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Awesome-Embodied-AI-Robot

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🤖 RoboLLM Hub | A curated collection of embodied AI and robot learning resources.具身智能与机器人学习资源集合，包含最新论文、代码与工具。👉

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- - deploy_docs.yml
  - sync_docs.yml
  - weekly_update.yml
- logo.svg
- - language_switcher.html
- - default.html
  - theme.html
- _config.yml
- environment_perception.md
- environment_perception_cn.md
- fundamental_theory.md
- fundamental_theory_cn.md
- index.md
- index_cn.md
- index_en.md
- motion_planning.md
- motion_planning_cn.md
- multimodal_interaction.md
- multimodal_interaction_cn.md
- robot_learning_and_reinforcement_learning.md
- robot_learning_and_reinforcement_learning_cn.md
- simulation_platforms.md
- simulation_platforms_cn.md
- task_planning.md
- task_planning_cn.md
- README.md
- README_CN.md
- README.md
- README_CN.md
- README.md
- README_CN.md
- README.md
- README_CN.md
- README.md
- README_CN.md
- sync_docs.py
- README.md
- README_CN.md
- README.md
- README_CN.md
README.md
README_CN.md
requirements.txt
update_papers.py

# Installation Guide

1. Get the code

git clone https://github.com/GlimmerLab/Awesome-Embodied-AI-Robot

Downloads the entire project code from GitHub to your computer.

cd Awesome-Embodied-AI-Robot

Moves into the project folder you just downloaded.

2. Python

Easy Recommended

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install -r requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

python <실행할 파일명>.py # README에서 정확한 실행 파일명을 확인하세요

Runs the Python script (or module).

✅ If it runs without errors and prints output in the terminal, it worked.

// repository documentation

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# Embodied AI Research Resources

<div align='center'>
  <img src="assets/logo.svg" width=250px >
</div>

<div align='center'>
  <img src="https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg" >
  <img src="https://img.shields.io/badge/License-MIT-turquoise.svg" >
  <img src="https://img.shields.io/badge/PRs-Welcome-brightgreen.svg" >
  <a href="README_CN.md">中文</a>
</div>

> 🌐 Language: [English](README.md) | [中文](README_CN.md)

This repository collects research resources in the field of Embodied AI, including papers, code implementations, and datasets. Embodied AI studies how robots can learn and accomplish tasks through interaction with the environment, which is an important intersection of artificial intelligence and robotics.

## Domain Relationships

Embodied AI research involves multiple interconnected domains:

- **Fundamental Theory**: Provides theoretical foundations for embodied AI, including cognitive science and control theory
- **Robot Learning & Reinforcement Learning**: Enables autonomous learning and decision-making capabilities for robots
- **Environment Perception**: Enables robots to understand and adapt to their environment, including visual language understanding
- **Motion Planning & Task Planning**: Implements robot action execution and task decomposition
- **Multimodal Interaction**: Supports multimodal interaction between robots and environment/humans
- **Simulation Platforms**: Provides virtual environments for robot learning and testing

## 📖 Contents

* [Fundamental Theory](Fundamental-Theory/README.md)
* [Robot Learning & Reinforcement Learning](Robot-Learning-and-Reinforcement-Learning/README.md)
* [Environment Perception](Environment-Perception/README.md)
* [Motion Planning](Motion-Planning/README.md)
* [Task Planning](Task-Planning/README.md)
* [Multimodal Interaction](Multimodal-Interaction/README.md)
* [Simulation Platforms](Simulation-Platforms/README.md)

## Statistics

- Total Papers: 6223
- Code Implementations: 6205

## Citation

If you use this repository in your research, please cite:

```BibTeX
@misc{Awesome-Embodied-AI@2025,
  title={Awesome-Embodied-AI: A curated list of Awesome Embodied AI Papers with codes},
  url={https://github.com/GlimmerLab/Awesome-Embodied-AI},
  author={GlimmerLab etc},
  year={2025}
}
```

## Contributing

We welcome new research resources! Please ensure:

1. Resources have high academic or practical value
2. Complete paper links and code repositories are provided (if available)
3. Resources are added to appropriate directories following the existing format
4. Statistics are updated accordingly

## License

This project is licensed under the [MIT License](LICENSE).

## 🎯Features

- 📚 Comprehensive paper collection
- 💻 Open source implementations
- 🔍 Detailed categorization
- 🌟 Important paper recommendations
- 📅 Regular updates

## 🌟Acknowledgments

Thanks to all researchers and developers who have contributed to this project!

## 📬Contact

- Project Maintainer: [GlimmerLab](junli440883@gmail.com)
- Project Homepage: [GitHub](https://github.com/GlimmerLab/Awesome-Embodied-AI)

## 🌟Contributors

Thanks to all our contributors:

<a href="https://github.com/GlimmerLab/Awesome-Embodied-AI/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=GlimmerLab/Awesome-Embodied-AI" />
</a>

Made with [contrib.rocks](https://contrib.rocks).

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