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README.md
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<h1 align="center">具身智能中文指南（12月15日前将完善）</h1>
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<p align="center">【 <a href="https://github.com/tianxingchen/Embodied-AI-Guide">Github Repo</a>, Latest Update: Sep 1, 2024 】 <img src="https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2Ftianxingchen%2FEmbodied-AI-Guide&count_bg=%232B8DD9&title_bg=%237834C6&icon=github.svg&icon_color=%23E7E7E7&title=Page+Viewers&edge_flat=false"/></a></p>
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<p align="center">【 <a href="https://github.com/tianxingchen/Embodied-AI-Guide">Github Repo</a>, Latest Update: Nov 30, 2024 】 <img src="https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2Ftianxingchen%2FEmbodied-AI-Guide&count_bg=%232B8DD9&title_bg=%237834C6&icon=github.svg&icon_color=%23E7E7E7&title=Page+Viewers&edge_flat=false"/></a></p>
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<p><b>🦉Contributors</b>: <a href="https://tianxingchen.github.io">陈天行 (25' 港大PhD)</a>, <a href="https://yudezou.github.io/">邹誉德 (25' 上交-浦江实验室联培PhD)</a>, <a href="">陈思翔 (25' 北大PhD)</a>, <a href="https://github.com/27yw">叶雯 (25' 中科院自动化所PhD)</a>, <a href="https://github.com/zanxinchen">陈攒鑫 (深大本科生)</a>, <a href="https://github.com/ShijiaPeng03">彭时佳 (深大本科生)</a></p>
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> Embodied AI (具身智能)入门的路径以及useful信息的总结，期望是按照路线走完后，新手可以快速建立关于这个领域的认知，希望能帮助到各位入门具身智能的朋友,欢迎star与PR🌟~<br>文章中引用文章的原作者，我们在[🙏 Acknowledgement - 致谢](#acknowledgement)部分进行了致谢，感谢他们的分享🌹<br><a href="https://hits.seeyoufarm.com">
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# Contents - 目录
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## Contents - 目录
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<nav>
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<ul>
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<li><a href="#start">Start Up - 从这里开始</a></li>
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<section id="start"></section>
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# Start Up - 从这里开始
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## Start Up - 从这里开始
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**什么是具身智能？**<br>
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具身智能是指一种基于物理身体进行感知和行动的智能系统，其通过智能体与环境的交互获取信息、理解问题、做出决策并实现行动，从而产生智能行为和适应性。
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<section id="rl"></section>
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# Reinforcement Learning - 强化学习
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## Reinforcement Learning - 强化学习
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UCB CS285 深度强化学习: [website](https://rail.eecs.berkeley.edu/deeprlcourse/) | [youtube](https://www.youtube.com/playlist?list=PL_iWQOsE6TfVYGEGiAOMaOzzv41Jfm_Ps)<br>
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台湾大学李宏毅公开课: [bilibili](https://www.bilibili.com/video/BV1XP4y1d7Bk/?spm_id_from=333.337.search-card.all.click&vd_source=ab9cf5374617c2867aaea34af29b53c9)<br>
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EasyRL - 蘑菇书: [website](https://datawhalechina.github.io/easy-rl/#/)<br>
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@ -41,13 +41,13 @@ EasyRL - 蘑菇书: [website](https://datawhalechina.github.io/easy-rl/#/)<br>
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<section id="il"></section>
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# Imitation Learning - 模仿学习
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## Imitation Learning - 模仿学习
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模仿学习简洁教程 - 南京大学LAMDA: [PDF](https://www.lamda.nju.edu.cn/xut/Imitation_Learning.pdf)<br>
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Supervised Policy Learning for Real Robots, RSS 2024 Workshop 教程：真实机器人的监督策略学习, [bilibili](https://www.bilibili.com/video/BV1Fx4y1s7if/?buvid=XY415384A771A6C681C9BEB3817566ED57724&is_story_h5=false&mid=ORgXkVzTHaOKTsml0RX5Gw%3D%3D&plat_id=240&share_from=ugc&share_medium=android&share_plat=android&share_source=WEIXIN&share_tag=s_i&spmid=dt.space-dt.0.0×tamp=1721464513&unique_k=Cqj5d9J&up_id=2185804&vd_source=ab9cf5374617c2867aaea34af29b53c9)
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<section id="llm_robot"></section>
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# LLM for Robotics - 大模型在机器人学中的应用
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## LLM for Robotics - 大模型在机器人学中的应用
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Robotics+LLM系列通过大语言模型控制机器人 [2]: [zhihu](https://zhuanlan.zhihu.com/p/668053911)<br>
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PDDL-wiki: [website](https://planning.wiki/)<br>
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An Introduction to PDDL: [PDF](https://www.cs.toronto.edu/~sheila/2542/s14/A1/introtopddl2.pdf)<br>
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@ -59,17 +59,17 @@ Lilian Weng 个人博客 - AI Agent 系统综述 [5]: 中文: [website](https://
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<section id="3dv"></section>
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# 3D Vision - 三维视觉
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## 3D Vision - 三维视觉
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三维视觉导论 - Andreas Geiger: [website](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/autonomous-vision/lectures/computer-vision/)<br>
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GAMES203 - 三维重建和理解: [bilibili](https://www.bilibili.com/video/BV1pw411d7aS/?share_source=copy_web&vd_source=0b7603f37af6d369a97df34525b149be)<br>
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Advances in 3D pre-training and downstream tasks: a survey. [PDF](https://link.springer.com/content/pdf/10.1007/s44336-024-00007-4.pdf)<br>
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## 3DGS
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### 3DGS
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3D Gaussian Splatting原理速通: [bilibili](https://www.bilibili.com/video/BV11e411n79b/?spm_id_from=333.788&vd_source=ab9cf5374617c2867aaea34af29b53c9)
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<section id="control"></section>
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# Control - 控制学
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## Control - 控制学
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彻底搞懂阻抗控制、导纳控制、力位混合控制: [CSDN](https://blog.csdn.net/a735148617/article/details/108564836)<br>
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具身智能ROS1基础: [website](http://www.autolabor.com.cn/book/ROSTutorials/)<br>
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具身智能ROS2基础: [website](https://zhangzhiwei-zzw.github.io/ROS2%E5%AD%A6%E4%B9%A0/ROS2/)<br>
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<section id="benchmarks"></section>
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# Benchmarks & Simulators - 基准 & 仿真器
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## Benchmarks & Simulators - 基准 & 仿真器
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具身智能常用benchmark总结 [1]: [zhihu](https://zhuanlan.zhihu.com/p/695342864)<br>
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常见仿真器wiki: [wiki](https://simulately.wiki/)
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| 仿真器 | 基准 |
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<section id="info"></section>
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# Useful Info - 有利于搭建认知的资料
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## Useful Info - 有利于搭建认知的资料
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具身智能基础技术路线-YunlongDong [2]: [PDF](./files/具身智能基础技术路线-YunlongDong.pdf), [bilibili](https://www.bilibili.com/video/BV1d5ukedEsi/?buvid=XXCD799C01878A6CFDECF3FB4427E2F070877&from_spmid=default-value&is_story_h5=false&mid=iWFclAyh36UYMh2G6ZcsDw%3D%3D&p=1&plat_id=114&share_from=ugc&share_medium=android&share_plat=android&share_session_id=9c0dccf5-ec0b-4369-8b89-ff1d848467ee&share_source=WEIXIN&share_tag=s_i&spmid=united.player-video-detail.0.0×tamp=1716466406&unique_k=Q0CaIUj&up_id=249218043)
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AI领域值得关注的博主列表 [3]: [zhihu](https://zhuanlan.zhihu.com/p/682110383)
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<section id="communities"></section>
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# Communities - 社区
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## Communities - 社区
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DeepTimber Robotics Innovations Community, 深木科研交流社区: [website](https://gamma.app/public/DeepTimber-Robotics-Innovations-Community-A-Community-for-Multi-m-og0uv8mswl1a3q7?mode=doc)
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<section id="acknowledgement"></section>
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<section id="companies"></section>
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# Companies - 公司
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## Companies - 公司
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松灵AgileX: [website](https://www.agilex.ai/)<br>
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宇树Unitree: [website](https://www.unitree.com/cn)<br>
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# 🙏 Acknowledgement - 致谢
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## 🙏 Acknowledgement - 致谢
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本文转载/引用了大量博主的文章，我们对他们的知识分享表示感谢，引用列表如下：
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| Since 2024 🌹 | | | |
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|------|------|------|------|
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| [1] 知乎[穆尧](https://www.zhihu.com/people/mu-yao-12-34) | [2] 知乎[东林钟声](https://www.zhihu.com/people/dong-lin-zhong-sheng-76), Github[Yunlong Dong](https://github.com/yunlongdong) | [3] 知乎[强化学徒](https://www.zhihu.com/people/heda-he-28) | [4] 知乎[Biang哥](https://www.zhihu.com/people/qi-da-guang) | [5] OpenAI [Lilian Weng](https://lilianweng.github.io/) |
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# 🏷️ License - 许可证
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## 🏷️ License - 许可证
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This repository is released under the MIT license. See LICENSE for additional details.
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