n* [COMPAS](https:\u002F\u002Fgithub.com\u002Fcompas-dev\u002Fcompas_fab) - COMPAS 框架下的机器人制造包。\n* [JdeRobot Academy](https:\u002F\u002Fgithub.com\u002FJdeRobot\u002FRoboticsAcademy) - JdeRobot Academy 是一套开源练习集，以实践方式学习机器人技术。\n* [clover](https:\u002F\u002Fgithub.com\u002FCopterExpress\u002Fclover) - 基于 ROS 的框架及 RPi 镜像，用于控制搭载 PX4 的无人机。\n* [ArduPilot](https:\u002F\u002Fgithub.com\u002FArduPilot\u002Fardupilot) - 自主飞行器的开源控制软件——包括直升机、固定翼飞机、漫游车、船只和潜水器。\n* [F Prime](https:\u002F\u002Fgithub.com\u002Fnasa\u002Ffprime) - 一种基于组件的框架，支持航天及其他嵌入式软件应用的快速开发和部署。\n\n## 开发环境\n### 编写与运行\n* [Vim-ros](https:\u002F\u002Fgithub.com\u002Ftaketwo\u002Fvim-ros) - 用于 ROS 开发的 Vim 插件。\n* [Visual Studio Code](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fvscode) - 用于编辑-构建-调试循环的代码编辑器。\n* [atom](https:\u002F\u002Fgithub.com\u002Fatom\u002Fatom) - 适合 21 世纪的可扩展文本编辑器。\n* [Teletype](https:\u002F\u002Fgithub.com\u002Fatom\u002Fteletype) - 在 Atom 中与团队成员共享工作区，并实时协作编写代码。\n* [Sublime](https:\u002F\u002Fwww.sublimetext.com\u002F) - 一款功能强大的文本编辑器，适用于代码、标记语言和散文。\n* [ade-cli](https:\u002F\u002Fgitlab.com\u002FApexAI\u002Fade-cli) - ADE 开发环境（ADE）利用 Docker 和 GitLab 来管理每个项目的开发工具环境及可选的数据卷镜像。\n* [recipe-wizard](https:\u002F\u002Fgithub.com\u002Ftrn84\u002Frecipe-wizard) - 一个 Dockerfile 生成器，用于在远程无头服务器系统上通过 nvidia-docker2、CUDA、ROS 和 Gazebo 运行 OpenGL（GLX）应用程序。\n* [Jupyter ROS](https:\u002F\u002Fgithub.com\u002FRoboStack\u002Fjupyter-ros) - 用于 ROS 机器人操作系统的 Jupyter 小部件助手。\n* [ros_rqt_plugin](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Fros_qtc_plugin) - 适用于 Python 的 ROS Qt Creator 插件。\n* [xeus-cling](https:\u002F\u002Fgithub.com\u002FQuantStack\u002Fxeus-cling) - C++ 编程语言的 Jupyter 内核。\n* [ROS IDEs](http:\u002F\u002Fwiki.ros.org\u002FIDEs) - 此页面汇集了使用集成开发环境（IDE）与 ROS 相关的经验和建议。\n* [TabNine](https:\u002F\u002Fgithub.com\u002Fzxqfl\u002FTabNine) - 全语言自动补全工具。\n* [kite](https:\u002F\u002Fkite.com\u002F) - 利用机器学习为 Python 提供有用的代码补全。\n* [jedi](https:\u002F\u002Fgithub.com\u002Fdavidhalter\u002Fjedi) - 用于 Python 的自动补全和静态分析库。\n* [roslibpy](https:\u002F\u002Fgithub.com\u002Fgramaziokohler\u002Froslibpy) - Python ROS Bridge 库允许使用 Python 和 IronPython 与开源机器人中间件 ROS 进行交互。\n* [pybind11](https:\u002F\u002Fgithub.com\u002Fpybind\u002Fpybind11) - 实现 C++11 与 Python 之间的无缝互操作。\n* [Sourcetrail](https:\u002F\u002Fgithub.com\u002FCoatiSoftware\u002FSourcetrail) - 免费且开源的跨平台源代码浏览器。\n* [rebound](https:\u002F\u002Fgithub.com\u002Fshobrook\u002Frebound) - 一个命令行工具，在抛出异常时即时检索 Stack Overflow 的相关结果。\n* [mybinder](https:\u002F\u002Fmybinder.org\u002F) - 在可执行环境中打开开源笔记本，使您的代码随时随地可被他人复现。\n* [ROSOnWindows](https:\u002F\u002Fms-iot.github.io\u002FROSOnWindows\u002F) - 面向 Windows 的 ROS1 实验性发布版。\n* [live-share](https:\u002F\u002Fgithub.com\u002FMicrosoftDocs\u002Flive-share) - 在您喜爱的工具中进行实时协作开发。\n* [cocalc](https:\u002F\u002Fgithub.com\u002Fsagemathinc\u002Fcocalc) - 云端协作计算平台。\n* [EasyClangComplete](https:\u002F\u002Fgithub.com\u002Fniosus\u002FEasyClangComplete) - 适用于 Sublime Text 3 的强大 C\u002FC++ 代码补全工具。\n* [vscode-ros](https:\u002F\u002Fgithub.com\u002Fms-iot\u002Fvscode-ros) - 用于机器人操作系统（ROS）开发的 Visual Studio Code 扩展。\n* [awesome-hpp](https:\u002F\u002Fgithub.com\u002Fp-ranav\u002Fawesome-hpp) - 精选的优秀仅头文件 C++ 库列表。\n* [Gitpod](https:\u002F\u002Fgithub.com\u002Fgitpod-io\u002Fgitpod) - 一个开源开发者平台，可自动配置即刻可用的开发环境。\n\n### 模板\n* [ROS](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fros_best_practices\u002Ftree\u002Fmaster\u002Fros_package_template) - 用于C++中ROS节点标准化的模板。\n* [Launch](https:\u002F\u002Fwiki.ros.org\u002Froslaunch\u002FTutorials\u002FRoslaunch%20tips%20for%20larger%20projects) - 关于如何为大型项目创建启动文件的模板。\n* [Bash](https:\u002F\u002Fgithub.com\u002Fralish\u002Fbash-script-template) - 结合最佳实践和多个实用函数的Bash脚本模板。\n* [URDF](https:\u002F\u002Fwiki.ros.org\u002Furdf\u002FExamples) - 不同类型机器人统一机器人描述格式（URDF）的创建示例。\n* [Python](http:\u002F\u002Fwiki.ros.org\u002FPyStyleGuide) - ROS Python代码编写应遵循的风格指南。\n* [Docker](https:\u002F\u002Fade-cli.readthedocs.io\u002Fen\u002Flatest\u002Fcreate-custom-base-image.html) - minimal-ade项目中的Dockerfile展示了如何创建自定义基础镜像的最小示例。\n* [VS Code ROS2工作区模板](https:\u002F\u002Fgithub.com\u002Fathackst\u002Fvscode_ros2_workspace) - 使用VSCode作为ROS2开发IDE的模板。\n\n### 构建与部署\n* [qemu-user-static](https:\u002F\u002Fgithub.com\u002Fmultiarch\u002Fqemu-user-static) - 通过QEMU和binfmt_misc实现对不同多架构容器的执行支持。\n* [在QNX上交叉编译ROS 2](https:\u002F\u002Fgitlab.apex.ai\u002Fsnippets\u002F97) - 介绍如何在QNX上交叉编译ROS 2。\n* [bloom](https:\u002F\u002Fgithub.com\u002Fros-infrastructure\u002Fbloom) - 一个发布自动化工具，使catkin包的发布更加容易。\n* [superflore](https:\u002F\u002Fgithub.com\u002Fros-infrastructure\u002Fsuperflore) - 针对机器人操作系统扩展的平台发布管理器。\n* [catkin_tools](https:\u002F\u002Fgithub.com\u002Fcatkin\u002Fcatkin_tools) - 用于操作catkin的命令行工具。\n* [industrial_ci](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Findustrial_ci) - 适用于ROS仓库的简易持续集成仓库。\n* [ros_gitlab_ci](https:\u002F\u002Fgitlab.com\u002FVictorLamoine\u002Fros_gitlab_ci) - 包含帮助脚本及如何在GitLab实例上托管的ROS项目中使用持续集成（CI）的说明。\n* [gitlab-runner](https:\u002F\u002Fgitlab.com\u002Fgitlab-org\u002Fgitlab-runner) - 运行测试并将结果发送到GitLab。\n* [colcon-core](https:\u002F\u002Fgithub.com\u002Fcolcon\u002Fcolcon-core) - 用于改进构建、测试和使用多个软件包的工作流程的命令行工具。\n* [gitlab-release](https:\u002F\u002Fgitlab.com\u002Falelec\u002Fgitlab-release) - 一个简单的Python3脚本，用于将（CI生成的）文件上传到当前项目的发布（标签）中。\n* [clang](https:\u002F\u002Fgithub.com\u002Fllvm-mirror\u002Fclang) - 这是C语言家族（C、C++、Objective-C和Objective-C++）的编译器前端，作为LLVM编译器基础设施项目的一部分构建。\n* [catkin_virtualenv](https:\u002F\u002Fgithub.com\u002Flocusrobotics\u002Fcatkin_virtualenv) - 通过virtualenv将Python依赖项打包到catkin包中。\n* [pyenv](https:\u002F\u002Fgithub.com\u002Fpyenv\u002Fpyenv) - 简单的Python版本管理工具。\n* [aptly](https:\u002F\u002Fgithub.com\u002Faptly-dev\u002Faptly) - Debian仓库管理工具。\n* [cross_compile](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Fcross_compile) - 用于ROS2交叉编译的资源。\n* [docker_images](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fdocker_images) - OSRF维护的ROS(2)和Gazebo官方Docker镜像。\n* [robot_upstart](https:\u002F\u002Fgithub.com\u002Fclearpathrobotics\u002Frobot_upstart) - 提供一套脚本来协助在Ubuntu Linux PC上启动后台ROS进程。\n* [robot_systemd](http:\u002F\u002Fdocs.ros.org\u002Fkinetic\u002Fapi\u002Frobot_systemd\u002Fhtml\u002F#) - 用于管理roscore和roslaunch启动与关闭的单元。\n* [ryo-iso](https:\u002F\u002Fryo-iso.readthedocs.io\u002Fen\u002Flatest\u002F) - 一个现代化的ISO构建工具，可通过yaml配置文件简化完整机器人操作系统的部署流程。\n* [network_autoconfig](http:\u002F\u002Fdocs.ros.org\u002Fkinetic\u002Fapi\u002Fnetwork_autoconfig\u002Fhtml\u002F) - 对大多数用例自动配置ROS网络，同时不影响需要手动配置的使用场景。\n* [rosbuild](https:\u002F\u002Froscon.ros.org\u002F2016\u002Fpresentations\u002FROSCon2016%20Build%20Farm.pdf) - ROS构建农场。\n* [cros](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Fcros) - ROS框架的纯C单线程实现。\n\n\n### 单元与集成测试\n* [setup-ros](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Fsetup-ros) - 此Action为GitHub Actions设置ROS和ROS 2环境。\n* [UnitTesting](https:\u002F\u002Fwiki.ros.org\u002FQuality\u002FTutorials\u002FUnitTesting) - 该页面阐述了为ROS编写和运行单元测试及集成测试的理由、最佳实践和政策。\n* [googletest](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fgoogletest) - Google的C++测试框架。\n* [pytest](https:\u002F\u002Fgithub.com\u002Fpytest-dev\u002Fpytest\u002F) - pytest框架使得编写小型测试变得简单，同时也能扩展以支持复杂的功能测试。\n* [doctest](https:\u002F\u002Fgithub.com\u002Fonqtam\u002Fdoctest) - 最快且功能丰富的C++11\u002F14\u002F17\u002F20单头文件测试框架，适用于单元测试和TDD。\n* [osrf_testing_tools_cpp](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fosrf_testing_tools_cpp) - 包含C++测试工具，用于OSRF项目。\n* [code_coverage](https:\u002F\u002Fgithub.com\u002Fmikeferguson\u002Fcode_coverage) - 用于运行覆盖率测试的ROS包。\n* [action-ros-ci](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Faction-ros-ci) - 使用colcon构建和测试ROS 2包的GitHub Action。\n\n### 代码检查与格式化\n* [action-ros-lint](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Faction-ros-lint) - 在ROS 2包上运行代码检查工具的GitHub Action。\n* [cppcheck](https:\u002F\u002Fgithub.com\u002Fdanmar\u002Fcppcheck) - C\u002FC++代码的静态分析工具。\n* [hadolint](https:\u002F\u002Fgithub.com\u002Fhadolint\u002Fhadolint) - Dockerfile代码检查工具，可验证内联Bash脚本，由Haskell编写。\n* [shellcheck](https:\u002F\u002Fgithub.com\u002Fkoalaman\u002Fshellcheck) - 用于Shell脚本的静态分析工具。\n* [catkin_lint](https:\u002F\u002Fgithub.com\u002Ffkie\u002Fcatkin_lint) - 检查ROS catkin构建系统的包配置。\n* [pylint](https:\u002F\u002Fgithub.com\u002FPyCQA\u002Fpylint\u002F) - Pylint是一个Python静态代码分析工具，用于查找编程错误、强制执行编码标准、检测代码异味，并提供简单的重构建议。\n* [black](https:\u002F\u002Fgithub.com\u002Fpsf\u002Fblack) - 无妥协的Python代码格式化工具。\n* [pydocstyle](https:\u002F\u002Fgithub.com\u002FPyCQA\u002Fpydocstyle) - 用于检查Python文档字符串规范是否符合要求的静态分析工具。\n* [haros](https:\u002F\u002Fgithub.com\u002Fgit-afsantos\u002Fharos) - ROS应用代码的静态分析工具。\n* [pydantic](https:\u002F\u002Fgithub.com\u002Fsamuelcolvin\u002Fpydantic) - 使用Python类型提示进行数据解析和验证。\n\n### 调试与追踪\n* [heaptrack](https:\u002F\u002Fgithub.com\u002FKDE\u002Fheaptrack) - 追踪所有内存分配，并用堆栈跟踪为这些事件添加注释。\n* [ros2_tracing](https:\u002F\u002Fgitlab.com\u002Fros-tracing\u002Fros2_tracing) - 用于 ROS 2 的追踪工具。\n* [Linuxperf](http:\u002F\u002Fwww.brendangregg.com\u002Flinuxperf.html) - 各种 Linux 性能相关资料。\n* [lptrace](https:\u002F\u002Fgithub.com\u002Fkhamidou\u002Flptrace) - 可以实时查看 Python 程序正在运行哪些函数。\n* [pyre-check](https:\u002F\u002Fgithub.com\u002Ffacebook\u002Fpyre-check) - 高效的 Python 类型检查工具。\n* [FlameGraph](https:\u002F\u002Fgithub.com\u002Fbrendangregg\u002FFlameGraph) - 可视化性能剖析结果。\n* [gpuvis](https:\u002F\u002Fgithub.com\u002Fmikesart\u002Fgpuvis) - GPU 跟踪可视化工具。\n* [sanitizer](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fsanitizers) - AddressSanitizer、ThreadSanitizer、MemorySanitizer。\n* [cppinsights](https:\u002F\u002Fgithub.com\u002Fandreasfertig\u002Fcppinsights) - C++ Insights - 让你以编译器的视角查看源代码。\n* [inspect](https:\u002F\u002Fpymotw.com\u002F2\u002Finspect\u002F) - inspect 模块提供了一系列函数，用于了解当前运行中的对象，包括模块、类、实例、函数和方法等。\n* [Roslaunch 节点在 Valgrind 或 GDB 中运行](https:\u002F\u002Fwiki.ros.org\u002Froslaunch\u002FTutorials\u002FRoslaunch%20Nodes%20in%20Valgrind%20or%20GDB) - 当调试使用 roslaunch 启动的 roscpp 节点时，你可能希望将其在调试程序（如 gdb 或 valgrind）中启动。\n* [pyperformance](https:\u002F\u002Fgithub.com\u002Fpython\u002Fpyperformance) - Python 性能基准测试套件。\n* [qira](https:\u002F\u002Fgithub.com\u002Fgeohot\u002Fqira) - QIRA 是 strace 和 gdb 的替代品。\n* [gdb-frontend](https:\u002F\u002Fgithub.com\u002Frohanrhu\u002Fgdb-frontend) - GDBFrontend 是一个简单、灵活且可扩展的 GUI 调试器。\n* [lttng](https:\u002F\u002Flttng.org\u002Fdocs\u002F) - 开源软件工具包，可用于同时追踪 Linux 内核、用户应用程序和用户库。\n* [ros2-performance](https:\u002F\u002Fgithub.com\u002Firobot-ros\u002Fros2-performance) - 可以轻松创建任意 ROS2 系统，并对其性能进行测量。\n* [bcc](https:\u002F\u002Fgithub.com\u002Fiovisor\u002Fbcc) - 基于 BPF 的 Linux IO 分析、网络监控等工具。\n* [tracy](https:\u002F\u002Fgithub.com\u002Fwolfpld\u002Ftracy) - 实时、纳秒级分辨率的游戏及其他应用远程遥测帧率分析工具。\n* [bpftrace](https:\u002F\u002Fgithub.com\u002Fiovisor\u002Fbpftrace) - 面向 Linux eBPF 的高级追踪语言。\n* [pudb](https:\u002F\u002Fgithub.com\u002Finducer\u002Fpudb) - Python 全屏控制台调试器。\n* [backward-cpp](https:\u002F\u002Fgithub.com\u002Fbombela\u002Fbackward-cpp) - 一款美观的 C++ 堆栈跟踪格式化打印工具。\n* [gdb-dashboard](https:\u002F\u002Fgithub.com\u002Fcyrus-and\u002Fgdb-dashboard) - GDB 控制面板是一个独立的 .gdbinit 文件，基于 Python API 编写，提供模块化的界面来显示被调试程序的相关信息。\n* [hotspot](https:\u002F\u002Fgithub.com\u002FKDAB\u002Fhotspot) - 用于性能分析的 Linux perf GUI。\n* [memory_profiler](https:\u002F\u002Fgithub.com\u002Fpythonprofilers\u002Fmemory_profiler) - 用于监控进程内存消耗的 Python 模块，同时也支持对 Python 程序逐行分析内存使用情况。\n* [ros1_fuzzer](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002Fros1_fuzzer) - 该模糊测试工具旨在通过针对目标节点处理的话题执行模糊测试，帮助开发者和研究人员发现 ROS 节点中的漏洞和缺陷。\n* [vscode-debug-visualizer](https:\u002F\u002Fgithub.com\u002Fhediet\u002Fvscode-debug-visualizer) - 一个 Visual Studio Code 扩展，可在调试过程中可视化数据。\n* [action-tmate](https:\u002F\u002Fgithub.com\u002Fmxschmitt\u002Faction-tmate) - 使用 tmate 通过 SSH 调试 GitHub Actions，从而直接访问运行器系统。\n* [libstatistics_collector](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Flibstatistics_collector) - ROS 2 库，提供用于收集度量数据并计算统计信息的类。\n* [system_metrics_collector](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Fsystem_metrics_collector) - 轻量级、实时的 ROS2 系统指标收集工具。\n\n\n### 版本控制\n* [git-fuzzy](https:\u002F\u002Fgithub.com\u002FbigH\u002Fgit-fuzzy) - 一个高度依赖 fzf 的 Git 命令行界面。\n* [meld](https:\u002F\u002Fgithub.com\u002FGNOME\u002Fmeld) - Meld 是一个可视化的差异比较和合并工具，可以帮助你比较文件、目录以及版本控制项目。\n* [tig](https:\u002F\u002Fgithub.com\u002Fjonas\u002Ftig) - Git 的文本模式界面。\n* [gitg](https:\u002F\u002Fgithub.com\u002FGNOME\u002Fgitg) - Git 的图形用户界面。\n* [git-cola](https:\u002F\u002Fgithub.com\u002Fgit-cola\u002Fgit-cola) - 浓缩咖啡般的 Git GUI。\n* [python-gitlab](https:\u002F\u002Fgithub.com\u002Fpython-gitlab\u002Fpython-gitlab) - 一个提供 GitLab 服务器 API 访问的 Python 包。\n* [bfg-repo-cleaner](https:\u002F\u002Fgithub.com\u002Frtyley\u002Fbfg-repo-cleaner) - 像 git-filter-branch 一样移除大型或有问题的 blob，但速度更快。\n* [nbdime](https:\u002F\u002Fgithub.com\u002Fjupyter\u002Fnbdime) - 用于 Jupyter 笔记本的差异比较和合并工具。\n* [semantic-release](https:\u002F\u002Fgithub.com\u002Fsemantic-release\u002Fsemantic-release) - 完全自动化的版本管理和包发布工具。\n* [go-semrel-gitab](https:\u002F\u002Fgitlab.com\u002Fjuhani\u002Fgo-semrel-gitlab) - 自动化 GitLab 的版本管理。\n* [Git-repo](https:\u002F\u002Fgerrit.googlesource.com\u002Fgit-repo\u002F) - Git-Repo 帮助管理多个 Git 仓库，执行到版本控制系统中的上传操作，并自动化部分开发工作流。\n* [dive](https:\u002F\u002Fgithub.com\u002Fwagoodman\u002Fdive) - 用于探索 Docker 镜像每一层的工具。\n* [dvc](https:\u002F\u002Fgithub.com\u002Fiterative\u002Fdvc) - 数据集和机器学习模型的管理和版本控制工具。\n* [learnGitBranching](https:\u002F\u002Fgithub.com\u002Fpcottle\u002FlearnGitBranching) - 一个 Git 仓库可视化工具、沙盒，以及一系列教育教程和挑战。\n* [gitfs](https:\u002F\u002Fgithub.com\u002FPresslabs\u002Fgitfs) - 可以将远程仓库的分支挂载到本地，之后对文件所做的任何更改都会自动提交到远程仓库。\n* [git-secret](https:\u002F\u002Fgithub.com\u002Fsobolevn\u002Fgit-secret) - 使用授权用户的公钥加密文件，允许受信任的用户使用 PGP 和他们的私钥访问加密数据。\n* [git-sweep](https:\u002F\u002Fgithub.com\u002Farc90\u002Fgit-sweep) - 一个命令行工具，帮助清理已合并到主分支的 Git 分支。\n* [lazygit](https:\u002F\u002Fgithub.com\u002Fjesseduffield\u002Flazygit) - 一个简单的终端 UI，用于 Git 命令，使用 Go 语言和 gocui 库编写。\n* [glab](https:\u002F\u002Fgithub.com\u002Fprofclems\u002Fglab) - 一个开源的 GitLab 命令行工具。\n\n## 模拟\n* [AI2-THOR](https:\u002F\u002Fgithub.com\u002Fallenai\u002Fai2thor) - 基于Unity的Python框架，为家用机器人代理提供交互、导航和操作支持，包含200多个自定义场景、1500多个带标注的对象以及200多种动作。\n* [Drake](https:\u002F\u002Fgithub.com\u002FRobotLocomotion\u002Fdrake) - Drake旨在模拟包括非常复杂动力学在内的机器人系统。\n* [Webots](https:\u002F\u002Fgithub.com\u002Fcyberbotics\u002Fwebots) - Webots是一款开源机器人仿真器，可与[ROS](http:\u002F\u002Fwiki.ros.org\u002Fwebots_ros)及[ROS2](http:\u002F\u002Fwiki.ros.org\u002Fwebots_ros2)等兼容。\n* [lgsv](https:\u002F\u002Fgithub.com\u002Flgsvl\u002Fsimulator) - LG电子美国研发中心开发了一款基于HDRP Unity的多机器人仿真器，专为自动驾驶汽车开发者设计。\n* [carla](https:\u002F\u002Fgithub.com\u002Fcarla-simulator\u002Fcarla) - 用于自动驾驶研究的开源仿真平台。\n* [awesome-CARLA](https:\u002F\u002Fgithub.com\u002FAmin-Tgz\u002Fawesome-CARLA) - 一个精选的CARLA教程、博客及相关项目的列表。\n* [ros-bridge](https:\u002F\u002Fgithub.com\u002Fcarla-simulator\u002Fros-bridge) - CARLA仿真器的ROS桥接工具。\n* [scenario_runner](https:\u002F\u002Fgithub.com\u002Fcarla-simulator\u002Fscenario_runner) - 交通场景定义与执行引擎。\n* [deepdive](https:\u002F\u002Fgithub.com\u002Fdeepdrive\u002Fdeepdrive) - 面向自动驾驶汽车的端到端仿真平台。\n* [uuv_simulator](https:\u002F\u002Fgithub.com\u002Fuuvsimulator\u002Fuuv_simulator) - 用于水下机器人仿真的Gazebo\u002FROS软件包。\n* [AirSim](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FAirSim) - 基于虚幻引擎构建的自动驾驶车辆开源仿真平台。\n* [self-driving-car-sim](https:\u002F\u002Fgithub.com\u002Fudacity\u002Fself-driving-car-sim) - 使用Unity开发的自动驾驶汽车仿真器。\n* [ROSIntegration](https:\u002F\u002Fgithub.com\u002Fcode-iai\u002FROSIntegration) - 用于在虚幻引擎中实现ROS支持的插件。\n* [gym-gazebo](https:\u002F\u002Fgithub.com\u002Ferlerobot\u002Fgym-gazebo) - OpenAI Gym的一个扩展，名为gym-gazebo，用于使用Gazebo进行仿真。\n* [gym-pybullet-drones](https:\u002F\u002Fgithub.com\u002FutiasDSL\u002Fgym-pybullet-drones) - 基于PyBullet的Gym环境，适用于单智能体和多智能体强化学习中的四旋翼无人机控制任务。\n* [safe-control-gym](https:\u002F\u002Fgithub.com\u002FutiasDSL\u002Fsafe-control-gym) - 基于PyBullet的CartPole和四旋翼无人机环境，结合CasADi符号动力学与约束条件，用于安全且鲁棒的学习型控制。\n* [highway-env](https:\u002F\u002Fgithub.com\u002Feleurent\u002Fhighway-env) - 一系列用于自动驾驶和战术决策任务的环境集合。\n* [VREP Interface](http:\u002F\u002Fwww.coppeliarobotics.com\u002FhelpFiles\u002Fen\u002FrosInterf.htm) - VREP仿真器的ROS桥接工具。\n* [car_demo](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fcar_demo) - 这是在Gazebo 9中对普锐斯进行的仿真，传感器数据通过ROS Kinetic发布。\n* [sumo](https:\u002F\u002Fgithub.com\u002Feclipse\u002Fsumo) - Eclipse SUMO是一个开源、高度便携、微观且连续的道路交通仿真软件包，专为处理大型路网而设计。\n* [open-simulation-interface](https:\u002F\u002Fgithub.com\u002FOpenSimulationInterface\u002Fopen-simulation-interface) - 用于虚拟场景中自动驾驶功能环境感知的通用接口。\n* [ESIM](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Frpg_esim\u002F) - 一款开源事件相机仿真器。\n* [Menge](https:\u002F\u002Fgithub.com\u002FMengeCrowdSim\u002FMenge) - 群体仿真框架。\n* [pedsim_ros](https:\u002F\u002Fgithub.com\u002Fsrl-freiburg\u002Fpedsim_ros) - 基于社会力模型的行人仿真器，适用于Gazebo。\n* [opencrg](http:\u002F\u002Fwww.opencrg.org\u002Fdownload.html) - 开放的文件格式和开源工具，用于道路表面的详细描述、创建和评估。\n* [esmini](https:\u002F\u002Fgithub.com\u002Fesmini\u002Fesmini) - 一个基础的OpenSCENARIO播放器。\n* [OpenSceneGraph](https:\u002F\u002Fgithub.com\u002Fopenscenegraph\u002FOpenSceneGraph) - 一款开源高性能3D图形工具包，被视觉仿真、游戏、虚拟现实、科学可视化和建模等领域的应用开发者广泛使用。\n* [morse](https:\u002F\u002Fgithub.com\u002Fmorse-simulator) - 一款基于Blender游戏引擎和Bullet物理引擎的学术机器人仿真器。\n* [ROSIntegrationVision](https:\u002F\u002Fgithub.com\u002Fcode-iai\u002FROSIntegrationVision) - 在虚幻引擎项目中支持启用ROS的RGBD数据采集。\n* [fetch_gazebo](https:\u002F\u002Fgithub.com\u002Ffetchrobotics\u002Ffetch_gazebo) - 包含Fetch Robotics Fetch和Freight Research Edition机器人的Gazebo仿真。\n* [rotors_simulator](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Frotors_simulator) - 提供了一些多旋翼飞行器模型。\n* [flow](https:\u002F\u002Fgithub.com\u002Fflow-project\u002Fflow) - 一个用于交通微观仿真中深度强化学习和控制实验的计算框架。\n* [gnss-ins-sim](https:\u002F\u002Fgithub.com\u002FAceinna\u002Fgnss-ins-sim) - GNSS+惯性导航传感器融合仿真器。包含运动轨迹生成器、传感器模型和导航算法。\n* [Ignition Robotics](https:\u002F\u002Fignitionrobotics.org) - 可在安全性测试中试验控制策略，并在持续集成测试中利用仿真优势。\n* [simulation assets for the SubT](https:\u002F\u002Fsubtchallenge.world\u002Fopenrobotics\u002Ffuel\u002Fcollections\u002FSubT%20Tech%20Repo) - 该合集包含用于SubT挑战虚拟竞赛的Gazebo仿真资产。\n* [gazebo_ros_motors](https:\u002F\u002Fgithub.com\u002Fnilseuropa\u002Fgazebo_ros_motors) - 包含两个Gazebo电机插件，一个带有理想速度控制器，另一个不带控制器，用于模拟直流电机。\n* [map2gazebo](https:\u002F\u002Fgithub.com\u002Fshilohc\u002Fmap2gazebo) - 一个从2D地图创建Gazebo环境的ROS软件包。\n* [sim_vehicle_dynamics](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fsim_vehicle_dynamics) - TUM Roborace团队的车辆动力学仿真软件。\n* [gym-carla](https:\u002F\u002Fgithub.com\u002Fcjy1992\u002Fgym-carla) - 一个用于CARLA仿真器的OpenAI Gym封装。\n* [simbody](https:\u002F\u002Fgithub.com\u002Fsimbody\u002Fsimbody) - 高性能C++多体动力学\u002F物理库，用于模拟关节式生物力学和机械系统，如车辆、机器人和人体骨骼。\n* [gazebo_models](https:\u002F\u002Fgithub.com\u002Fosrf\u002Fgazebo_models) - 该仓库存储了Gazebo模型数据库。\n* [pylot](https:\u002F\u002Fgithub.com\u002Ferdos-project\u002Fpylot) - 基于CARLA仿真器运行的自动驾驶平台。\n* [flightmare](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Fflightmare) - Flightmare由两个主要组件构成：一个基于Unity的可配置渲染引擎，以及一个灵活的动力学仿真物理引擎。\n* [champ](https:\u002F\u002Fgithub.com\u002Fchvmp\u002Fchamp) - 用于CHAMP四足机器人控制器的ROS软件包。\n* [rex-gym](https:\u002F\u002Fgithub.com\u002Fnicrusso7\u002Frex-gym) - 一个开源四足机器人（SpotMicro）的OpenAI Gym环境。\n* [Trick](https:\u002F\u002Fgithub.com\u002Fnasa\u002FTrick) - 由NASA约翰逊航天中心开发，是一个强大的仿真开发框架，使用户能够为航天器开发的各个阶段构建应用程序。\n* [usv_sim_lsa](https:\u002F\u002Fgithub.com\u002Fdisaster-robotics-proalertas\u002Fusv_sim_lsa) - 在Gazebo中进行的无人水面艇仿真，考虑水流和风的影响。\n* [42](https:\u002F\u002Fgithub.com\u002Fericstoneking\u002F42) - 用于航天器姿态控制系统分析与设计的仿真。\n* [Complete_Street_Rule](https:\u002F\u002Fgithub.com\u002Fd-wasserman\u002FComplete_Street_Rule) - 一种面向场景的设计工具，旨在让用户能够在ArcGIS CityEngine中快速生成程序化生成的多模式街道。\n* [AutoCore simulation](https:\u002F\u002Fgithub.com\u002Fautowarefoundation\u002F) - 为Autoware提供测试环境，在早期开发阶段内容可能会随更新而变化。\n* [fields-ignition](https:\u002F\u002Fgithub.com\u002Fazazdeaz\u002Ffields-ignition) - 为Ignition Gazebo生成随机农田场景。\n* [Unity-Robotics-Hub](https:\u002F\u002Fgithub.com\u002FUnity-Technologies\u002FUnity-Robotics-Hub) - Unity中用于机器人仿真的工具、教程、资源和文档的中央存储库。\n* [BlueSky](https:\u002F\u002Fgithub.com\u002FTUDelft-CNS-ATM\u002Fbluesky) - BlueSky的目标是为所有希望可视化、分析或模拟空中交通的人提供工具，使其无需任何限制、许可证或约束即可完成这些任务。\n* [Cloe](https:\u002F\u002Fgithub.com\u002Feclipse\u002Fcloe) - 通过提供闭环仿真统一接口，赋能自动驾驶软件组件的开发者。\n* [Dynamic_logistics_Warehouse](https:\u002F\u002Fgithub.com\u002Fbelal-ibrahim\u002Fdynamic_logistics_warehouse) - Gazebo中仓库动态环境的仿真。\n* [OpenCDA](https:\u002F\u002Fgithub.com\u002Fucla-mobility\u002FOpenCDA) - 一个基于CARLA+SUMO的通用框架，用于原型化全栈协同驾驶自动化应用。\n\n## 电子与机械\n* [HRIM](https:\u002F\u002Fgithub.com\u002FAcutronicRobotics\u002FHRIM) - 一种用于机器人硬件的信息模型。\n* [URDF](https:\u002F\u002Fgithub.com\u002Fros\u002Furdf) - 统一机器人描述格式（URDF）解析代码的仓库。\n* [phobos](https:\u002F\u002Fgithub.com\u002Fdfki-ric\u002Fphobos) - Blender 的一个插件，允许在所见即所得的环境中创建 URDF、SDF 和 SMURF 机器人模型。\n* [urdf-viz](https:\u002F\u002Fgithub.com\u002FOTL\u002Furdf-viz) - 可视化 URDF\u002FXACRO 文件，URDF 查看器支持 Windows\u002FmacOS\u002FLinux。\n* [solidworks_urdf_exporter](https:\u002F\u002Fgithub.com\u002Fros\u002Fsolidworks_urdf_exporter) - SolidWorks 到 URDF 的导出工具。\n* [FreeCAD](https:\u002F\u002Fgithub.com\u002FFreeCAD\u002FFreeCAD) - 您自己的 3D 参数化建模软件。\n* [kicad](http:\u002F\u002Fwww.kicad.org\u002F) - 跨平台且开源的电子设计自动化套件。\n* [PcbDraw](https:\u002F\u002Fgithub.com\u002Fyaqwsx\u002FPcbDraw) - 将您的 KiCAD 电路板转换为适合引脚图的美观 2D 图纸。\n* [kicad-3rd-party-tools](https:\u002F\u002Fgithub.com\u002Fxesscorp\u002Fkicad-3rd-party-tools) - 其他人开发的用于增强 KiCad PCB EDA 套件功能的工具。\n* [PandaPower](http:\u002F\u002Fwww.pandapower.org) - 一款易于使用、高度自动化的开源电力系统建模、分析和优化工具。\n* [LibrePCB](https:\u002F\u002Fgithub.com\u002FLibrePCB\u002FLibrePCB) - 一款强大、创新且直观的 EDA 工具，适合所有人使用。\n* [openscad](https:\u002F\u002Fgithub.com\u002Fopenscad\u002Fopenscad) - 一款用于创建实体 3D CAD 模型的软件。\n* [ngspice](http:\u002F\u002Fngspice.sourceforge.net\u002F) - 一款用于电气和电子电路的开源 SPICE 仿真器。\n* [GNSS-SDR](https:\u002F\u002Fgithub.com\u002Fgnss-sdr\u002Fgnss-sdr) - GNSS-SDR 提供了与多种射频前端及原始采样文件格式的接口，并以标准格式生成处理结果。\n* [riscv](https:\u002F\u002Friscv.org) - 自由开放的 RISC 指令集架构。\n* [urdfpy](https:\u002F\u002Fgithub.com\u002Fmmatl\u002Furdfpy) - 一个简单易用的库，用于加载、操作、保存和可视化 URDF 文件。\n* [FMPy](https:\u002F\u002Fgithub.com\u002FCATIA-Systems\u002FFMPy) - 在 Python 中模拟功能模型单元（FMU）。\n* [FMIKit-Simulink](https:\u002F\u002Fgithub.com\u002FCATIA-Systems\u002FFMIKit-Simulink) - 使用 Simulink 导入和导出功能模型单元。\n* [oemof-solph](https:\u002F\u002Fgithub.com\u002Foemof\u002Foemof-solph) - 一个模块化的开源框架，用于建模能源供应系统。\n* [NASA-3D-Resources](https:\u002F\u002Fgithub.com\u002Fnasa\u002FNASA-3D-Resources) - 这里收录了来自 NASA 内部不断增长的 3D 模型、纹理和图像资源。\n* [SUAVE](https:\u002F\u002Fgithub.com\u002Fsuavecode\u002FSUAVE) - 飞机设计工具箱。\n* [opem](https:\u002F\u002Fgithub.com\u002FECSIM\u002Fopem) - 开源 PEMFC 仿真工具（OPEM）是一款用于评估质子交换膜燃料电池性能的建模工具。\n* [pvlib-python](https:\u002F\u002Fgithub.com\u002Fpvlib\u002Fpvlib-python) - 一个社区支持的工具，提供一系列函数和类，用于模拟光伏能源系统的性能。\n* [WireViz](https:\u002F\u002Fgithub.com\u002Fformatc1702\u002FWireViz) - 一款用于轻松记录电缆、线束和连接器引脚分配的工具。\n* [Horizon](https:\u002F\u002Fgithub.com\u002Fhorizon-eda\u002Fhorizon) - EDA 是一套电子设计自动化软件，支持印刷电路板设计的端到端集成工作流，包括元器件管理和原理图输入。\n* [tigl](https:\u002F\u002Fgithub.com\u002FDLR-SC\u002Ftigl) - TiGL 几何库可用于计算和处理存储在 CPACS 文件中的飞机几何形状。\n* [foxBMS](https:\u002F\u002Fgithub.com\u002FfoxBMS\u002Ffoxbms) - 一个免费、开放且灵活的电池管理系统开发环境。\n* [cadCAD](https:\u002F\u002Fgithub.com\u002FcadCAD-org\u002FcadCAD) - 一个 Python 包，通过仿真辅助复杂系统的设计、测试和验证过程，支持蒙特卡洛方法、A\u002FB 测试和参数扫描。\n* [OpenMDAO](https:\u002F\u002Fgithub.com\u002FOpenMDAO\u002FOpenMDAO) - 一个用于高效多学科优化的开源框架。\n* [ODrive](https:\u002F\u002Fgithub.com\u002Fmadcowswe\u002FODrive) - 目标是使廉价无刷电机能够在高性能机器人项目中得到应用。\n* [OpenTirePython](https:\u002F\u002Fgithub.com\u002FOpenTire\u002FOpenTirePython) - 一个开源的数学轮胎建模库。\n* [Inkscape Ray Optics](https:\u002F\u002Fgithub.com\u002FdamienBloch\u002Finkscape-raytracing) - Inkscape 的一个扩展，可更方便地绘制光学示意图。\n* [OpenAeroStruct](https:\u002F\u002Fgithub.com\u002Fmdolab\u002FOpenAeroStruct) - 一款轻量级工具，利用 OpenMDAO 进行气动结构优化。\n\n## 传感器处理\n\n### 标定与变换\n* [tf2](http:\u002F\u002Fwiki.ros.org\u002Ftf2) - 变换库，允许用户随时间跟踪多个坐标系。\n* [TriP](https:\u002F\u002Fgithub.com\u002FTriPed-Robot\u002FTriP) - 用于串联机器人、并联机器人以及两者的混合型机器人的逆运动学库。\n* [lidar_align](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Flidar_align) - 一种简单的方法，用于确定3D激光雷达与6自由度位姿传感器之间的外参标定。\n* [kalibr](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fkalibr) - Kalibr 视觉-惯性标定工具箱。\n* [Calibnet](https:\u002F\u002Fgithub.com\u002Fepiception\u002FCalibNet) - 基于3D空间变换网络的自监督外参标定方法。\n* [lidar_camera_calibration](https:\u002F\u002Fgithub.com\u002Fankitdhall\u002Flidar_camera_calibration) - 一个ROS软件包，用于计算激光雷达与相机之间的刚体变换。\n* [ILCC](https:\u002F\u002Fgithub.com\u002Fmfxox\u002FILCC) - 基于反射强度辅助的3D激光雷达自动精确外参标定方法。\n* [easy_handeye](https:\u002F\u002Fgithub.com\u002FIFL-CAMP\u002Feasy_handeye) - 一个简单直接的ROS库，用于手眼标定。\n* [imu_utils](https:\u002F\u002Fgithub.com\u002Fgaowenliang\u002Fimu_utils) - 一个用于分析IMU性能的ROS工具包。\n* [kalibr_allan](https:\u002F\u002Fgithub.com\u002Frpng\u002Fkalibr_allan) - 用于Kalibr和惯性卡尔曼滤波器的IMU Allan方差图。\n* [pyquaternion](https:\u002F\u002Fgithub.com\u002FKieranWynn\u002Fpyquaternion) - 一个功能齐全的Python模块，用于表示和使用四元数。\n* [robot_calibration](https:\u002F\u002Fgithub.com\u002Fmikeferguson\u002Frobot_calibration\u002F) - 该软件包提供对机器人多项参数的标定，例如：3D相机内参、外参、关节角度偏移以及机器人基座偏移。\n* [multi_sensor_calibration](https:\u002F\u002Fgithub.com\u002Ftudelft-iv\u002Fmulti_sensor_calibration\u002F) - 包含用于标定由激光雷达、雷达和相机组成的传感器系统的工具。\n* [LiDARTag](https:\u002F\u002Fgithub.com\u002FUMich-BipedLab\u002FLiDARTag) - 一种基于点云激光雷达数据的实时基准标记。\n* [multicam_calibration](https:\u002F\u002Fgithub.com\u002FKumarRobotics\u002Fmulticam_calibration) - 相机的内外参标定。\n* [ikpy](https:\u002F\u002Fgithub.com\u002FPhylliade\u002Fikpy) - 一个以性能和模块化为目标的逆运动学库。\n* [livox_camera_lidar_calibration](https:\u002F\u002Fgithub.com\u002FLivox-SDK\u002Flivox_camera_lidar_calibration) - 用于标定Livox激光雷达与相机之间的外参。\n* [lidar_camera_calibration](https:\u002F\u002Fgithub.com\u002Fheethesh\u002Flidar_camera_calibration) - 使用ROS、OpenCV和PCL进行相机与激光雷达的标定。\n* [e2calib](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Fe2calib) - 包含用于从事件数据重建视频以进行标定的代码。\n\n\n### 感知流水线\n* [SARosPerceptionKitti](https:\u002F\u002Fgithub.com\u002Fappinho\u002FSARosPerceptionKitti) - 用于KITTI视觉基准测试套件中感知（传感器处理、检测、跟踪和评估）的ROS软件包。\n* [multiple-object-tracking-lidar](https:\u002F\u002Fgithub.com\u002Fpraveen-palanisamy\u002Fmultiple-object-tracking-lidar) - 使用LIDAR扫描或点云检测、跟踪并分类多个目标的C++实现。\n* [cadrl_ros](https:\u002F\u002Fgithub.com\u002Fmfe7\u002Fcadrl_ros) - 用于通过深度强化学习训练的地面机器人进行动态避障的ROS软件包。\n* [AugmentedAutoencoder](https:\u002F\u002Fgithub.com\u002FDLR-RM\u002FAugmentedAutoencoder) - 基于RGB图像的目标检测和6D位姿估计流水线。\n* [jsk_recognition](https:\u002F\u002Fgithub.com\u002Fjsk-ros-pkg\u002Fjsk_recognition) - JSK实验室使用的感知相关软件包集合。\n* [GibsonEnv](https:\u002F\u002Fgithub.com\u002FStanfordVL\u002FGibsonEnv) - Gibson环境：面向具身智能体的真实世界感知。\n* [morefusion](https:\u002F\u002Fgithub.com\u002Fwkentaro\u002Fmorefusion) - 基于体积融合的多目标推理6D位姿估计算法。\n* [se(3)-TrackNet](https:\u002F\u002Fgithub.com\u002Fwenbowen123\u002Firos20-6d-pose-tracking) - 当物体的CAD模型可用时，用于动态目标6D位姿跟踪的软件包。\n\n### 机器学习\n* [DLIB](https:\u002F\u002Fgithub.com\u002Fdavisking\u002Fdlib) - 一个用于在 C++ 中构建实际机器学习和数据分析应用的工具包。\n* [fastai](https:\u002F\u002Fgithub.com\u002Ffastai\u002Ffastai) - fastai 库通过现代最佳实践简化了快速且准确的神经网络训练。\n* [tpot](https:\u002F\u002Fgithub.com\u002FEpistasisLab\u002Ftpot) - 一个使用遗传编程优化机器学习流水线的 Python 自动化机器学习工具。\n* [deap](https:\u002F\u002Fgithub.com\u002FDEAP\u002Fdeap) - Python 中的分布式进化算法。\n* [gym](https:\u002F\u002Fgithub.com\u002Fopenai\u002Fgym) - 用于开发和比较强化学习算法的工具包。\n* [tensorflow_ros_cpp](https:\u002F\u002Fgithub.com\u002Ftradr-project\u002Ftensorflow_ros_cpp) - 一个 ROS 包，允许在 C++ 中进行 TensorFlow 推理，而无需自行编译 TensorFlow。\n* [Tensorflow Federated](https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Ffederated) - TensorFlow Federated (TFF) 是一个用于去中心化数据上进行机器学习及其他计算的开源框架。\n* [finn](https:\u002F\u002Fgithub.com\u002FXilinx\u002Ffinn) - 在 FPGA 上实现快速、可扩展的量化神经网络推理。\n* [neuropod](https:\u002F\u002Fgithub.com\u002Fuber\u002Fneuropod) - Neuropod 是一个库，提供统一的接口，用于在 C++ 和 Python 中运行来自多个框架的深度学习模型。\n* [leela-zero](https:\u002F\u002Fgithub.com\u002Fleela-zero\u002Fleela-zero) - 这是对 Alpha Go Zero 论文《无需人类知识即可掌握围棋》中描述系统的相当忠实的重新实现。\n* [Trax](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Ftrax) - 一个专注于序列模型和强化学习的深度学习库。\n* [mlflow](https:\u002F\u002Fgithub.com\u002Fmlflow\u002Fmlflow) - 一个用于简化机器学习开发的平台，包括实验跟踪、将代码打包为可复现的运行以及共享和部署模型。\n* [Netron](https:\u002F\u002Fgithub.com\u002Flutzroeder\u002FNetron) - 神经网络、深度学习和机器学习模型的可视化工具。\n* [MNN](https:\u002F\u002Fgithub.com\u002Falibaba\u002FMNN) - 由阿里巴巴的关键业务场景实战检验过的超高速轻量级深度学习框架。\n* [Tensorforce](https:\u002F\u002Fgithub.com\u002Ftensorforce\u002Ftensorforce) - 一个开源的深度强化学习框架，强调模块化的灵活库设计和面向研究与实践的简单易用性。\n* [Dopamine](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fdopamine) - 一个用于快速原型化强化学习算法的研究框架。\n* [catalyst](https:\u002F\u002Fgithub.com\u002Fcatalyst-team\u002Fcatalyst) - 该框架专注于可重复性、快速实验以及代码和想法的复用。\n* [ray](https:\u002F\u002Fgithub.com\u002Fray-project\u002Fray) - 一个用于构建和运行分布式应用的快速简便框架。\n* [tf-agents](https:\u002F\u002Fgithub.com\u002Ftensorflow\u002Fagents) - 一个可靠、可扩展且易于使用的 TensorFlow 库，适用于上下文多臂老虎机和强化学习。\n* [ReAgent](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002FReAgent) - Facebook 开发并使用的开源端到端应用强化学习（RL）平台。\n* [Awesome-Mobile-Machine-Learning](https:\u002F\u002Fgithub.com\u002Ffritzlabs\u002FAwesome-Mobile-Machine-Learning) - 针对 iOS、Android 和边缘设备的精选移动机器学习资源列表。\n* [cnn-explainer](https:\u002F\u002Fgithub.com\u002Fpoloclub\u002Fcnn-explainer) - 通过交互式可视化学习卷积神经网络。\n* [modelzoo](https:\u002F\u002Fgithub.com\u002Fautowarefoundation\u002Fmodelzoo) - 用于自动驾驶应用的机器学习模型集合。\n* [nnstreamer-ros](https:\u002F\u002Fgithub.com\u002Fnnstreamer\u002Fnnstreamer-ros) - 一组 Gstreamer 插件和 ROS 示例，使 Gstreamer 开发人员能够轻松高效地采用神经网络模型，同时让神经网络开发者也能轻松高效地管理神经网络流水线及其滤波器。\n\n\n### 并行处理\n* [dask](https:\u002F\u002Fgithub.com\u002Fdask\u002Fdask) - 基于任务调度的 Python 并行计算。\n* [cupy](https:\u002F\u002Fgithub.com\u002Fcupy\u002Fcupy) - 使用 CUDA 加速的类似 NumPy 的 API。\n* [Thrust](https:\u002F\u002Fgithub.com\u002Fthrust\u002Fthrust) - 一个类似于 C++ 标准库的并行编程库。\n* [ArrayFire](https:\u002F\u002Fgithub.com\u002Farrayfire\u002Farrayfire) - 一个通用 GPU 库。\n* [OpenMP](https:\u002F\u002Fwww.openmp.org\u002F) - 一个支持多平台共享内存并行编程的应用程序接口，适用于 C、C++ 和 Fortran。\n* [VexCL](https:\u002F\u002Fgithub.com\u002Fddemidov\u002Fvexcl) - VexCL 是一个用于 OpenCL\u002FCUDA\u002FOpenMP 的 C++ 向量表达式模板库。\n* [PYNQ](https:\u002F\u002Fgithub.com\u002FXilinx\u002FPYNQ) - Xilinx 的一个开源项目，使使用 Zynq 全可编程片上系统设计嵌入式系统变得更加容易。\n* [numba](https:\u002F\u002Fgithub.com\u002Fnumba\u002Fnumba) - 使用 LLVM 的 NumPy 感知动态 Python 编译器。\n* [TensorRT](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FTensorRT) - 一个用于 NVIDIA GPU 和深度学习加速器上的高性能推理的 C++ 库。\n* [libcudacxx](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Flibcudacxx) - 提供一种异构的 C++ 标准库实现，可在 CPU 和 GPU 代码中以及两者之间使用。\n\n### 图像处理\n* [CV-pretrained-model](https:\u002F\u002Fgithub.com\u002Fbalavenkatesh3322\u002FCV-pretrained-model) - 计算机视觉预训练模型集合。\n* [image_pipeline](https:\u002F\u002Fgithub.com\u002Fros-perception\u002Fimage_pipeline) - 弥补了从相机驱动获取原始图像到更高层次视觉处理之间的空白。\n* [gstreamer](https:\u002F\u002Fgstreamer.freedesktop.org\u002F) - 基于管道的多媒体框架，可将各种媒体处理系统连接起来，完成复杂的流程。\n* [ros2_openvino_toolkit](https:\u002F\u002Fgithub.com\u002Fintel\u002Fros2_openvino_toolkit) - 提供经过ROS适配的神经网络运行时框架，用于快速部署视觉推理应用和解决方案。\n* [vision_visp](https:\u002F\u002Fgithub.com\u002Flagadic\u002Fvision_visp) - 将ViSP视觉伺服库提供的ViSP运动边缘跟踪器封装为ROS软件包。\n* [apriltag_ros](https:\u002F\u002Fgithub.com\u002FAprilRobotics\u002Fapriltag_ros) - AprilTag 3视觉标记检测器的ROS封装。\n* [deep_object_pose](https:\u002F\u002Fgithub.com\u002FNVlabs\u002FDeep_Object_Pose) - 深度对象姿态估计。\n* [DetectAndTrack](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002FDetectAndTrack) - 检测与跟踪：高效姿态估计。\n* [SfMLearner](https:\u002F\u002Fgithub.com\u002Ftinghuiz\u002FSfMLearner) - 用于深度和自运动估计的无监督学习框架。\n* [imgaug](https:\u002F\u002Fgithub.com\u002Faleju\u002Fimgaug) - 用于机器学习实验的图像增强工具。\n* [vision_opencv](https:\u002F\u002Fgithub.com\u002Fros-perception\u002Fvision_opencv) - 用于将ROS与OpenCV（实时计算机视觉编程函数库）对接的软件包。\n* [darknet_ros](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fdarknet_ros) - YOLO ROS：面向ROS的实时目标检测。\n* [ros_ncnn](https:\u002F\u002Fgithub.com\u002Fnilseuropa\u002Fros_ncnn) - 在NCNN推理引擎上运行YOLACT \u002F YOLO *(以及其他模型)* 的ROS实现。\n* [tf-pose-estimation](https:\u002F\u002Fgithub.com\u002Fildoonet\u002Ftf-pose-estimation) - 使用TensorFlow和自定义架构实现的深度姿态估计，以支持快速推理。\n* [find-object](https:\u002F\u002Fgithub.com\u002Fintrolab\u002Ffind-object) - 简单的Qt界面，用于尝试OpenCV中SIFT、SURF、FAST、BRIEF等特征检测器和描述子的实现。\n* [yolact](https:\u002F\u002Fgithub.com\u002Fdbolya\u002Fyolact) - 一种简单、全卷积的实时实例分割模型。\n* [Kimera-Semantics](https:\u002F\u002Fgithub.com\u002FMIT-SPARK\u002FKimera-Semantics) - 基于2D数据的实时3D语义重建。\n* [detectron2](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fdetectron2) - 新一代目标检测与分割研究平台。\n* [OpenVX](https:\u002F\u002Fwww.khronos.org\u002Fopenvx\u002F) - 实现性能与功耗优化的计算机视觉处理，尤其适用于嵌入式和实时应用场景。\n* [3d-vehicle-tracking](https:\u002F\u002Fgithub.com\u002Fucbdrive\u002F3d-vehicle-tracking) - 联合单目3D车辆检测与跟踪的官方实现。\n* [pysot](https:\u002F\u002Fgithub.com\u002FSTVIR\u002Fpysot) - PySOT的目标是为视觉跟踪研究提供高质量、高性能的代码库。\n* [semantic_slam](https:\u002F\u002Fgithub.com\u002Ffloatlazer\u002Fsemantic_slam) - 使用手持RGB-D相机在ROS中实现的实时语义SLAM。\n* [kitti_scan_unfolding](https:\u002F\u002Fgithub.com\u002Fltriess\u002Fkitti_scan_unfolding) - 我们在论文《基于扫描的LiDAR点云语义分割：一项实验研究》中提出了KITTI扫描展开方法。\n* [packnet-sfm](https:\u002F\u002Fgithub.com\u002FTRI-ML\u002Fpacknet-sfm) - 丰田研究院（TRI）机器学习团队发明的自监督单目深度估计方法的PyTorch官方实现。\n* [AB3DMOT](https:\u002F\u002Fgithub.com\u002Fxinshuoweng\u002FAB3DMOT) - 本工作提出了一种简单但精确的实时3D多目标跟踪基线系统。\n* [monoloco](https:\u002F\u002Fgithub.com\u002Fvita-epfl\u002Fmonoloco) - “MonoLoco：单目行人3D定位与不确定性估计”的PyTorch官方实现。\n* [Poly-YOLO](https:\u002F\u002Fgitlab.com\u002Firafm-ai\u002Fpoly-yolo) - 基于YOLOv3的原始思想构建，去除了其两个弱点：大量重写的标签和锚点分布效率低下。\n* [satellite-image-deep-learning](https:\u002F\u002Fgithub.com\u002Frobmarkcole\u002Fsatellite-image-deep-learning) - 面向卫星及航空影像的深度学习资源。\n* [robosat](https:\u002F\u002Fgithub.com\u002Fmapbox\u002Frobosat) - 面向航空和卫星影像的语义分割。\n* [big_transfer](https:\u002F\u002Fgithub.com\u002Fgoogle-research\u002Fbig_transfer) - 由谷歌研究院创建的通用视觉表征学习模型。\n* [LEDNet](https:\u002F\u002Fgithub.com\u002Fxiaoyufenfei\u002FLEDNet) - 用于实时语义分割的轻量级编码器-解码器网络。\n* [TorchSeg](https:\u002F\u002Fgithub.com\u002Fycszen\u002FTorchSeg) - 该项目旨在使用PyTorch为语义分割模型提供快速、模块化的参考实现。\n* [simpledet](https:\u002F\u002Fgithub.com\u002Ftusimple\u002Fsimpledet) - 一个简单且多功能的对象检测与实例识别框架。\n* [meshroom](https:\u002F\u002Fgithub.com\u002Falicevision\u002Fmeshroom) - Meshroom是一款基于AliceVision摄影测量计算机视觉框架的免费开源3D重建软件。\n* [EasyOCR](https:\u002F\u002Fgithub.com\u002FJaidedAI\u002FEasyOCR) - 即用型光学字符识别（OCR），支持包括中文、日文、韩文和泰文在内的40多种语言。\n* [pytracking](https:\u002F\u002Fgithub.com\u002Fvisionml\u002Fpytracking) - 基于PyTorch的通用Python框架，用于视觉目标跟踪和视频目标分割。\n* [ros_deep_learning](https:\u002F\u002Fgithub.com\u002Fdusty-nv\u002Fros_deep_learning) - 面向ROS的深度学习推理节点，支持NVIDIA Jetson TX1\u002FTX2\u002FXavier及TensorRT。\n* [hyperpose](https:\u002F\u002Fgithub.com\u002Ftensorlayer\u002Fhyperpose) - HyperPose：实时人体姿态估计的灵活库。\n* [fawkes](https:\u002F\u002Fgithub.com\u002FShawn-Shan\u002Ffawkes) - 抵御人脸识别系统的隐私保护工具。\n* [anonymizer](https:\u002F\u002Fgithub.com\u002Funderstand-ai\u002Fanonymizer) - 用于模糊人脸和车牌的匿名化工具。\n* [opendatacam](https:\u002F\u002Fgithub.com\u002Fopendatacam\u002Fopendatacam) - 只保存调查得到的元数据，特别是物体移动路径或特定点处计数的物体数量。\n* [Cam2BEV](https:\u002F\u002Fgithub.com\u002Fika-rwth-aachen\u002FCam2BEV) - 给定多辆汽车搭载的摄像头图像，计算语义分割后的鸟瞰图（BEV）的TensorFlow实现。\n* [flownet2-pytorch](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fflownet2-pytorch) - FlowNet 2.0的PyTorch实现：基于深度网络的光流估计演进。\n* [Simd](https:\u002F\u002Fgithub.com\u002Fermig1979\u002FSimd) - C++图像处理与机器学习库，支持SIMD指令集：SSE、SSE2、SSE3、SSSE3、SSE4.1、SSE4.2、AVX、AVX2、AVX-512、VMX(Altivec)和VSX(Power7)，以及ARM平台上的NEON。\n* [AliceVision](https:\u002F\u002Fgithub.com\u002Falicevision\u002FAliceVision) - 一款摄影测量计算机视觉框架，提供3D重建和相机跟踪算法。\n* [satpy](https:\u002F\u002Fgithub.com\u002Fpytroll\u002Fsatpy) - 用于读取和处理气象遥感数据，并将其写入各种图像和数据文件格式的Python库。\n* [eo-learn](https:\u002F\u002Fgithub.com\u002Fsentinel-hub\u002Feo-learn) - 一系列开源Python软件包，旨在无缝访问和处理由任何卫星星座获取的时空图像序列，实现及时、自动化的操作。\n* [libvips](https:\u002F\u002Fgithub.com\u002Flibvips\u002Flibvips) - 一款快速且内存占用低的图像处理库。\n\n### 雷达处理\n* [pyroSAR](https:\u002F\u002Fgithub.com\u002Fjohntruckenbrodt\u002FpyroSAR) - 用于大规模合成孔径雷达卫星数据处理的框架。\n* [CameraRadarFusionNet](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002FCameraRadarFusionNet) - 慕尼黑工业大学Roborace团队软件栈 - 路径跟踪控制、速度控制、曲率控制及状态估计。\n\n### 激光雷达与点云处理\n* [cilantro](https:\u002F\u002Fgithub.com\u002Fkzampog\u002Fcilantro) - 一个轻量级的C++库，用于处理点云数据。\n* [open3d](https:\u002F\u002Fgithub.com\u002Fintel-isl\u002FOpen3D) - Open3D：现代的三维数据处理库。\n* [SqueezeSeg](https:\u002F\u002Fgithub.com\u002FBichenWuUCB\u002FSqueezeSeg) - SqueezeSeg的实现，基于卷积神经网络的激光雷达点云分割方法。\n* [point_cloud_io](https:\u002F\u002Fgithub.com\u002FANYbotics\u002Fpoint_cloud_io) - ROS节点，用于从文件（如ply、vtk）中读取和写入点云。\n* [python-pcl](https:\u002F\u002Fgithub.com\u002Fstrawlab\u002Fpython-pcl) - 点云库的Python绑定。\n* [libpointmatcher](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Flibpointmatcher) - 用于机器人2D\u002F3D建图的“迭代最近点”库。\n* [depth_clustering](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fdepth_clustering) - 使用Velodyne传感器生成的点云的快速且鲁棒的聚类算法。\n* [lidar-bonnetal](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Flidar-bonnetal) - 面向自动驾驶的激光雷达点云语义与实例分割。\n* [CSF](https:\u002F\u002Fgithub.com\u002Fjianboqi\u002FCSF) - 基于布料模拟的激光雷达点云地面滤波\u002F分割（裸地提取）方法。\n* [robot_body_filter](https:\u002F\u002Fgithub.com\u002Fpeci1\u002Frobot_body_filter) - 一个高度可配置的LaserScan\u002FPointCloud2滤波器，允许动态地从测量数据中移除机器人自身的三维模型。\n* [grid_map](https:\u002F\u002Fgithub.com\u002FANYbotics\u002Fgrid_map) - 通用的网格地图库，用于移动机器人建图。\n* [elevation_mapping](https:\u002F\u002Fgithub.com\u002FANYbotics\u002Felevation_mapping) - 面向崎岖地形导航的以机器人为中心的高程映射。\n* [rangenet_lib](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Frangenet_lib) - 包含关于RangeNet++推理如何与TensorRT及C++接口协同工作的简单使用说明。\n* [pointcloud_to_laserscan](https:\u002F\u002Fgithub.com\u002Fros-perception\u002Fpointcloud_to_laserscan) - 将三维点云转换为二维激光扫描。\n* [octomap](https:\u002F\u002Fgithub.com\u002FOctoMap\u002Foctomap) - 基于八叉树的高效概率性三维建图框架。\n* [pptk](https:\u002F\u002Fgithub.com\u002Fheremaps\u002Fpptk) - 来自HEREMaps的点处理工具包。\n* [gpu-voxels](https:\u002F\u002Fwww.gpu-voxels.org\u002F) - GPU-Voxels是一个基于CUDA的库，能够在各种类型的3D传感器采集的实时点云与动画3D模型之间实现高分辨率的体积碰撞检测。\n* [spatio_temporal_voxel_layer](https:\u002F\u002Fgithub.com\u002FSteveMacenski\u002Fspatio_temporal_voxel_layer) - 一种利用现代3D图形技术的新体素层，用于现代化导航环境表示。\n* [LAStools](https:\u002F\u002Fgithub.com\u002FLAStools\u002FLAStools) - 备受赞誉的高效激光雷达处理软件。\n* [PCDet](https:\u002F\u002Fgithub.com\u002Fsshaoshuai\u002FPCDet) - 一个基于PyTorch的通用代码库，用于从点云中进行三维目标检测。\n* [PDAL](https:\u002F\u002Fgithub.com\u002FPDAL\u002FPDAL) - 一个用于转换和操作点云数据的C++ BSD库。\n* [PotreeConverter](https:\u002F\u002Fgithub.com\u002Fpotree\u002FPotreeConverter) - 从las、laz、二进制ply、xyz或ptx文件构建potree八叉树。\n* [fast_gicp](https:\u002F\u002Fgithub.com\u002FSMRT-AIST\u002Ffast_gicp) - 一系列基于GICP的快速点云配准算法。\n* [ndt_omp](https:\u002F\u002Fgithub.com\u002Fkoide3\u002Fndt_omp) - 多线程且支持SSE指令集的NDT算法。\n* [laser_line_extraction](https:\u002F\u002Fgithub.com\u002Fkam3k\u002Flaser_line_extraction) - 一个ROS包，用于从LaserScan消息中提取线段。\n* [Go-ICP](https:\u002F\u002Fgithub.com\u002Fyangjiaolong\u002FGo-ICP) - Go-ICP算法的实现，用于全局最优的三维点集配准。\n* [PointCNN](https:\u002F\u002Fgithub.com\u002Fyangyanli\u002FPointCNN) - 一个简单通用的框架，用于从点云中学习特征。\n* [segmenters_lib](https:\u002F\u002Fgithub.com\u002FLidarPerception\u002Fsegmenters_lib) - 激光雷达分割库，用于基于分割的目标检测。\n* [MotionNet](https:\u002F\u002Fgithub.com\u002Fpxiangwu\u002FMotionNet) - 基于鸟瞰图的地图，用于自动驾驶中的联合感知与运动预测。\n* [PolarSeg](https:\u002F\u002Fgithub.com\u002Fedwardzhou130\u002FPolarSeg) - 一种改进的网格表示法，用于在线激光雷达点云的语义分割。\n* [traversability_mapping](https:\u002F\u002Fgithub.com\u002FTixiaoShan\u002Ftraversability_mapping) - 接收来自Velodyne VLP-16激光雷达的点云，并实时输出用于自主导航的通行能力地图。\n* [lidar_super_resolution](https:\u002F\u002Fgithub.com\u002FRobustFieldAutonomyLab\u002Flidar_super_resolution) - 基于仿真的地面车辆激光雷达超分辨率技术。\n* [Cupoch](https:\u002F\u002Fgithub.com\u002Fneka-nat\u002Fcupoch) - 一个使用CUDA实现快速三维数据处理和机器人计算的库。\n* [linefit_ground_segmentation](https:\u002F\u002Fgithub.com\u002Florenwel\u002Flinefit_ground_segmentation) - 地面分割算法的实现。\n* [Draco](https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fdraco) - 一个用于压缩和解压缩三维几何网格和点云的库。\n* [Votenet](https:\u002F\u002Fgithub.com\u002Ffacebookresearch\u002Fvotenet) - 基于深度霍夫投票的点云三维目标检测。\n* [lidar_undistortion](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Flidar_undistortion) - 提供基于外部6DoF位姿估计输入的激光雷达运动去畸变功能。\n* [superpoint_graph](https:\u002F\u002Fgithub.com\u002Floicland\u002Fsuperpoint_graph) - 使用超级点图进行大规模点云语义分割。\n* [RandLA-Net](https:\u002F\u002Fgithub.com\u002FQingyongHu\u002FRandLA-Net) - 高效的大规模点云语义分割。\n* [Det3D](https:\u002F\u002Fgithub.com\u002Fpoodarchu\u002FDet3D) - 第一个三维目标检测工具箱，提供了PointPillars、SECOND、PIXOR等多种三维目标检测算法的开箱即用实现。\n* [OverlapNet](https:\u002F\u002Fgithub.com\u002FPRBonn\u002FOverlapNet) - 一种改进的暹罗网络，用于预测由3D激光雷达扫描生成的一对范围图像之间的重叠及相对偏航角。\n* [mp2p_icp](https:\u002F\u002Fgithub.com\u002FMOLAorg\u002Fmp2p_icp) - C++中多基元到基元（MP2P）ICP算法的集合。\n* [OpenPCDet](https:\u002F\u002Fgithub.com\u002Fopen-mmlab\u002FOpenPCDet) - 一个基于激光雷达的三维目标检测工具箱。\n* [torch-points3d](https:\u002F\u002Fgithub.com\u002Fnicolas-chaulet\u002Ftorch-points3d) - 用于在点云上进行深度学习的PyTorch框架。\n* [PolyFit](https:\u002F\u002Fgithub.com\u002FLiangliangNan\u002FPolyFit) - 基于点云的多边形曲面重建。\n* [mmdetection3d](https:\u002F\u002Fgithub.com\u002Fopen-mmlab\u002Fmmdetection3d) - 下一代通用三维目标检测平台。\n* [gpd](https:\u002F\u002Fgithub.com\u002Fatenpas\u002Fgpd) - 以点云作为输入，输出可行抓取姿态估计。\n* [SalsaNext](https:\u002F\u002Fgithub.com\u002FTiagoCortinhal\u002FSalsaNext) - 面向自动驾驶的激光雷达点云不确定性感知语义分割。\n* [Super-Fast-Accurate-3D-Object-Detection](https:\u002F\u002Fgithub.com\u002Fmaudzung\u002FSuper-Fast-Accurate-3D-Object-Detection) - 基于3D激光雷达点云的超快速且精确的三维目标检测（PyTorch实现）。\n* [kaolin](https:\u002F\u002Fgithub.com\u002FNVIDIAGameWorks\u002Fkaolin) - 一个加速3D深度学习研究的PyTorch库。\n* [CamVox](https:\u002F\u002Fgithub.com\u002FISEE-Technology\u002FCamVox) - 一个基于摄像头和Livox激光雷达的低成本SLAM系统。\n* [SA-SSD](https:\u002F\u002Fgithub.com\u002Fskyhehe123\u002FSA-SSD) - 基于结构感知的单阶段点云三维目标检测。\n* [cuda-pcl](https:\u002F\u002Fgithub.com\u002FNVIDIA-AI-IOT\u002Fcuda-pcl) - 利用NVIDIA CUDA加速的PCL库，助力机器人领域的激光雷达应用。\n* [urban_road_filter](https:\u002F\u002Fgithub.com\u002Fjkk-research\u002Furban_road_filter) - 自动驾驶车辆的实时激光雷达城市道路与人行道检测。\n* [Removert](https:\u002F\u002Fgithub.com\u002Firapkaist\u002Fremovert) - 先移除再恢复。通过构建静态地图来实现野外静态地图构建及动态点云移除工具。\n* [KISS-ICP](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fkiss-icp) - 一条几乎无需调参即可在大多数情况下直接使用的激光雷达里程计流程。\n\n## 定位与状态估计\n* [evo](https:\u002F\u002Fgithub.com\u002FMichaelGrupp\u002Fevo) - 用于评估里程计和SLAM的Python工具包。\n* [robot_localization](https:\u002F\u002Fgithub.com\u002Fcra-ros-pkg\u002Frobot_localization) - 非线性状态估计算法节点集合。\n* [fuse](https:\u002F\u002Fgithub.com\u002Flocusrobotics\u002Ffuse) - 用于在机器人上实时进行传感器融合的通用架构。\n* [GeographicLib](https:\u002F\u002Fgithub.com\u002FSciumo\u002FGeographicLib) - 用于地理投影的C++库。\n* [ntripbrowser](https:\u002F\u002Fgithub.com\u002Femlid\u002Fntripbrowser) - 用于浏览NTRIP（通过互联网协议传输RTCM）的Python API。\n* [imu_tools](https:\u002F\u002Fgithub.com\u002Fccny-ros-pkg\u002Fimu_tools) - 与IMU相关的滤波器和可视化工具。\n* [RTKLIB](https:\u002F\u002Fgithub.com\u002Frtklibexplorer\u002FRTKLIB) - 针对单频和双频低成本GPS接收机，尤其是u-blox接收机优化的RTKLIB版本。\n* [gLAB](https:\u002F\u002Fgage.upc.edu\u002FgLAB\u002F) - 能够以厘米级精度对GNSS观测值（伪距和载波相位）进行建模，支持独立GPS定位、PPP、SBAS和DGNSS。\n* [ai-imu-dr](https:\u002F\u002Fgithub.com\u002Fmbrossar\u002Fai-imu-dr) - 包含我们基于IMU的新型高精度轮式车辆航位推算方法的代码。\n* [Kalman-and-Bayesian-Filters-in-Python](https:\u002F\u002Fgithub.com\u002Frlabbe\u002FKalman-and-Bayesian-Filters-in-Python) - 使用Jupyter Notebook的卡尔曼滤波器教程。\n* [mcl_3dl](https:\u002F\u002Fgithub.com\u002Fat-wat\u002Fmcl_3dl) - 一个ROS节点，用于为配备3D激光雷达的移动机器人实现概率性的3D\u002F6自由度定位系统。\n* [se2lam](https:\u002F\u002Fgithub.com\u002Fizhengfan\u002Fse2lam) - 基于里程计和视觉信息融合的地面上车辆SE(2)空间上的定位与建图。\n* [mmWave-localization-learning](https:\u002F\u002Fgithub.com\u002Fgante\u002FmmWave-localization-learning) - 基于毫米波传输的机器学习定位方法，具有高精度和高能效。\n* [dynamic_robot_localization](https:\u002F\u002Fgithub.com\u002Fcarlosmccosta\u002Fdynamic_robot_localization) - 一个ROS软件包，利用PCL实现3DoF和6DoF定位，并可通过OctoMap动态更新地图。\n* [eagleye](https:\u002F\u002Fgithub.com\u002FMapIV\u002Feagleye) - 一款开源的车辆定位软件，结合GNSS和IMU使用。\n* [python-sgp4](https:\u002F\u002Fgithub.com\u002Fbrandon-rhodes\u002Fpython-sgp4) - SGP4卫星位置库的Python版本。\n* [PROJ](https:\u002F\u002Fgithub.com\u002FOSGeo\u002FPROJ) - 地图投影与坐标变换库。\n* [rpg_trajectory_evaluation](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Frpg_trajectory_evaluation) - 实现了视觉（惯性）里程计中常用的轨迹评估方法。\n* [pymap3d](https:\u002F\u002Fgithub.com\u002Fgeospace-code\u002Fpymap3d) - 纯Python（可选Numpy）的地球空间ECEF、ENU、ECI三维坐标转换工具。\n* [libRSF](https:\u002F\u002Fgithub.com\u002FTUC-ProAut\u002FlibRSF) - 用于在线定位的鲁棒传感器融合库。\n\n## 同时定位与建图\n### 激光雷达\n* [KISS-ICP](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fkiss-icp) - 一种激光雷达里程计流程，在大多数情况下无需调整任何参数即可直接运行。\n* [loam_velodyne](https:\u002F\u002Fgithub.com\u002Flaboshinl\u002Floam_velodyne) - 激光里程计与建图（Loam）是一种利用3D激光雷达进行状态估计和建图的实时方法。\n* [lio-mapping](https:\u002F\u002Fgithub.com\u002Fhyye\u002Flio-mapping) - 紧耦合3D激光雷达惯性里程计与建图（LIO-mapping）的实现。\n* [A-LOAM](https:\u002F\u002Fgithub.com\u002FHKUST-Aerial-Robotics\u002FA-LOAM) - LOAM的高级实现。\n* [Fast LOAM](https:\u002F\u002Fgithub.com\u002Fwh200720041\u002Ffloam) - 快速且优化的激光雷达里程计与建图。\n* [LIO_SAM](https:\u002F\u002Fgithub.com\u002FTixiaoShan\u002FLIO-SAM) - 通过平滑与建图实现的紧耦合激光雷达惯性里程计。\n* [cartographer_ros](https:\u002F\u002Fgithub.com\u002Fgooglecartographer\u002Fcartographer_ros) - 提供Cartographer的ROS集成。\n* [loam_livox](https:\u002F\u002Fgithub.com\u002Fhku-mars\u002Floam_livox) - 一款针对Livox激光雷达的鲁棒激光雷达里程计与建图（LOAM）软件包。\n* [StaticMapping](https:\u002F\u002Fgithub.com\u002FEdwardLiuyc\u002FStaticMapping) - 使用激光雷达对静态环境进行建图。\n* [semantic_suma](https:\u002F\u002Fgithub.com\u002FPRBonn\u002Fsemantic_suma\u002F) - 结合Surfel建图和语义分割的语义建图。\n* [slam_toolbox](https:\u002F\u002Fgithub.com\u002FSteveMacenski\u002Fslam_toolbox) - 适用于潜在大规模地图的终身建图与定位的ROS Slam工具箱。\n* [maplab](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fmaplab) - 一个开放的视觉惯性建图框架。\n* [hdl_graph_slam](https:\u002F\u002Fgithub.com\u002Fkoide3\u002Fhdl_graph_slam) - 一个开源的ROS软件包，用于使用3D激光雷达进行实时6DOF SLAM。\n* [interactive_slam](https:\u002F\u002Fgithub.com\u002FSMRT-AIST\u002Finteractive_slam) - 与现有的自动SLAM软件包不同，我们只需最少的人工干预。\n* [LeGO-LOAM](https:\u002F\u002Fgithub.com\u002FRobustFieldAutonomyLab\u002FLeGO-LOAM) - 一种轻量级、地面优化的激光雷达里程计与建图方案，适用于复杂地形。\n* [pyslam](https:\u002F\u002Fgithub.com\u002Fluigifreda\u002Fpyslam) - 包含一个基于单目视觉的Python里程计流程。\n* [Kitware SLAM](https:\u002F\u002Fgitlab.kitware.com\u002Fkeu-computervision\u002Fslam\u002F) - Kitware开发的纯激光雷达视觉SLAM，以及便于使用的ROS和ParaView封装。\n* [horizon_highway_slam](https:\u002F\u002Fgithub.com\u002FLivox-SDK\u002Fhorizon_highway_slam) - 一款鲁棒、低漂移、实时的高速公路SLAM软件包，适用于Livox Horizon激光雷达。\n* [mola](https:\u002F\u002Fgithub.com\u002FMOLAorg\u002Fmola) - 一种模块化的定位与建图系统。\n* [DH3D](https:\u002F\u002Fgithub.com\u002FJuanDuGit\u002FDH3D) - 用于大规模6DOF重定位的深度分层3D描述符。\n* [LaMa](https:\u002F\u002Fgithub.com\u002Firis-ua\u002Firis_lama) - LaMa是一个用于机器人定位与建图的C++11软件库。\n* [Scan Context](https:\u002F\u002Fgithub.com\u002Firapkaist\u002Fscancontext) - 全局激光雷达描述子，用于场景识别和长期定位。\n* [M-LOAM](https:\u002F\u002Fgithub.com\u002Fgogojjh\u002FM-LOAM) - 针对多激光雷达系统，具备在线外参标定功能的鲁棒里程计与建图。\n\n### 视觉\n* [orb_slam_2_ros](https:\u002F\u002Fgithub.com\u002FappliedAI-Initiative\u002Forb_slam_2_ros) - ORB_SLAM2 的 ROS 实现。\n* [orbslam-map-saving-extension](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Forbslam-map-saving-extension) - 该扩展将 ORB 特征的地图保存到磁盘，以便在未来沿相同轨迹运行时作为参考。\n* [dso](https:\u002F\u002Fgithub.com\u002FJakobEngel\u002Fdso\u002F) - 直接稀疏里程计。\n* [viso2](https:\u002F\u002Fgithub.com\u002Fsrv\u002Fviso2) - libviso2 的 ROS 封装，libviso2 是一个用于视觉里程计的库。\n* [xivo](https:\u002F\u002Fgithub.com\u002Fucla-vision\u002Fxivo) - X 惯性辅助视觉里程计。\n* [rovio](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Frovio) - 鲁棒视觉惯性里程计框架。\n* [LSD-SLAM](https:\u002F\u002Fgithub.com\u002Ftum-vision\u002Flsd_slam) - 大规模直接单目 SLAM 是一种实时单目 SLAM。\n* [CubeSLAM 和 ORB SLAM](https:\u002F\u002Fgithub.com\u002Fshichaoy\u002Fcube_slam) - CubeSLAM 和 ORB SLAM 的单目 3D 目标检测与 SLAM 套件。\n* [VINS-Fusion](https:\u002F\u002Fgithub.com\u002FHKUST-Aerial-Robotics\u002FVINS-Fusion) - 一种鲁棒且通用的多传感器视觉惯性状态估计算法。\n* [openvslam](https:\u002F\u002Fgithub.com\u002Fxdspacelab\u002Fopenvslam) - OpenVSLAM：一个多功能的视觉 SLAM 框架。\n* [basalt](https:\u002F\u002Fgitlab.com\u002FVladyslavUsenko\u002Fbasalt) - 基于非线性因子恢复的视觉惯性建图。\n* [Kimera](https:\u002F\u002Fgithub.com\u002FMIT-SPARK\u002FKimera) - 一个用于实时度量语义同时定位与建图的 C++ 库，它使用相机图像和惯性数据构建环境的语义标注 3D 网格。\n* [tagslam](https:\u002F\u002Fgithub.com\u002Fberndpfrommer\u002Ftagslam) - 一个基于 ROS 的包，利用 AprilTag 基准标记进行同时定位与建图。\n* [LARVIO](https:\u002F\u002Fgithub.com\u002FPetWorm\u002FLARVIO) - 一种轻量级、高精度且鲁棒的单目视觉惯性里程计，基于多状态约束卡尔曼滤波器。\n* [fiducials](https:\u002F\u002Fgithub.com\u002FUbiquityRobotics\u002Ffiducials) - 使用基准标记进行同时定位与建图。\n* [open_vins](https:\u002F\u002Fgithub.com\u002Frpng\u002Fopen_vins) - 一个用于视觉惯性导航研究的开源平台。\n* [ORB_SLAM3](https:\u002F\u002Fgithub.com\u002FUZ-SLAMLab\u002FORB_SLAM3) - ORB-SLAM3：一个精确的开源库，适用于视觉、视觉惯性及多地图 SLAM。\n* [Atlas](https:\u002F\u002Fgithub.com\u002Fmagicleap\u002FAtlas) - 从已定位图像中端到端重建 3D 场景。\n* [vilib](https:\u002F\u002Fgithub.com\u002Fuzh-rpg\u002Fvilib) - 该库专注于使用 CUDA 的 VIO 流水线前端。\n* [hloc](https:\u002F\u002Fgithub.com\u002Fcvg\u002FHierarchical-Localization) - 一套模块化的工具箱，用于最先进的 6 自由度视觉定位。它实现了分层定位，利用图像检索和特征匹配，速度快、精度高且可扩展。\n* [ESVO](https:\u002F\u002Fgithub.com\u002FHKUST-Aerial-Robotics\u002FESVO) - 一种新颖的实时立体事件相机视觉里程计流程。\n* [gradslam](https:\u002F\u002Fgithub.com\u002Fgradslam\u002Fgradslam) - 一个面向 PyTorch 的开源可微分稠密 SLAM 库。\n\n\n### 向量地图\n* [OpenDRIVE](http:\u002F\u002Fwww.opendrive.org\u002Findex.html) - 一种用于道路网络逻辑描述的开放文件格式。\n* [MapsModelsImporter](https:\u002F\u002Fgithub.com\u002Feliemichel\u002FMapsModelsImporter) - 一个 Blender 插件，用于从 Google 地图导入模型。\n* [Lanelet2](https:\u002F\u002Fgithub.com\u002Ffzi-forschungszentrum-informatik\u002FLanelet2) - 用于自动驾驶的地图处理框架。\n* [barefoot](https:\u002F\u002Fgithub.com\u002Fbmwcarit\u002Fbarefoot) - 在线和离线地图匹配，既可独立使用，也可在云端运行。\n* [iD](https:\u002F\u002Fgithub.com\u002Fopenstreetmap\u002FiD) - 一款易于使用的 JavaScript 开源地图编辑器。\n* [RapiD](https:\u002F\u002Fgithub.com\u002Ffacebookincubator\u002FRapiD) - Facebook 打造的增强版 iD，结合 AI 进行地图绘制。\n* [segmap](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fsegmap) - 基于 3D 分段的地图表示。\n* [Mapbox](https:\u002F\u002Fgithub.com\u002Fmapbox\u002Fmapbox-gl-js) - 一个用于在网络上创建交互式、可定制向量地图的 JavaScript 库。\n* [osrm-backend](https:\u002F\u002Fgithub.com\u002FProject-OSRM\u002Fosrm-backend) - 开源路由引擎 - C++ 后端。\n* [assuremapingtools](https:\u002F\u002Fgithub.com\u002Fhatem-darweesh\u002Fassuremapingtools) - 一款桌面工具，用于查看、编辑和保存道路网络地图，适用于 Autoware 等自动驾驶平台。\n* [geopandas](https:\u002F\u002Fgithub.com\u002Fgeopandas\u002Fgeopandas) - 一个为 pandas 对象添加地理数据支持的项目。\n* [MapToolbox](https:\u002F\u002Fgithub.com\u002Fautocore-ai\u002FMapToolbox) - 用于在 Unity 中制作 Autoware 向量地图的插件。\n* [imagery-index](https:\u002F\u002Fgithub.com\u002Fideditor\u002Fimagery-index) - 一份对地图绘制有用的航空和卫星影像索引。\n* [mapillary_tools](https:\u002F\u002Fgithub.com\u002Fmapillary\u002Fmapillary_tools) - 一个用于处理和上传图像到 Mapillary 的库。\n* [mapnik](https:\u002F\u002Fgithub.com\u002Fmapnik\u002Fmapnik) - 结合像素级完美的图像输出与闪电般的制图算法，并提供 C++、Python 和 Node.js 接口。\n* [gdal](https:\u002F\u002Fgithub.com\u002FOSGeo\u002Fgdal) - GDAL 是一个开源、采用 X\u002FMIT 许可证的栅格和矢量地理空间数据格式转换库。\n* [grass](https:\u002F\u002Fgithub.com\u002FOSGeo\u002Fgrass) - GRASS GIS - 免费且开源的地理信息系统 (GIS)。\n* [3d-tiles](https:\u002F\u002Fgithub.com\u002FCesiumGS\u002F3d-tiles) - 用于流式传输大规模异构 3D 地理空间数据集的规范。\n* [osmnx](https:\u002F\u002Fgithub.com\u002Fgboeing\u002Fosmnx) - 用于街道网络的 Python 工具。可以从 OpenStreetMap 获取、建模、分析和可视化街道网络及其他空间数据。\n\n## 预测\n* [Awesome-Interaction-aware-Trajectory-Prediction](https:\u002F\u002Fgithub.com\u002Fjiachenli94\u002FAwesome-Interaction-aware-Trajectory-Prediction) - 一系列最先进的轨迹预测研究资料。\n* [sgan](https:\u002F\u002Fgithub.com\u002Fagrimgupta92\u002Fsgan) - 基于生成对抗网络的社会可接受轨迹。\n\n## 行为与决策\n* [Groot](https:\u002F\u002Fgithub.com\u002FBehaviorTree\u002FGroot) - 用于创建行为树的图形化编辑器。兼容 BehaviorTree.CPP。\n* [BehaviorTree.CPP](https:\u002F\u002Fgithub.com\u002FBehaviorTree\u002FBehaviorTree.CPP) - C++ 行为树库。\n* [RAFCON](https:\u002F\u002Fgithub.com\u002FDLR-RM\u002FRAFCON) - 使用层次状态机，支持并发状态执行，用于表示机器人程序。\n* [ROSPlan](https:\u002F\u002Fgithub.com\u002FKCL-Planning\u002FROSPlan) - 适用于 ROS 系统的任务规划通用框架。\n* [ad-rss-lib](https:\u002F\u002Fgithub.com\u002Fintel\u002Fad-rss-lib) - 实现自动驾驶车辆责任敏感安全模型（RSS）的库。\n* [FlexBE](https:\u002F\u002Fflexbe.github.io\u002F) - 基于 ROS 的 smach 的层次状态机图形化编辑器。\n* [sts_bt_library](https:\u002F\u002Fgithub.com\u002FAutonomous-Logistics\u002Fsts_bt_library) - 该库提供使用定义好的树结构（如Fallback、Sequence 或 Parallel 节点）来搭建自定义行为逻辑的功能。\n* [SMACC](https:\u002F\u002Fgithub.com\u002Freelrbtx\u002FSMACC) - 面向实时 ROS（机器人操作系统）应用的事件驱动、异步行为状态机库，采用 C++ 编写。\n* [py_trees_ros](https:\u002F\u002Fgithub.com\u002Fsplintered-reality\u002Fpy_trees_ros) - 扩展 py_trees 以在 ROS 中使用的行为、行为树及实用工具。\n\n## 规划与控制\n* [pacmod](https:\u002F\u002Fgithub.com\u002Fastuff\u002Fpacmod) - 旨在让用户通过PACMod线控系统控制车辆。\n* [mpcc](https:\u002F\u002Fgithub.com\u002Falexliniger\u002FMPCC) - 用于自动驾驶赛车的模型预测轮廓控制器。\n* [rrt](https:\u002F\u002Fgithub.com\u002FRoboJackets\u002Frrt) - C++实现的快速探索随机树算法。\n* [HypridAStarTrailer](https:\u002F\u002Fgithub.com\u002FAtsushiSakai\u002FHybridAStarTrailer) - 基于混合A*算法的拖车卡车路径规划算法。\n* [path_planner](https:\u002F\u002Fgithub.com\u002Fkarlkurzer\u002Fpath_planner) - 用于KTH研究概念车的混合A*路径规划器。\n* [open_street_map](https:\u002F\u002Fgithub.com\u002Fros-geographic-info\u002Fopen_street_map) - 用于处理OpenStreetMap地理信息的ROS软件包。\n* [开源汽车控制](https:\u002F\u002Fgithub.com\u002FPolySync\u002Foscc) - 一套软硬件设计，可实现对现代汽车的计算机控制，从而促进自动驾驶技术的发展。\n* [fastrack](https:\u002F\u002Fgithub.com\u002FHJReachability\u002Ffastrack) - FaSTrack（快速安全跟踪）的ROS实现。\n* [commonroad](https:\u002F\u002Fcommonroad.in.tum.de\u002F) - 道路运动规划的可组合基准测试集。\n* [traffic-editor](https:\u002F\u002Fgithub.com\u002Fosrf\u002Ftraffic-editor) - 用于机器人交通流的图形化编辑器。\n* [steering_functions](https:\u002F\u002Fgithub.com\u002Fhbanzhaf\u002Fsteering_functions) - 包含一个C++库，实现了适用于具有有限转弯半径的类汽车机器人的转向函数。\n* [moveit](https:\u002F\u002Fmoveit.ros.org\u002F) - 易于使用的机器人操作平台，用于开发应用、评估设计及构建集成产品。\n* [flexible-collision-library](https:\u002F\u002Fgithub.com\u002Fflexible-collision-library\u002Ffcl) - 用于在由三角形组成的几何模型对之间执行三种类型的邻近性查询的库。\n* [aikido](https:\u002F\u002Fgithub.com\u002Fpersonalrobotics\u002Faikido) - 用于运动学、动力学和优化的人工智能。\n* [casADi](https:\u002F\u002Fgithub.com\u002Fcasadi\u002Fcasadi) - 一种符号框架，用于数值优化，在稀疏矩阵值计算图上实现前向和反向模式的自动微分。\n* [ACADO工具箱](https:\u002F\u002Fgithub.com\u002Facado\u002Facado) - 用于自动控制和动态优化的软件环境及算法集合。\n* [control-toolbox](https:\u002F\u002Fgithub.com\u002Fethz-adrl\u002Fcontrol-toolbox) - 一个高效的C++库，用于机器人中的控制、估计、优化和运动规划。\n* [CrowdNav](https:\u002F\u002Fgithub.com\u002Fvita-epfl\u002FCrowdNav) - 基于注意力机制的深度强化学习的群体感知型机器人导航。\n* [ompl](https:\u002F\u002Fgithub.com\u002Fompl\u002Fompl) - 包含多种最先进的基于采样的运动规划算法。\n* [openrave](https:\u002F\u002Fgithub.com\u002Frdiankov\u002Fopenrave) - 开放式机器人自动化虚拟环境：用于测试、开发和部署机器人运动规划算法的环境。\n* [teb_local_planner](https:\u002F\u002Fgithub.com\u002Frst-tu-dortmund\u002Fteb_local_planner) - 基于定时弹性带的移动机器人最优轨迹规划器，考虑了独特的拓扑结构。\n* [pinocchio](https:\u002F\u002Fgithub.com\u002Fstack-of-tasks\u002Fpinocchio) - 刚体动力学算法及其解析导数的快速灵活实现。\n* [rmf_core](https:\u002F\u002Fgithub.com\u002Fosrf\u002Frmf_core) - rmf_core软件包提供了机器人中间件框架（RMF）的集中式功能。\n* [OpEn](https:\u002F\u002Fgithub.com\u002Falphaville\u002Foptimization-engine) - 用于下一代机器人和自主系统的快速准确嵌入式优化求解器。\n* [autogenu-jupyter](https:\u002F\u002Fgithub.com\u002Fmayataka\u002Fautogenu-jupyter) - 该项目提供了基于延续\u002FGMRES方法（C\u002FGMRES方法）的非线性模型预测控制（NMPC）求解器，以及NMPC的自动代码生成器。\n* [global_racetrajectory_optimization](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fglobal_racetrajectory_optimization) - 此仓库包含多种生成全局竞速轨迹的方法。\n* [toppra](https:\u002F\u002Fgithub.com\u002Fhungpham2511\u002Ftoppra) - 用于计算受运动学和动力学约束的机器人时间最优路径参数化的库。\n* [tinyspline](https:\u002F\u002Fgithub.com\u002Fmsteinbeck\u002Ftinyspline) - TinySpline是一个小型但功能强大的库，可用于插值、变换和查询任意NURBS、B样条和贝塞尔曲线。\n* [dual quaternions ros](https:\u002F\u002Fgithub.com\u002FAchllle\u002Fdual_quaternions_ros) - 用于双四元数SLERP的ROS Python包。\n* [mb planner](https:\u002F\u002Fgithub.com\u002Funr-arl\u002Fmbplanner_ros) - 用于狭小空间的空中飞行器规划器。曾用于DARPA SubT挑战赛。\n* [ilqr](https:\u002F\u002Fgithub.com\u002Fanassinator\u002Filqr) - 具有自动微分动力学模型的迭代线性二次调节器。\n* [EGO-Planner](https:\u002F\u002Fgithub.com\u002FZJU-FAST-Lab\u002Fego-planner) - 一种轻量级的基于梯度的局部规划器，无需ESDF构建，相比一些最先进的方法显著减少了计算时间。\n* [pykep](https:\u002F\u002Fgithub.com\u002Fesa\u002Fpykep) - 一个科学库，提供行星际轨道设计研究的基本工具。\n* [am_traj](https:\u002F\u002Fgithub.com\u002FZJU-FAST-Lab\u002Fam_traj) - 基于交替最小化的轨迹生成，适用于四旋翼无人机的激进飞行。\n* [GraphBasedLocalTrajectoryPlanner](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002FGraphBasedLocalTrajectoryPlanner) - 曾在Roborace Alpha赛季的真实赛车上使用，并达到了超过200公里\u002F小时的速度。\n* [se2_navigation](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fse2_navigation) - 纯追踪控制器和基于Reeds-Shepp采样的规划器，用于SE(2)空间中的导航。\n* [Ruckig](https:\u002F\u002Fruckig.com) - 即时运动生成。实时。加速度受限。时间最优。\n\n\n## 用户交互\n\n### 图形用户界面\n* [imgui](https:\u002F\u002Fgithub.com\u002Focornut\u002Fimgui) - 旨在实现快速迭代，使程序员能够创建内容创作工具以及可视化和调试工具。\n* [qtpy](https:\u002F\u002Fgithub.com\u002Fspyder-ide\u002Fqtpy) - 提供一个统一的层，用单一代码库支持 PyQt5、PySide2、PyQt4 和 PySide。\n* [mir](https:\u002F\u002Fgithub.com\u002FMirServer\u002Fmir) - Mir 是一套用于构建基于 Wayland 的桌面环境的库。\n* [rqt](https:\u002F\u002Fwiki.ros.org\u002Frqt) - 基于 Qt 的 ROS GUI 开发框架。它由三个部分\u002F元包组成。\n* [cage](https:\u002F\u002Fgithub.com\u002FHjdskes\u002Fcage) - 这是 Cage，一个 Wayland 售货亭模式系统。该系统会运行一个全屏的最大化应用。\n* [chilipie](https:\u002F\u002Fgithub.com\u002Ffuturice\u002Fchilipie-kiosk) - 易于使用的树莓派镜像，可直接启动进入全屏 Chrome 浏览器。\n* [pencil](https:\u002F\u002Fgithub.com\u002Fevolus\u002Fpencil) - 一款人人可用的绘图和 GUI 原型设计工具。\n* [dynamic_reconfigure](https:\u002F\u002Fwiki.ros.org\u002Fdynamic_reconfigure) - dynamic_reconfigure 的重点在于提供一种标准方法，将节点的部分参数暴露给外部重新配置。\n* [ddynamic_reconfigure](https:\u002F\u002Fgithub.com\u002Fpal-robotics\u002Fddynamic_reconfigure) - 允许使用 dynamic_reconfigure 框架修改 ROS 节点的参数，而无需编写 cfg 文件。\n* [elements](https:\u002F\u002Fgithub.com\u002Fcycfi\u002Felements) - 一个轻量级、细粒度、与分辨率无关的模块化 GUI 库。\n* [NanoGUI](https:\u002F\u002Fgithub.com\u002Fwjakob\u002Fnanogui) - 一个极简的跨平台 OpenGL 3.x 或更高版本的小部件库。\n\n\n### 声学用户界面\n* [pyo](https:\u002F\u002Fgithub.com\u002Fbelangeo\u002Fpyo) - 一个用 C 语言编写的 Python 模块，包含用于各种音频信号处理的类。\n* [rhasspy](https:\u002F\u002Fgithub.com\u002Fsynesthesiam\u002Frhasspy) - Rhasspy（发音为 RAH-SPEE）是一个受 Jasper 启发的离线、多语言语音助手工具包，可与 Home Assistant、Hass.io 和 Node-RED 良好兼容。\n* [mycroft-core](https:\u002F\u002Fgithub.com\u002FMycroftAI\u002Fmycroft-core) - Mycroft 是一个可 hack 的开源语音助手。\n* [DDSP](https:\u002F\u002Fgithub.com\u002Fmagenta\u002Fddsp) - 一个包含常见 DSP 函数（如合成器、波形整形器和滤波器）可微分版本的库。\n* [NoiseTorch](https:\u002F\u002Fgithub.com\u002Flawl\u002FNoiseTorch) - 在任何应用中创建一个能够抑制噪声的虚拟麦克风。\n* [DeepSpeech](https:\u002F\u002Fgithub.com\u002Fmozilla\u002FDeepSpeech) - 一个开源的语音转文本引擎，采用基于百度 Deep Speech 研究论文的机器学习技术训练的模型。\n* [waveglow](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fwaveglow) - 一种基于流的语音合成生成网络。\n* [TTS](https:\u002F\u002Fgithub.com\u002Fcoqui-ai\u002FTTS) - 一个经过研究和生产验证的深度学习文本转语音工具包。\n\n\n### 命令行界面\n* [the-art-of-command-line](https:\u002F\u002Fgithub.com\u002Fjlevy\u002Fthe-art-of-command-line) - 一页纸掌握命令行技巧。\n* [cornerman 的 dotfiles](https:\u002F\u002Fgithub.com\u002Fcornerman\u002Fdotfiles) - 功能强大的 zsh 和 vim 配置文件。\n* [dotbot](https:\u002F\u002Fgithub.com\u002Fanishathalye\u002Fdotbot) - 一个用于引导你的 dotfiles 的工具。\n* [prompt-hjem](https:\u002F\u002Fgithub.com\u002Fcornerman\u002Fprompt-hjem) - 一个漂亮的 zsh 提示符。\n* [ag](https:\u002F\u002Fgithub.com\u002Fggreer\u002Fthe_silver_searcher) - 一个类似于 ack 的代码搜索工具，但速度更快。\n* [fzf](https:\u002F\u002Fgithub.com\u002Fjunegunn\u002Ffzf) - 一个命令行模糊查找工具。\n* [pkgtop](https:\u002F\u002Fgithub.com\u002Forhun\u002Fpkgtop) - 专为 GNU\u002FLinux 设计的交互式软件包管理器和资源监视器。\n* [asciimatics](https:\u002F\u002Fgithub.com\u002Fpeterbrittain\u002Fasciimatics) - 一个跨平台包，用于执行类似 curses 的操作，并提供更高级别的 API 和小部件，以创建文本 UI 和 ASCII 艺术动画。\n* [gocui](https:\u002F\u002Fgithub.com\u002Fjroimartin\u002Fgocui) - 一个极简的 Go 包，用于创建控制台用户界面。\n* [TerminalImageViewer](https:\u002F\u002Fgithub.com\u002Fstefanhaustein\u002FTerminalImageViewer) - 一个小型 C++ 程序，使用 RGB ANSI 代码和 Unicode 方块图形字符在（现代）终端上显示图像。\n* [rosshow](https:\u002F\u002Fgithub.com\u002Fdheera\u002Frosshow) - 使用 Unicode\u002FASCII 艺术在终端内可视化 ROS 主题。\n* [python-prompt-toolkit](https:\u002F\u002Fgithub.com\u002Fprompt-toolkit\u002Fpython-prompt-toolkit) - 一个用于在 Python 中构建强大交互式命令行应用程序的库。\n* [guake](https:\u002F\u002Fgithub.com\u002FGuake\u002Fguake) - GNOME 下拉终端。\n* [wemux](https:\u002F\u002Fgithub.com\u002Fzolrath\u002Fwemux) - 多用户 Tmux 轻松搞定。\n* [tmuxp](https:\u002F\u002Fgithub.com\u002Ftmux-python\u002Ftmuxp) - 一个基于 libtmux 构建的会话管理器。\n* [mapscii](https:\u002F\u002Fgithub.com\u002Frastapasta\u002Fmapscii) - 为你的控制台渲染的世界地图。\n* [terminator](https:\u002F\u002Flaunchpad.net\u002Fterminator) - 该项目的目标是开发一款实用的终端布局工具。\n* [bat](https:\u002F\u002Fgithub.com\u002Fsharkdp\u002Fbat) - 一个带翅膀的 cat(1) 克隆版。\n* [fx](https:\u002F\u002Fgithub.com\u002Fantonmedv\u002Ffx) - 命令行工具和终端 JSON 查看器。\n* [tmate](https:\u002F\u002Fgithub.com\u002Ftmate-io\u002Ftmate) - 即时终端共享。\n\n## 数据可视化与任务控制\n* [xdot](https:\u002F\u002Fgithub.com\u002Fjrfonseca\u002Fxdot.py) - 用于Graphviz dot语言编写的图的交互式查看器。\n* [guacamole](https:\u002F\u002Fguacamole.apache.org\u002F) - 无客户端远程桌面网关。支持VNC、RDP和SSH等标准协议。\n* [ros3djs](https:\u002F\u002Fgithub.com\u002FRobotWebTools\u002Fros3djs) - 用于ROS JavaScript库的3D可视化库。\n* [webviz](https:\u002F\u002Fgithub.com\u002Fcruise-automation\u002Fwebviz) - 类似rviz的基于Web的可视化库。\n* [plotly.py](https:\u002F\u002Fgithub.com\u002Fplotly\u002Fplotly.py) - Python的开源交互式绘图库。\n* [PlotJuggler](https:\u002F\u002Fgithub.com\u002Ffacontidavide\u002FPlotJuggler) - 你应得的时间序列可视化工具。\n* [bokeh](https:\u002F\u002Fgithub.com\u002Fbokeh\u002Fbokeh) - 从Python实现的浏览器端交互式数据可视化。\n* [voila](https:\u002F\u002Fgithub.com\u002Fvoila-dashboards\u002Fvoila) - 将Jupyter笔记本转换为独立的Web应用和仪表板。\n* [Pangolin](https:\u002F\u002Fgithub.com\u002Fstevenlovegrove\u002FPangolin) - Pangolin是一个轻量级、可移植的快速开发库，用于管理OpenGL显示\u002F交互以及抽象视频输入。\n* [rqt_bag](http:\u002F\u002Fwiki.ros.org\u002Frqt_bag) - 提供用于显示和回放ROS bag文件的GUI插件。\n* [kepler.gl](https:\u002F\u002Fgithub.com\u002Fkeplergl\u002Fkepler.gl) - Kepler.gl是一款功能强大的开源地理空间分析工具，适用于大规模数据集。\n* [qgis_ros](https:\u002F\u002Fgithub.com\u002Flocusrobotics\u002Fqgis_ros) - 在功能丰富的GIS环境中访问bag文件和实时话题数据。\n* [openmct](https:\u002F\u002Fgithub.com\u002Fnasa\u002Fopenmct) - 基于Web的任务控制框架。\n* [web_video_server](https:\u002F\u002Fgithub.com\u002FRobotWebTools\u002Fweb_video_server) - 以多种格式对ROS图像话题进行HTTP流传输。\n* [RVizWeb](https:\u002F\u002Fgithub.com\u002Fosrf\u002Frvizweb) - 提供了一种便捷的方式，构建并启动具有类似RViz功能的Web应用。\n* [marvros](https:\u002F\u002Fgithub.com\u002Fmavlink\u002Fmavros) - MAVLink到ROS的网关，带有地面控制站代理。\n* [octave](https:\u002F\u002Fwww.gnu.org\u002Fsoftware\u002Foctave\u002F) - 提供一个方便的命令行界面，用于数值求解线性和非线性问题，并使用与Matlab高度兼容的语言进行其他数值实验。\n* [streetscape.gl](https:\u002F\u002Fgithub.com\u002Fuber\u002Fstreetscape.gl) - Streetscape.gl是一个用于以XVIZ协议可视化自动驾驶和机器人数据的工具包。\n* [urdf-loaders](https:\u002F\u002Fgithub.com\u002Fgkjohnson\u002Furdf-loaders) - 适用于Unity和THREE.js的URDF加载器，附带示例ATHLETE URDF文件。\n* [obs-studio](https:\u002F\u002Fgithub.com\u002Fobsproject\u002Fobs-studio) - 用于直播和屏幕录制的免费开源软件。\n* [K3D-tools](https:\u002F\u002Fgithub.com\u002FK3D-tools) - 用于3D可视化的Jupyter笔记本扩展。\n* [PyQtGraph](https:\u002F\u002Fgithub.com\u002Fpyqtgraph\u002Fpyqtgraph) - 面向科学\u002F工程应用的快速数据可视化和GUI工具。\n* [ipygany](https:\u002F\u002Fgithub.com\u002FQuantStack\u002Fipygany) - Jupyter笔记本中的3D科学可视化。\n* [Foxglove Studio](https:\u002F\u002Fgithub.com\u002Ffoxglove\u002Fstudio) - 用于机器人可视化和调试的Web及桌面应用；是webviz的活跃维护分支。\n* [ROS-Mobile](https:\u002F\u002Fgithub.com\u002FROS-Mobile\u002FROS-Mobile-Android) - Android平台上的可视化与控制应用。\n\n\n### 标注\n* [labelbox](https:\u002F\u002Fgithub.com\u002FLabelbox\u002Flabelbox) - 构建和部署人工智能应用最快的数据标注方式。\n* [PixelAnnotationTool](https:\u002F\u002Fgithub.com\u002Fabreheret\u002FPixelAnnotationTool) - 快速标注图像。\n* [LabelImg](https:\u002F\u002Fgithub.com\u002Ftzutalin\u002FlabelImg) - 一款图形化图像标注工具，用于在图像中框选标签对象。\n* [cvat](https:\u002F\u002Fgithub.com\u002Fopencv\u002Fcvat) - 功能强大且高效的计算机视觉标注工具（CVAT）。\n* [point_labeler](https:\u002F\u002Fgithub.com\u002Fjbehley\u002Fpoint_labeler) - 用于单个点云或点云流的标注工具。\n* [label-studio](https:\u002F\u002Fgithub.com\u002Fheartexlabs\u002Flabel-studio) - Label Studio是一款多类型数据标注工具，输出格式标准化。\n* [napari](https:\u002F\u002Fgithub.com\u002Fnapari\u002Fnapari) - 一款快速、交互式的多维图像查看器，专为Python设计。\n* [semantic-segmentation-editor](https:\u002F\u002Fgithub.com\u002FHitachi-Automotive-And-Industry-Lab\u002Fsemantic-segmentation-editor) - 一款基于Web的标注工具，用于创建AI训练数据集（2D和3D）。\n* [3d-bat](https:\u002F\u002Fgithub.com\u002Fwalzimmer\u002F3d-bat) - 用于点云和图像标注的3D边界框标注工具。\n* [labelme](https:\u002F\u002Fgithub.com\u002Fwkentaro\u002Flabelme) - 使用Python进行图像多边形标注（多边形、矩形、圆形、直线、点以及图像级别的标记标注）。\n* [universal-data-tool](https:\u002F\u002Fgithub.com\u002FUniversalDataTool\u002Funiversal-data-tool) - 在简单的Web界面或桌面应用中协作并标注任何类型的数据、图像、文本或文档。\n* [BMW-Labeltool-Lite](https:\u002F\u002Fgithub.com\u002FBMW-InnovationLab\u002FBMW-Labeltool-Lite) - 为您提供易于使用的标注工具，用于最先进的深度学习训练目的。\n* [3d-annotation-tool](https:\u002F\u002Fgithub.com\u002FStrayRobots\u002F3d-annotation-tool) - 一款轻量级工具，可用于为点云添加边界框、矩形、关键点等标注。\n\n\n### 点云\n* [CloudCompare](https:\u002F\u002Fgithub.com\u002FCloudCompare\u002FCloudCompare) - CloudCompare是一款用于处理3D点云（及三角网格）的软件。\n* [Potree](https:\u002F\u002Fgithub.com\u002Fpotree\u002Fpotree) - 用于大型数据集的WebGL点云查看器。\n* [point_cloud_viewer](https:\u002F\u002Fgithub.com\u002Fgooglecartographer\u002Fpoint_cloud_viewer) - 让查看海量点云变得简单便捷。\n* [LidarView](https:\u002F\u002Fgithub.com\u002FKitware\u002FLidarView) - 对来自LiDAR传感器的实时采集3D LiDAR数据进行实时可视化和简便处理。\n* [VeloView](https:\u002F\u002Fgithub.com\u002FKitware\u002FVeloView) - 对来自Velodyne HDL传感器的实时采集3D LiDAR数据进行实时可视化。\n* [entwine](https:\u002F\u002Fgithub.com\u002Fconnormanning\u002Fentwine\u002F) - 一款针对海量点云的数据组织库，旨在处理包含数万亿点的大规模数据集以及桌面规模的点云。\n* [polyscope](https:\u002F\u002Fgithub.com\u002Fnmwsharp\u002Fpolyscope) - 一款C++和Python编写的3D数据查看器，适用于网格和点云等数据。\n* [Pcx](https:\u002F\u002Fgithub.com\u002Fkeijiro\u002FPcx) - Unity平台下的点云导入与渲染工具。\n* [ImmersivePoints](https:\u002F\u002Fgithub.com\u002Frmeertens\u002FImmersivePoints) - 一款面向虚拟现实设备的Web应用，让用户能够以最自然的方式探索3D数据。\n\n### RViz\n* [mapviz](https:\u002F\u002Fgithub.com\u002Fswri-robotics\u002Fmapviz) - 用于2D数据的模块化ROS可视化工具。\n* [rviz_cinematographer](https:\u002F\u002Fgithub.com\u002FAIS-Bonn\u002Frviz_cinematographer) - 易于使用的工具，用于为RViz相机创建和编辑轨迹。\n* [rviz_satellite](https:\u002F\u002Fgithub.com\u002Fgareth-cross\u002Frviz_satellite) - 在RViz中显示互联网卫星影像。\n* [rviz_visual_tools](https:\u002F\u002Fgithub.com\u002FPickNikRobotics\u002Frviz_visual_tools) - 用于在RViz中显示形状和网格的C++ API封装。\n\u003C!--lint ignore double-link-->\n* [xpp](https:\u002F\u002Fgithub.com\u002Fleggedrobotics\u002Fxpp) - 用于足式机器人的运动规划可视化。\n* [rviz stereo](http:\u002F\u002Fwiki.ros.org\u002Frviz\u002FTutorials\u002FRviz%20in%20Stereo) - 3D立体渲染会为每只眼睛显示不同的视图，从而使场景看起来具有深度。\n* [jsk_visualization](https:\u002F\u002Fgithub.com\u002Fjsk-ros-pkg\u002Fjsk_visualization) - Jsk可视化ROS包，适用于RViz和rqt。\n* [moveit_visual_tools](https:\u002F\u002Fgithub.com\u002Fros-planning\u002Fmoveit_visual_tools) - 通过发布的标记在RViz中显示和调试MoveIt!数据的辅助函数。\n\n\n## 操作系统\n### 监控\n* [rosmon](https:\u002F\u002Fgithub.com\u002Fxqms\u002Frosmon) - ROS节点启动器及监控守护进程。\n* [multimaster_fkie](https:\u002F\u002Fgithub.com\u002Ffkie\u002Fmultimaster_fkie) - 基于GUI的管理环境，非常有助于管理ROS启动配置和控制正在运行的节点。\n* [collectd](https:\u002F\u002Fgithub.com\u002Fcollectd\u002Fcollectd\u002F) - 一个小型守护进程，定期收集系统信息，并提供多种机制来存储和监控这些值。\n* [lnav](http:\u002F\u002Flnav.org\u002F) - 一种增强的日志文件查看器，能够利用所查看文件中的任何语义信息，例如时间戳和日志级别。\n* [htop](https:\u002F\u002Fgithub.com\u002Fhishamhm\u002Fhtop) - 一款面向Unix系统的交互式文本模式进程查看器。其目标是成为更好的“top”。\n* [atop](https:\u002F\u002Fgithub.com\u002FAtoptool\u002Fatop) - 一款具有日志记录和回放功能的Linux系统与进程监控工具。\n* [psutil](https:\u002F\u002Fgithub.com\u002Fgiampaolo\u002Fpsutil) - 一个跨平台的Python库，用于进程和系统监控。\n* [gputil](https:\u002F\u002Fgithub.com\u002Fanderskm\u002Fgputil) - 一个Python模块，用于通过nvidia-smi程序化地从NVIDIA GPU获取GPU状态。\n* [gpustat](https:\u002F\u002Fgithub.com\u002Fwookayin\u002Fgpustat) - 一个简单的命令行实用程序，用于查询和监控GPU状态。\n* [nvtop](https:\u002F\u002Fgithub.com\u002FSyllo\u002Fnvtop) - 类似htop的NVIDIA GPU监控工具。\n* [ShellHub](https:\u002F\u002Fwww.shellhub.io) - ShellHub是一个现代化的SSH服务器，可通过命令行（使用任何SSH客户端）或基于Web的用户界面远程访问Linux设备，旨在作为sshd的替代方案。可以将ShellHub视为面向边缘计算和云计算的集中式SSH。\n* [Sshwifty](https:\u002F\u002Fgithub.com\u002Fnirui\u002Fsshwifty) - Sshwifty是一款专为Web设计的SSH和Telnet连接工具。\n* [spdlog](https:\u002F\u002Fgithub.com\u002Fgabime\u002Fspdlog) - 一个非常快速、仅包含头文件或已编译的C++日志库。\n* [ctop](https:\u002F\u002Fgithub.com\u002Fbcicen\u002Fctop) - 一个类似于top的容器指标界面。\n* [ntop](https:\u002F\u002Fgithub.com\u002Fntop\u002Fntopng) - 基于Web的流量与安全网络流量监控。\n* [jupyterlab-nvdashboard](https:\u002F\u002Fgithub.com\u002Frapidsai\u002Fjupyterlab-nvdashboard) - 一个用于显示GPU使用情况仪表板的JupyterLab扩展。\n\n### 数据库与记录\n* [ncdu](https:\u002F\u002Fdev.yorhel.nl\u002Fncdu) - Ncdu是一个带有ncurses界面的磁盘使用分析工具。\n* [borg](https:\u002F\u002Fgithub.com\u002Fborgbackup\u002Fborg) - 一种具有去重、压缩和认证加密功能的归档工具。\n* [bag-database](https:\u002F\u002Fgithub.com\u002Fswri-robotics\u002Fbag-database) - 一个用于编目bag文件并提供基于Web的UI以访问这些文件的服务器。\n* [marv-robotics](https:\u002F\u002Fgitlab.com\u002Fternaris\u002Fmarv-robotics) - MARV Robotics是一个强大且可扩展的数据管理平台。\n* [kitti2bag](https:\u002F\u002Fgithub.com\u002Ftomas789\u002Fkitti2bag) - 以简单的方式将KITTI数据集转换为ROS bag文件。\n* [pykitti](https:\u002F\u002Fgithub.com\u002FutiasSTARS\u002Fpykitti) - 用于处理KITTI数据的Python工具。\n* [rosbag_editor](https:\u002F\u002Fgithub.com\u002Ffacontidavide\u002Frosbag_editor) - 使用简单的GUI从现有rosbag中创建新的rosbag。\n* [nextcloud](https:\u002F\u002Fgithub.com\u002Fnextcloud\u002Fserver) - Nextcloud是一套客户端-服务器软件，用于创建和使用文件托管服务。\n* [ros_type_introspection](https:\u002F\u002Fgithub.com\u002Ffacontidavide\u002Fros_type_introspection) - 反序列化在编译时未知的ROS消息。\n* [syncthing](https:\u002F\u002Fgithub.com\u002Fsyncthing\u002Fsyncthing) - 一个持续的文件同步程序。\n* [rqt_bag_exporter](https:\u002F\u002Fgitlab.com\u002FInstitutMaupertuis\u002Frqt_bag_exporter) - 一个Qt GUI，用于将ROS bag主题导出为文件（CSV和\u002F或视频）。\n* [xviz](https:\u002F\u002Fgithub.com\u002Fuber\u002Fxviz) - 一种用于实时传输和可视化自动驾驶数据的协议。\n* [kitti_to_rosbag](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fkitti_to_rosbag) - 一套用于处理KITTI原始数据并将其转换为ROS bag的工具。同时还提供了一个库，可以直接访问位姿、Velodyne扫描和图像。\n* [ros_numpy](https:\u002F\u002Fgithub.com\u002Feric-wieser\u002Fros_numpy) - 用于在ROS消息与numpy数组之间进行转换的工具。\n* [kitti_ros](https:\u002F\u002Fgithub.com\u002FLidarPerception\u002Fkitti_ros) - 一个基于ROS的播放器，用于回放KITTI数据集。\n* [DuckDB](https:\u002F\u002Fgithub.com\u002Fcwida\u002Fduckdb) - 一个可嵌入的SQL OLAP数据库管理系统。\n\n### 网络分布式文件系统\n* [sshfs](https:\u002F\u002Fgithub.com\u002Fosxfuse\u002Fsshfs) - 基于SSH文件传输协议的文件系统。\n* [moosefs](https:\u002F\u002Fgithub.com\u002Fmoosefs\u002Fmoosefs) - 一个可扩展的分布式存储系统。\n* [ceph](https:\u002F\u002Fgithub.com\u002Fceph\u002Fceph) - 一个分布式对象、块和文件存储平台。\n* [nfs](https:\u002F\u002Fgithub.com\u002Fsahlberg\u002Flibnfs) - 一种最初由Sun Microsystems开发的分布式文件系统协议。\n* [ansible-role-nfs](https:\u002F\u002Fgithub.com\u002Fgeerlingguy\u002Fansible-role-nfs) - 在RedHat\u002FCentOS或Debian\u002FUbuntu上安装NFS实用程序。\n\n### 服务器基础设施与高性能计算\n* [mass](https:\u002F\u002Fgithub.com\u002Fmaas\u002Fmaas) - 自助式远程安装 Windows、CentOS、ESXi 和 Ubuntu 到物理服务器上，将您的数据中心转变为裸机云。\n* [polyaxon](https:\u002F\u002Fgithub.com\u002Fpolyaxon\u002Fpolyaxon) - 一个用于复现和管理机器学习及深度学习应用全生命周期的平台。\n* [localstack](https:\u002F\u002Fgithub.com\u002Flocalstack\u002Flocalstack) - 一个功能齐全的本地 AWS 云栈。可在离线状态下开发和测试您的云及无服务器应用。\n* [nvidia-docker](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fnvidia-docker) - 构建并运行利用 NVIDIA GPU 的 Docker 容器。\n* [kubeflow](https:\u002F\u002Fgithub.com\u002Fkubeflow\u002Fkubeflow) - 面向 Kubernetes 的机器学习工具包。\n* [log-pilot](https:\u002F\u002Fgithub.com\u002FAliyunContainerService\u002Flog-pilot) - 收集 Docker 容器的日志。\n* [traefik](https:\u002F\u002Fgithub.com\u002Fcontainous\u002Ftraefik) - 云原生边缘路由器。\n* [graylog2-server](https:\u002F\u002Fgithub.com\u002FGraylog2\u002Fgraylog2-server) - 免费且开源的日志管理工具。\n* [ansible](https:\u002F\u002Fgithub.com\u002Fansible\u002Fansible) - Ansible 是一款极简的 IT 自动化平台，可让您更轻松地部署应用程序和系统。\n* [pyinfra](https:\u002F\u002Fgithub.com\u002FFizzadar\u002Fpyinfra) - 可用于临时命令执行、服务部署、配置管理等。\n* [docker-py](https:\u002F\u002Fgithub.com\u002Fdocker\u002Fdocker-py) - Docker Engine API 的 Python 库。\n* [noVNC](https:\u002F\u002Fgithub.com\u002Fnovnc\u002FnoVNC) - 基于 HTML5 的 VNC 客户端。\n* [Slurm](https:\u002F\u002Fgithub.com\u002FSchedMD\u002Fslurm) - Slurm：高度可扩展的工作负载管理器。\n* [jupyterhub](https:\u002F\u002Fgithub.com\u002Fjupyterhub\u002Fjupyterhub) - Jupyter 笔记本的多用户服务器。\n* [Portainer](https:\u002F\u002Fgithub.com\u002Fportainer\u002Fportainer) - 让 Docker 管理变得简单。\n* [enroot](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fenroot) - 一种简单而强大的工具，可将传统的容器\u002F操作系统镜像转换为非特权沙盒环境。\n* [docker-firefox](https:\u002F\u002Fgithub.com\u002Fjlesage\u002Fdocker-firefox) - 运行包含 Firefox 和 noVNC 的 Docker 容器，以便远程访问无头服务器。\n* [luigi](https:\u002F\u002Fgithub.com\u002Fspotify\u002Fluigi) - 一个帮助您构建复杂批处理作业流水线的 Python 模块。它负责处理依赖关系解析、工作流管理、可视化等功能，并内置了对 Hadoop 的支持。\n* [triton-inference-server](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Ftriton-inference-server) - NVIDIA Triton 推理服务器提供针对 NVIDIA GPU 优化的云端推理解决方案。\n* [cudf](https:\u002F\u002Fgithub.com\u002Frapidsai\u002Fcudf) - 提供类似 pandas 的 API，数据工程师和数据科学家会感到熟悉，因此他们可以使用该库轻松加速工作流程，而无需深入了解 CUDA 编程细节。\n\n\n### 嵌入式操作系统\n* [vxworks7-ros2-build](https:\u002F\u002Fgithub.com\u002FWind-River\u002Fvxworks7-ros2-build) - 用于自动化构建 VxWorks 7 和 ROS2 的构建系统。\n* [Yocto](https:\u002F\u002Fgit.yoctoproject.org\u002F) - 提供工具和流程，使开发者能够为嵌入式软件创建独立于底层硬件架构的 Linux 发行版。\n* [Automotive Graded Linux](https:\u002F\u002Fwww.automotivelinux.org\u002Fsoftware) - 一个协作式的开源项目，汇集汽车制造商、供应商和技术公司，共同构建基于 Linux 的开放式软件平台，用于汽车应用，有望成为事实上的行业标准。\n* [bitbake](https:\u002F\u002Fgithub.com\u002Fopenembedded\u002Fbitbake) - 一个通用的任务执行引擎，能够在复杂的任务间依赖约束下高效并行地运行 Shell 和 Python 任务。\n* [Jailhouse](https:\u002F\u002Fgithub.com\u002Fsiemens\u002Fjailhouse) - Jailhouse 是一个基于 Linux 的分区型虚拟机管理程序。\n* [Xen](https:\u002F\u002Fwiki.debian.org\u002FXen) - 一个开源（GPL）Type-1 或裸金属虚拟机管理程序。\n* [QEMU](https:\u002F\u002Fwww.qemu.org\u002F) - 一个通用且开源的机器模拟器和虚拟化工具。\n* [qemu-xilinx](https:\u002F\u002Fgithub.com\u002FXilinx\u002Fqemu) - Quick EMUlator (QEMU) 的分支版本，针对 Xilinx 平台提供了更好的支持和建模。\n* [rosserial](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Frosserial) - 适用于小型嵌入式设备（如 Arduino）的 ROS 客户端库。\n* [meta-ros](https:\u002F\u002Fgithub.com\u002Fros\u002Fmeta-ros\u002Ftree\u002Fthud-draft) - 用于 ROS 应用的 OpenEmbedded 层。\n* [meta-balena](https:\u002F\u002Fgithub.com\u002Fbalena-os\u002Fmeta-balena) - 在嵌入式设备上运行 Docker 容器。\n* [micro-ros](https:\u002F\u002Fmicro-ros.github.io\u002F) - 与“常规”ROS 2 相比，主要区别在于 micro-ROS 使用实时操作系统 (RTOS)，而非 Linux，并采用 DDS 协议以适应资源极度受限的环境。\n* [nvidia-container-runtime](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fnvidia-container-runtime\u002F) - NVIDIA 容器运行时是一种感知 GPU 的容器运行时，兼容 Docker、CRI-O 等主流容器技术所使用的开放容器倡议 (OCI) 规范。\n* [fusesoc](https:\u002F\u002Fgithub.com\u002Folofk\u002Ffusesoc) - 用于 FPGA\u002FASIC 开发的包管理器和构建抽象工具。\n* [jetson_easy](https:\u002F\u002Fgithub.com\u002Frbonghi\u002Fjetson_easy) - 自动化脚本，用于设置和配置您的 NVIDIA Jetson 设备。\n* [docker-jetpack-sdk](https:\u002F\u002Fgithub.com\u002Ftrn84\u002Fdocker-jetpack-sdk) - 允许在 Docker 容器内使用 NVIDIA JetPack SDK 进行下载、刷机和安装。\n* [Pressed](https:\u002F\u002Fwiki.debian.org\u002FDebianInstaller\u002FPreseed) - 提供了一种方式，在 Debian 安装过程中自动回答问题，而无需在安装进行时手动输入答案。\n* [jetson_stats](https:\u002F\u002Fgithub.com\u002Frbonghi\u002Fjetson_stats) - 用于监控和控制您的 NVIDIA Jetson 设备（Xavier NX、Nano、AGX Xavier、TX1、TX2）的工具包，兼容所有 NVIDIA Jetson 生态系统。\n* [ros_jetson_stats](https:\u002F\u002Fgithub.com\u002Frbonghi\u002Fros_jetson_stats) - ROS 版本的 jetson-stats 包装器，可在诊断消息中显示您的 NVIDIA Jetson 设备状态。\n* [OpenCR](https:\u002F\u002Fgithub.com\u002FROBOTIS-GIT\u002FOpenCR) - 用于 ROS 的开源控制模块。\n* [acrn-hypervisor](https:\u002F\u002Fgithub.com\u002Fprojectacrn\u002Facrn-hypervisor) - 定义了一个设备虚拟机管理程序参考栈以及架构，允许在一个整合系统上通过虚拟机管理程序安全地运行多个软件子系统。\n* [jetson-containers](https:\u002F\u002Fgithub.com\u002Fdusty-nv\u002Fjetson-containers) - 适用于 Jetson 和 JetPack 4.4 的机器学习容器。\n\n\n### 实时内核\n* [ELISA](https:\u002F\u002Felisa.tech\u002F) - 该项目旨在简化企业构建和认证基于 Linux 的安全关键型应用——即那些一旦失效可能导致人员伤亡、重大财产损失或环境破坏的系统。\n* [PREEMPT_RT 内核补丁](https:\u002F\u002Fwiki.linuxfoundation.org\u002Frealtime\u002Fdocumentation\u002Fstart) - PREEMPT_RT 内核补丁的目标是尽量减少不可抢占的内核代码量。\n\n## 网络与中间件\n* [performance_test](https:\u002F\u002Fgithub.com\u002FApexAI\u002Fperformance_test) - 用于测试基于发布\u002F订阅通信框架性能的工具。\n* [realtime_support](https:\u002F\u002Fgithub.com\u002Fros2\u002Frealtime_support) - 用于测量抖动和延迟的最小化实时测试工具。\n* [ros1_bridge](https:\u002F\u002Fgithub.com\u002Fros2\u002Fros1_bridge) - 提供ROS 1与ROS 2之间双向通信的ROS 2软件包。\n* [Fast-RTPS](https:\u002F\u002Fgithub.com\u002FeProsima\u002FFast-RTPS) - 由对象管理组织（OMG）联盟定义并维护的一种协议，它通过UDP等不可靠传输介质提供发布-订阅通信。\n* [protobuf](https:\u002F\u002Fgithub.com\u002Fprotocolbuffers\u002Fprotobuf) - Google的数据交换格式。\n* [opensplice](https:\u002F\u002Fgithub.com\u002FADLINK-IST\u002Fopensplice) - Vortex OpenSplice社区版。\n* [cyclonedds](https:\u002F\u002Fgithub.com\u002Feclipse-cyclonedds\u002Fcyclonedds) - Eclipse Cyclone DDS是一个高性能且健壮的开源DDS实现。\n* [iceoryx](https:\u002F\u002Fgithub.com\u002Feclipse\u002Ficeoryx) - 适用于基于POSIX系统的IPC中间件。\n* [rosbridge_suite](https:\u002F\u002Fgithub.com\u002FRobotWebTools\u002Frosbridge_suite) - 提供ROS的JSON接口，允许任何客户端发送JSON来发布或订阅ROS话题、调用ROS服务等。\n* [ros2arduino](https:\u002F\u002Fgithub.com\u002FROBOTIS-GIT\u002Fros2arduino) - 该库帮助Arduino板使用XRCE-DDS与ROS2进行通信。\n* [eCAL](https:\u002F\u002Fgithub.com\u002Fcontinental\u002F) - 增强型通信抽象层（eCAL）是一种中间件，可在单个计算机节点上或计算机网络中的不同节点之间实现可扩展、高性能的进程间通信。\n* [AUTOSAR-Adaptive](https:\u002F\u002Fgithub.com\u002FUmlautSoftwareDevelopmentAccount\u002FAUTOSAR-Adaptive) - 基于R19-11的AUTOSAR Adaptive平台实现。\n* [ocpp](https:\u002F\u002Fgithub.com\u002FNewMotion\u002Focpp) - 开放式充电桩协议（OCPP）是一种用于电动汽车充电器与中央后台系统之间通信的网络协议。\n* [micro-ROS for Arduino](https:\u002F\u002Fgithub.com\u002Fmicro-ROS\u002Fmicro_ros_arduino) - 一个基于Arduino IDE或Arduino CLI的裸机项目的实验性micro-ROS库。\n* [mqtt_bridge](https:\u002F\u002Fgithub.com\u002Fgroove-x\u002Fmqtt_bridge) - 提供ROS与MQTT之间双向桥接功能。\n\n\n### 以太网与无线网络\n* [SOES](https:\u002F\u002Fgithub.com\u002FOpenEtherCATsociety\u002FSOES) - SOES是用C语言编写的EtherCAT从站栈。\n* [netplan](https:\u002F\u002Fnetplan.io\u002F) - 只需创建所需网络接口及其配置的YAML描述即可。\n* [airalab](https:\u002F\u002Fgithub.com\u002Fairalab) - AIRA是面向支持ROS的网络物理系统的参考Robonomics网络客户端。\n* [rdbox](https:\u002F\u002Fgithub.com\u002Frdbox-intec\u002Frdbox) - RDBOX是为ROS机器人设计的IT基础设施。\n* [ros_ethercat](https:\u002F\u002Fgithub.com\u002Fshadow-robot\u002Fros_ethercat) - 这是对pr2_ethercat主循环的重新实现，不依赖于PR2软件。\n* [wavemon](https:\u002F\u002Fgithub.com\u002Fuoaerg\u002Fwavemon) - 一款基于ncurses的无线网络设备监控应用。\n* [wireless](https:\u002F\u002Fgithub.com\u002Fclearpathrobotics\u002Fwireless) - 使ROS能够获取无线网络信息。\n* [ptpd](https:\u002F\u002Fgithub.com\u002Fptpd\u002Fptpd) - PTP守护进程（PTPd）是根据IEEE Std 1588-2008标准实现的精确时间协议（PTP）版本2。PTP可为以太网局域网连接的计算机提供精确的时间同步。\n* [iperf](https:\u002F\u002Fgithub.com\u002Fesnet\u002Fiperf) - 一种用于测量TCP、UDP和SCTP网络带宽的工具。\n* [tcpreplay](https:\u002F\u002Fgithub.com\u002Fappneta\u002Ftcpreplay) - 用于pcap文件编辑和重放的工具。\n* [nethogs](https:\u002F\u002Fgithub.com\u002Fraboof\u002Fnethogs) - 按进程对带宽进行分组。\n* [pyshark](https:\u002F\u002Fgithub.com\u002FKimiNewt\u002Fpyshark) - tshark的Python封装，允许使用Wireshark解码器进行Python数据包解析。\n* [pingtop](https:\u002F\u002Fgithub.com\u002Flaixintao\u002Fpingtop) - 同时ping多个服务器，并在类似top的终端界面中显示结果。\n* [termshark](https:\u002F\u002Fgithub.com\u002Fgcla\u002Ftermshark) - 一款受Wireshark启发的tshark终端UI。\n* [udpreplay](https:\u002F\u002Fgithub.com\u002Frigtorp\u002Fudpreplay) - 从pcap文件中重放UDP数据包。\n* [openwifi](https:\u002F\u002Fgithub.com\u002Fopen-sdr\u002Fopenwifi) - 基于软件定义无线电的Linux mac80211兼容全栈IEEE802.11\u002FWi-Fi设计。\n\n### 控制器局域网\n* [awesome CAN](https:\u002F\u002Fgithub.com\u002FiDoka\u002Fawesome-canbus) - 一个精选的、关于CAN总线工具、硬件和资源的列表。\n* [AndrOBD](https:\u002F\u002Fgithub.com\u002Ffr3ts0n\u002FAndrOBD) - 使用任何ELM327适配器进行Android OBD诊断。\n* [ddt4all](https:\u002F\u002Fgithub.com\u002Fcedricp\u002Fddt4all) - DDT4All是一款工具，可用于创建自定义的ECU参数界面，并通过廉价的ELM327接口连接到CAN网络。\n* [cabana](https:\u002F\u002Fgithub.com\u002Fcommaai\u002Fcabana) - CAN可视化工具及DBC文件生成器。\n* [opendbc](https:\u002F\u002Fgithub.com\u002Fcommaai\u002Fopendbc) - 该项目旨在 democratize 您爱车解码环的访问权限。\n* [libuavcan](https:\u002F\u002Fgithub.com\u002FUAVCAN\u002Flibuavcan) - 一种开源的轻量级协议，专为航空航天和机器人应用设计，可在诸如CAN总线等稳健的车载网络上实现可靠通信。\n* [python-can](https:\u002F\u002Fgithub.com\u002Fhardbyte\u002Fpython-can) - can包为Python开发者提供控制器局域网支持。\n* [CANopenNode](https:\u002F\u002Fgithub.com\u002FCANopenNode\u002FCANopenNode) - 国际标准化（EN 50325-4）（CiA301）的基于CAN的嵌入式控制系统高层协议。\n* [python-udsoncan](https:\u002F\u002Fgithub.com\u002Fpylessard\u002Fpython-udsoncan) - UDS（ISO-14229）标准的Python实现。\n* [uds-c](https:\u002F\u002Fgithub.com\u002Fopenxc\u002Fuds-c) - 统一诊断服务（UDS）和OBD-II（车辆车载诊断）C语言库。\n* [cantools](https:\u002F\u002Fgithub.com\u002Feerimoq\u002Fcantools) - Python 3中的CAN总线工具。\n* [CANdevStudio](https:\u002F\u002Fgithub.com\u002FGENIVI\u002FCANdevStudio) - CANdevStudio旨在成为CAN仿真软件的经济高效替代品。它可与多种CAN硬件接口配合使用。\n* [can-utils](https:\u002F\u002Fgithub.com\u002Flinux-can\u002Fcan-utils) - Linux-CAN \u002F SocketCAN用户空间应用程序。\n* [ros_canopen](https:\u002F\u002Fgithub.com\u002Fros-industrial\u002Fros_canopen) - 面向ROS的CANopen驱动框架。\n* [decanstructor](https:\u002F\u002Fgithub.com\u002FJWhitleyAStuff\u002Fdecanstructor) - 最权威的ROS CAN分析工具。\n* [kvaser_interface](https:\u002F\u002Fgithub.com\u002Fastuff\u002Fkvaser_interface) - 该软件包旨在提供一种标准化方式，从ROS中访问Kvaser CAN设备。\n* [canmatrix](https:\u002F\u002Fgithub.com\u002Febroecker\u002Fcanmatrix) - 用于转换CAN数据库格式：.arxml、.dbc、.dbf、.kcd。\n* [autosar](https:\u002F\u002Fgithub.com\u002Fcogu\u002Fautosar) - 一组用于处理AUTOSAR XML文件的Python模块。\n* [canopen](https:\u002F\u002Fgithub.com\u002Fchristiansandberg\u002Fcanopen) - CANopen标准的Python实现。该项目的目标是通过Python式的接口支持CiA 301标准中最常用的部分。\n* [SavvyCAN](https:\u002F\u002Fgithub.com\u002Fcollin80\u002FSavvyCAN) - 基于Qt5的跨平台工具，可用于加载、保存和捕获CAN总线帧。\n* [Open-Vehicle-Monitoring-System-3](https:\u002F\u002Fgithub.com\u002Fopenvehicles\u002FOpen-Vehicle-Monitoring-System-3) - 该系统可实时监控车辆的各项指标，如电池荷电状态、温度、胎压以及诊断故障信息。\n\n### 传感器与执行器接口\n* [Tesla-API](https:\u002F\u002Fgithub.com\u002Ftimdorr\u002Ftesla-api) - 提供远程监控和控制Model S（以及未来特斯拉车型）的功能。\n* [flirpy](https:\u002F\u002Fgithub.com\u002FLJMUAstroecology\u002Fflirpy) - 一个用于与FLIR热成像相机及图像交互的Python库。\n* [nerian_stereo](https:\u002F\u002Fgithub.com\u002Fnerian-vision\u002Fnerian_stereo) - 用于Nerian的SceneScan和SP1双目视觉传感器的ROS节点。\n* [pymmw](https:\u002F\u002Fgithub.com\u002Fm6c7l\u002Fpymmw) - 这是一个由Python脚本组成的工具箱，用于与TI的IWR1443毫米波感知设备评估模块（BoosterPack）进行交互。\n* [ti_mmwave_rospkg](https:\u002F\u002Fgithub.com\u002Fradar-lab\u002Fti_mmwave_rospkg) - TI毫米波雷达ROS驱动程序（包含传感器融合和混合功能）。\n* [pacmod3](https:\u002F\u002Fgithub.com\u002Fastuff\u002Fpacmod3) - 该ROS节点旨在让用户通过PACMod线控系统（板卡版本3）来控制车辆。\n* [ros2_intel_realsense](https:\u002F\u002Fgithub.com\u002Fintel\u002Fros2_intel_realsense) - 这些是用于在ROS2中使用Intel RealSense相机（D400系列）的软件包。\n* [sick_scan](https:\u002F\u002Fgithub.com\u002FSICKAG\u002Fsick_scan) - 该栈提供适用于SICK TiM系列激光扫描仪的ROS2驱动程序。\n* [ouster_example](https:\u002F\u002Fgithub.com\u002Fouster-lidar\u002Fouster_example) - 用于连接和配置OS1、读取及可视化数据，并与ROS对接的示例代码。\n* [ros2_ouster_drivers](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Fros2_ouster_drivers) - 这些是Ouster OS-1 3D激光雷达的ROS2驱动程序实现。\n* [livox_ros_driver](https:\u002F\u002Fgithub.com\u002FLivox-SDK\u002Flivox_ros_driver) - 一个新的ROS软件包，专门用于连接Livox生产的激光雷达产品。\n* [velodyne](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Fvelodyne) - 一组支持Velodyne高精度3D激光雷达的ROS软件包。\n* [ublox](https:\u002F\u002Fgithub.com\u002FKumarRobotics\u002Fublox) - 提供对u-blox GPS接收器的支持。\n* [crazyflie_ros](https:\u002F\u002Fgithub.com\u002Fwhoenig\u002Fcrazyflie_ros) - Bitcraze Crazyflie的ROS驱动程序。\n* [pointgrey_camera_driver](https:\u002F\u002Fgithub.com\u002Fros-drivers\u002Fpointgrey_camera_driver) - 基于官方FlyCapture2 SDK的Pt. Grey相机ROS驱动程序。\n* [novatel_gps_driver](https:\u002F\u002Fgithub.com\u002Fswri-robotics\u002Fnovatel_gps_driver) - NovAtel GPS\u002FGNSS接收器的ROS驱动程序。\n* [pylon-ros-camera](https:\u002F\u002Fgithub.com\u002Fbasler\u002Fpylon-ros-camera) - Basler GigE Vision和USB3 Vision相机的官方pylon ROS驱动程序。\n* [ethz_piksi_ros](https:\u002F\u002Fgithub.com\u002Fethz-asl\u002Fethz_piksi_ros) - 包含用于在ROS中使用Piksi实时动态定位（RTK）GPS设备的（Python）ROS驱动程序、工具、启动文件以及相关维基文档。\n* [sick_safetyscanners](https:\u002F\u002Fgithub.com\u002FSICKAG\u002Fsick_safetyscanners) - 一个ROS驱动程序，用于读取SICK安全扫描仪的原始数据，并将其以laser_scan消息的形式发布。\n* [bosch_imu_driver](https:\u002F\u002Fgithub.com\u002Fmdrwiega\u002Fbosch_imu_driver) - Bosch BNO055 IMU传感器的驱动程序。仅实现了UART通信接口（需选择正确的传感器模式）。\n* [oxford_gps_eth](https:\u002F\u002Fbitbucket.org\u002FDataspeedInc\u002Foxford_gps_eth\u002F) - 使用NCOM数据包结构为OxTS GPS接收器提供的以太网接口。\n* [ifm3d](https:\u002F\u002Fgithub.com\u002Fifm\u002Fifm3d) - 用于操作ifm基于pmd技术的3D ToF相机的库和实用工具。\n* [cepton_sdk_redist](https:\u002F\u002Fgithub.com\u002Fceptontech\u002Fcepton_sdk_redist\u002F) - 为Cepton激光雷达提供ROS支持。\n* [jetson_csi_cam](https:\u002F\u002Fgithub.com\u002Fpeter-moran\u002Fjetson_csi_cam) - 一个ROS软件包，使用户能够轻松地在Nvidia Jetson TK1、TX1或TX2上使用CSI摄像头并与ROS集成。\n* [ros_astra_camera](https:\u002F\u002Fgithub.com\u002Forbbec\u002Fros_astra_camera) - Orbbec 3D相机的ROS驱动程序。\n* [spot_ros](https:\u002F\u002Fgithub.com\u002Fclearpathrobotics\u002Fspot_ros) - Spot机器人的ROS驱动程序。\n* [blickfeld-scanner-lib](https:\u002F\u002Fgithub.com\u002FBlickfeld\u002Fblickfeld-scanner-lib) - 一个跨平台库，用于与Blickfeld GmbH的激光雷达设备进行通信。\n* [TauLidarCamera](https:\u002F\u002Fgithub.com\u002FOnionIoT\u002Ftau-LiDAR-camera) - 用于构建基于Tau LiDAR Camera应用的主机端API。\n\n## 安全\n* [owasp-threat-dragon-desktop](https:\u002F\u002Fgithub.com\u002Fmike-goodwin\u002Fowasp-threat-dragon-desktop) - Threat Dragon 是一款免费、开源、跨平台的威胁建模应用，支持系统绘图和规则引擎，可自动生成威胁与缓解措施。\n* [launch_ros_sandbox](https:\u002F\u002Fgithub.com\u002Fros-tooling\u002Flaunch_ros_sandbox) - 可以定义在受限环境中运行节点的启动文件，例如 Docker 容器或具有有限权限的独立用户账户。\n* [wolfssl](https:\u002F\u002Fgithub.com\u002FwolfSSL\u002Fwolfssl) - 一个小型、快速、可移植的 TLS\u002FSSL 实现，适用于从嵌入式设备到云端的各种场景。\n* [CANalyzat0r](https:\u002F\u002Fgithub.com\u002Fschutzwerk\u002FCANalyzat0r) - 针对专有汽车协议的安全分析工具包。\n* [RSF](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002FRSF) - 机器人安全框架 (RSF) 是一种用于执行机器人安全评估的标准化方法论。\n* [How-to-Secure-A-Linux-Server](https:\u002F\u002Fgithub.com\u002Fimthenachoman\u002FHow-To-Secure-A-Linux-Server) - 一份不断更新的 Linux 服务器安全指南。\n* [lynis](https:\u002F\u002Fgithub.com\u002FCISOfy\u002Flynis) - 适用于 Linux、macOS 和基于 UNIX 的系统的安全审计工具。有助于合规性测试（HIPAA\u002FISO27001\u002FPCI DSS）和系统加固。\n* [OpenVPN](https:\u002F\u002Fgithub.com\u002FOpenVPN\u002Fopenvpn) - 一个开源的 VPN 守护进程。\n* [openfortivpn](https:\u002F\u002Fgithub.com\u002Fadrienverge\u002Fopenfortivpn) - 一个用于 PPP+SSL VPN 隧道服务的客户端，兼容 Fortinet VPN。\n* [WireGuard](https:\u002F\u002Fgithub.com\u002FWireGuard\u002FWireGuard) - WireGuard 是一种创新的 VPN，直接运行在 Linux 内核中，并采用最先进的密码学技术。\n* [ssh-auditor](https:\u002F\u002Fgithub.com\u002Fncsa\u002Fssh-auditor) - 扫描您网络中的弱 SSH 密码。\n* [vulscan](https:\u002F\u002Fgithub.com\u002Fscipag\u002Fvulscan) - 使用 Nmap NSE 进行高级漏洞扫描。\n* [nmap-vulners](https:\u002F\u002Fgithub.com\u002FvulnersCom\u002Fnmap-vulners) - 基于 Vulners.com API 的 NSE 脚本。\n* [brutespray](https:\u002F\u002Fgithub.com\u002Fx90skysn3k\u002Fbrutespray) - 自动尝试针对发现的服务使用默认凭据。\n* [fail2ban](https:\u002F\u002Fgithub.com\u002Ffail2ban\u002Ffail2ban) - 一个守护进程，用于封禁多次认证失败的主机。\n* [DependencyCheck](https:\u002F\u002Fgithub.com\u002Fjeremylong\u002FDependencyCheck) - 一款软件成分分析工具，可检测应用程序依赖项中公开披露的漏洞。\n* [Firejail](https:\u002F\u002Fgithub.com\u002Fnetblue30\u002Ffirejail) - 一个 SUID 沙箱程序，通过使用 Linux 命名空间、seccomp-bpf 和 Linux 功能集来限制不受信任应用程序的运行环境，从而降低安全漏洞的风险。\n* [RVD](https:\u002F\u002Fgithub.com\u002Faliasrobotics\u002FRVD) - 机器人漏洞数据库。由社区贡献的机器人漏洞与弱点档案。\n* [ros2_dds_security](http:\u002F\u002Fdesign.ros2.org\u002Farticles\u002Fros2_dds_security.html) - 通过定义服务插件接口 (SPI) 架构、一组内置的 SPI 实现以及由 SPI 强制实施的安全模型，来增强安全性。\n* [Security-Enhanced Linux](https:\u002F\u002Fgithub.com\u002FSELinuxProject\u002Fselinux) - 一个 Linux 内核安全模块，提供支持访问控制安全策略的机制，包括强制访问控制 (MAC)。\n* [OpenTitan](https:\u002F\u002Fgithub.com\u002FlowRISC\u002Fopentitan) - 将使硅根信任的设计和实现更加透明、可信且安全，适用于企业、平台提供商和芯片制造商。OpenTitan 由 lowRISC CIC 管理，作为一个协作项目，旨在生成高质量的开放 IP，以便作为功能齐全的产品进行部署。\n* [bandit](https:\u002F\u002Fgithub.com\u002FPyCQA\u002Fbandit) - 一个用于查找 Python 代码中常见安全问题的工具。\n* [hardening](https:\u002F\u002Fgithub.com\u002Fkonstruktoid\u002Fhardening) - 一种快速提升 Ubuntu 服务器安全性的方法。\n* [Passbolt](https:\u002F\u002Fgithub.com\u002Fpassbolt\u002Fpassbolt_docker) - Passbolt 是一款免费且开源的密码管理器，允许团队成员安全地存储和共享凭据。\n* [gopass](https:\u002F\u002Fgithub.com\u002Fgopasspw\u002Fgopass) - 一个用 Go 编写的命令行密码管理器。\n* [pass](https:\u002F\u002Fwww.passwordstore.org\u002F) - 标准的 Unix 密码管理器。\n* [Vault](https:\u002F\u002Fgithub.com\u002Fhashicorp\u002Fvault) - 一个用于安全访问机密信息的工具。机密是指任何需要严格控制访问权限的内容，例如 API 密钥、密码、证书等。\n* [legion](https:\u002F\u002Fgithub.com\u002FGoVanguard\u002Flegion) - 一个开源、易用、高度可扩展且半自动化的网络渗透测试框架，有助于信息系统的发现、侦察和利用。\n* [openscap](https:\u002F\u002Fgithub.com\u002FOpenSCAP\u002Fopenscap) - oscap 程序是一个命令行工具，允许用户加载、扫描、验证、编辑和导出 SCAP 文档。\n\n## 数据集\n* [Papers With Code](https:\u002F\u002Fwww.paperswithcode.com\u002Fdatasets) - Papers With Code 提供的数千个机器学习数据集。\n* [KITTI-360](https:\u002F\u002Fgithub.com\u002Fautonomousvision\u002Fkitti360Scripts) - 这个大规模数据集包含 32 万张图像和 10 万次激光扫描，覆盖 73.7 公里的行驶距离。\n* [waymo_ros](https:\u002F\u002Fgithub.com\u002FYonoHub\u002Fwaymo_ros) - 这是一个用于将 Waymo 开放数据集连接到 ROS 的 ROS 包。\n* [waymo-open-dataset](https:\u002F\u002Fgithub.com\u002Fwaymo-research\u002Fwaymo-open-dataset) - Waymo 开放数据集由 Waymo 自动驾驶汽车在各种条件下收集的高分辨率传感器数据组成。\n* [福特自动驾驶车辆数据集](https:\u002F\u002Favdata.ford.com\u002Fhome\u002Fdefault.aspx) - 福特提供了一个具有挑战性的多智能体季节性数据集，该数据集由福特自动驾驶车队在不同日期和时间收集而成。\n* [awesome-robotics-datasets](https:\u002F\u002Fgithub.com\u002Fsunglok\u002Fawesome-robotics-datasets) - 面向机器人技术和计算机视觉的实用数据集合集。\n* [nuscenes-devkit](https:\u002F\u002Fgithub.com\u002Fnutonomy\u002Fnuscenes-devkit) - nuScenes 数据集的开发工具包。\n* [dataset-api](https:\u002F\u002Fgithub.com\u002FApolloScapeAuto\u002Fdataset-api) - 这是 ApolloScape 数据集、CVPR 2019 自动驾驶挑战研讨会以及 ECCV 2018 挑战赛的工具库仓库。\n* [utbm_robocar_dataset](https:\u002F\u002Fgithub.com\u002Fepan-utbm\u002Futbm_robocar_dataset) - 用于自动驾驶的欧盟长期多传感器数据集。\n* [DBNet](https:\u002F\u002Fgithub.com\u002Fdriving-behavior\u002FDBNet) - 用于驾驶行为学习的大规模数据集。\n* [argoverse-api](https:\u002F\u002Fgithub.com\u002Fargoai\u002Fargoverse-api) - Argoverse 数据集的官方 GitHub 仓库。\n* [DDAD](https:\u002F\u002Fgithub.com\u002FTRI-ML\u002FDDAD) - 来自 TRI（丰田研究院）的新型自动驾驶基准测试，适用于在复杂多样的城市环境中进行远距离（最远 250 米）和密集深度估计。\n* [pandaset-devkit](https:\u002F\u002Fgithub.com\u002Fscaleapi\u002Fpandaset-devkit) - Hesai 和 Scale 提供的面向自动驾驶的公开大规模数据集。\n* [a2d2_to_ros](https:\u002F\u002Fgitlab.com\u002FMaplessAI\u002Fexternal\u002Fa2d2_to_ros) - 用于将 A2D2 数据集转换为 ROS bag 文件的工具。\n* [awesome-satellite-imagery-datasets](https:\u002F\u002Fgithub.com\u002Fchrieke\u002Fawesome-satellite-imagery-datasets) - 计算机视觉和深度学习用带标注的卫星图像训练数据集列表。\n* [sentinelsat](https:\u002F\u002Fgithub.com\u002Fsentinelsat\u002Fsentinelsat) - 搜索和下载哥白尼哨兵卫星图像。\n* [adas-dataset-form](https:\u002F\u002Fwww.flir.com\u002Foem\u002Fadas\u002Fadas-dataset-form\u002F) - 用于算法训练的热成像数据集。\n* [h3d](https:\u002F\u002Fusa.honda-ri.com\u002Fh3d) - H3D 是本田提供的一个大规模全环绕 3D 多目标检测与跟踪数据集。\n* [Mapillary Vistas 数据集](https:\u002F\u002Fwww.mapillary.com\u002Fdataset\u002Fvistas) - 一个多样化的街景图像数据集，带有像素级精确且针对特定实例的人工标注，用于理解全球各地的街景。\n* [TensorFlow 数据集](https:\u002F\u002Fwww.tensorflow.org\u002Fdatasets\u002Fcatalog\u002Foverview) - TensorFlow 数据集提供了许多公共数据集，以 tf.data.Dataset 格式呈现。\n* [racetrack-database](https:\u002F\u002Fgithub.com\u002FTUMFTM\u002Fracetrack-database) - 包含来自全球超过 20 条赛道（主要为 F1 和 DTM）的中心线（x 和 y 坐标）、赛道宽度及理想行驶路线。\n* [BlenderProc](https:\u002F\u002Fgithub.com\u002FDLR-RM\u002FBlenderProc) - 一种基于程序化方法的 Blender 工作流，用于生成照片级真实的训练图像。\n* [Atlatec 样本地图数据](https:\u002F\u002Fwww.atlatec.de\u002Fgetsampledata.html) - 仅使用两台相机和 GPS，在旧金山市中心创建的用于自动驾驶和仿真的 3D 地图。\n* [Lyft Level 5 数据集](https:\u002F\u002Fself-driving.lyft.com\u002Flevel5\u002Fdata\u002F) - Level 5 正在为 Lyft 网络开发自动驾驶系统。我们正在收集和处理来自自动驾驶车队的数据，并与您共享。\n* [holicity](https:\u002F\u002Fgithub.com\u002Fzhou13\u002Fholicity) - 用于学习整体 3D 结构的城市尺度数据平台。\n* [UTD19](https:\u002F\u002Futd19.ethz.ch\u002F) - 目前公开的最大多城市交通数据集。\n* [ASTYX HIRES2019 DATASET](http:\u002F\u002Fwww.pinchofintelligence.com\u002Fvisualising-lidar-and-radar-in-virtual-reality\u002F) - 用于基于深度学习的 3D 物体检测的汽车雷达数据集。\n* [Objectron](https:\u002F\u002Fgithub.com\u002Fgoogle-research-datasets\u002FObjectron\u002F) - 一系列以物体为中心的短视频片段，附带 AR 会话元数据，包括相机姿态、稀疏点云以及周围环境平面表面的特征描述。\n* [ONCE 数据集](https:\u002F\u002Fonce-for-auto-driving.github.io\u002Findex.html) - 一个包含 2D 和 3D 物体标注的大规模自动驾驶数据集。\n\n## 脚注\n\n感谢 [xpp](http:\u002F\u002Fwiki.ros.org\u002Fxpp) 团队制作了我们使用的这张精彩 GIF。","# Awesome Robotic Tooling 快速上手指南\n\n`awesome-robotic-tooling` 并非一个单一的软体或库，而是一个**精选的工具列表资源库**。它汇集了用于专业机器人开发（C++\u002FPython）、ROS、自动驾驶及航空航天领域的开源软件和硬件工具。\n\n本指南将帮助你获取该列表，并指导你如何利用其中的资源来搭建你的机器人开发环境。\n\n## 环境准备\n\n由于这是一个文档列表而非可执行程序，对环境的要求主要取决于你计划从列表中选择的具体工具。但为了浏览和贡献该列表，你需要以下基础环境：\n\n*   **操作系统**: Linux (推荐 Ubuntu 20.04\u002F22.04), macOS 或 Windows (需配合 WSL2)。\n*   **前置依赖**:\n    *   `git`: 用于克隆仓库。\n    *   `curl` 或 `wget`: 用于下载相关脚本（可选）。\n    *   **开发语言环境**: 根据你感兴趣的方向，可能需要安装 Python (`python3-pip`) 或 C++ 构建工具 (`build-essential`, `cmake`)。\n    *   **ROS\u002FROS2**: 列表中大量工具依赖 ROS 生态，建议预先安装 [ROS Noetic](http:\u002F\u002Fwiki.ros.org\u002Fnoetic) 或 [ROS2 Humble\u002FIron](https:\u002F\u002Fdocs.ros.org\u002F)。\n\n> **国内加速建议**:\n> *   克隆 GitHub 仓库时，若速度较慢，可使用国内镜像源（如 Gitee 镜像）或配置代理。\n> *   Python 包安装请配置清华源或阿里源：`pip config set global.index-url https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple`。\n\n## 安装步骤（获取资源列表）\n\n你不需要“安装”这个列表本身，而是将其克隆到本地以便随时查阅，或者直接在网页端浏览。\n\n### 方法一：克隆仓库到本地（推荐）\n\n方便离线查阅及搜索特定工具。\n\n```bash\n# 1. 克隆仓库\ngit clone https:\u002F\u002Fgithub.com\u002Fprotontypes\u002Fawesome-robotic-tooling.git\n\n# 2. 进入目录\ncd awesome-robotic-tooling\n\n# 3. (可选) 查看目录结构\nls -l\n```\n\n### 方法二：在线浏览\n\n直接访问 GitHub 页面查看分类整理的工具列表：\n[https:\u002F\u002Fgithub.com\u002Fprotontypes\u002Fawesome-robotic-tooling](https:\u002F\u002Fgithub.com\u002Fprotontypes\u002Fawesome-robotic-tooling)\n\n## 基本使用\n\n该项目的核心用法是**按需检索**并**集成**到你自己的项目中。以下是典型的使用流程：\n\n### 1. 查找所需工具\n根据你的开发阶段，在 `README.md` 或本地文件中查找对应分类。例如：\n*   **仿真**: 查看 `Simulation` 章节 (如 Gazebo, Webots)。\n*   **感知**: 查看 `Sensor Processing` -> `Lidar and Point Cloud Processing` (如 PCL, Open3D)。\n*   **部署**: 查看 `Development Environment` -> `Build and Deploy` (如 Docker, CI\u002FCD 工具)。\n\n### 2. 集成示例：安装一个感知库\n假设你在 `Lidar and Point Cloud Processing` 章节中找到了 **Open3D**，你可以按照其官方文档进行安装和使用。\n\n**安装命令 (Python):**\n```bash\n# 使用国内源加速安装\npip install open3d -i https:\u002F\u002Fpypi.tuna.tsinghua.edu.cn\u002Fsimple\n```\n\n**最小化使用示例 (Python):**\n```python\nimport open3d as o3d\n\n# 读取点云数据\npcd = o3d.io.read_point_cloud(\"test_data\u002Fkronrod.ply\")\n\n# 可视化点云\no3d.visualization.draw_geometries([pcd])\n```\n\n### 3. 集成示例：搭建开发模板\n假设你在 `Development Environment` -> `Template` 章节找到了一个 C++ ROS 项目模板。\n\n**使用步骤:**\n```bash\n# 1. 使用 degit 或直接 git clone 模板仓库 (以常见的 catkin 模板为例)\ngit clone https:\u002F\u002Fgithub.com\u002Fprotontypes\u002Fcmake-catkin-template.git my_robot_project\n\n# 2. 进入项目\ncd my_robot_project\n\n# 3. 初始化子模块 (如果模板包含子模块)\ngit submodule update --init --recursive\n\n# 4. 编译 (假设使用 catkin_make)\ncatkin_make\n```\n\n### 4. 参与贡献\n如果你发现了新的优秀工具，可以遵循以下步骤贡献回社区：\n\n```bash\n# 1. Fork 本仓库\n# 2. 克隆你的 Fork\ngit clone https:\u002F\u002Fgithub.com\u002FYOUR_USERNAME\u002Fawesome-robotic-tooling.git\n\n# 3. 创建新分支\ngit checkout -b add-new-tool\n\n# 4. 编辑 README.md，在对应分类下添加新工具链接和描述\n# 5. 提交并推送\ngit add README.md\ngit commit -m \"Add [Tool Name] to [Category]\"\ngit push origin add-new-tool\n\n# 6. 在 GitHub 上发起 Pull Request\n```\n\n通过这种方式，`awesome-robotic-tooling` 成为了你机器人开发工具箱的“索引”，帮助你快速定位并引入业界成熟的基础设施，避免重复造轮子。","某自动驾驶初创团队正在开发一款基于 C++ 和 ROS 的物流机器人，急需构建稳定的感知与控制模块。\n\n### 没有 awesome-robotic-tooling 时\n- **重复造轮子**：工程师花费数周在 GitHub 上盲目搜索雷达点云处理和传感器校准工具，难以甄别项目质量，导致开发进度严重滞后。\n- **环境配置混乱**：缺乏统一的构建模板和依赖管理指南，不同成员的本地开发环境差异巨大，代码在各自机器上运行正常却无法集成。\n- **测试与调试困难**：缺少专业的仿真工具和链路追踪方案，团队只能在实车上反复试错，不仅效率低下，还增加了硬件损坏的安全风险。\n- **技术栈碎片化**：由于没有权威的架构设计参考，通信中间件、实时内核及数据可视化组件选型随意，系统后期维护成本极高。\n\n### 使用 awesome-robotic-tooling 后\n- **精准选型提效**：直接利用列表中经过筛选的点云处理（如 PCL 扩展）和校准工具库，将感知模块的开发周期从数周缩短至几天。\n- **标准化开发流**：采纳推荐的 C++\u002FPython 项目模板和 CI\u002FCD 部署方案，统一了团队环境，实现了代码提交即自动构建与测试。\n- **安全仿真验证**：引入清单中成熟的仿真平台和调试追踪工具，在虚拟环境中完成了 90% 的极端场景测试，大幅降低实车调试风险。\n- **系统化架构**：参考其关于通信协调、实时内核及安全要求的分类指引，构建了高内聚低耦合的系统架构，确保了软件的专业性与可扩展性。\n\nawesome-robotic-tooling 通过提供一站式的高质量工具索引，帮助团队避免了低效的重复探索，让开发者能专注于核心算法创新而非基础设施搭建。","https:\u002F\u002Foss.gittoolsai.com\u002Fimages\u002FLy0n_awesome-robotic-tooling_73b6ee19.png","Ly0n","Tobias Augspurger","https:\u002F\u002Foss.gittoolsai.com\u002Favatars\u002FLy0n_35c7e4fb.jpg","Aerospace engineer with a passion for open sustainable technology ","@open-energy-transition @protontypes","Germany, Aachen","tobias.augspurger@protontypes.eu",null,"https:\u002F\u002Fopensustain.tech\u002F","https:\u002F\u002Fgithub.com\u002FLy0n",3789,537,"2026-04-08T16:00:19","CC0-1.0",1,"Linux, macOS, Windows","未说明",{"notes":90,"python":88,"dependencies":91},"该项目是一个机器人开发工具的精选列表（Awesome List），而非单一的可执行软件工具。它涵盖了通信、文档、仿真、传感器处理等多个领域的开源工具推荐。具体的运行环境需求（如操作系统版本、GPU、内存、Python 版本等）取决于列表中用户选择使用的具体子工具。部分工具支持 Docker 部署，部分工具涉及 C++ 编译或特定的 ROS 版本依赖。",[92,93,94],"ROS","C++","Python",[96,14,13],"其他",[98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],"ros","robotics","python","cplusplus","ros2","robot","awesome-list","awesome","slam","machine-learning","point-cloud","cpp","self-driving-car","autonomous-driving","aerospace","robotic","automotive","lidar","artificial-intelligence","mapping","2026-03-27T02:49:30.150509","2026-04-10T22:21:34.298550",[],[]]