/awesome-isaac-gym

A curated list of awesome NVIDIA Issac Gym frameworks, papers, software, and resources

Awesome NVIDIA Isaac Gym 🤖

Awesome

A curated collection of resources related to NVIDIA Isaac Gym, a high-performance GPU-based physics simulation environment for robot learning.

🎯 Quick Links


📋 Contents


🚀 Latest Releases


🎓 Getting Started

  1. Installation & Setup

  2. Basic Concepts

📚 Official Resources

Core Documentation

Learning Resources

📖 Learning Materials

Tutorials

Comprehensive tutorial series from RSS 2021 Workshop:

  1. Introduction & Getting Started
  2. Environments, Training & Tips
  3. Academic Labs Series:
  4. New Frontiers in GPU Accelerated RL

Video Guides

Locomotion

  • [RSS2024] Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion: paper, code

  • [RSS2022] Rapid Locomotion via Reinforcement Learning: paper, openreview, code

  • [CoRL2021] Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning: paper, openreview, code, project

  • [ICRA2021] Dynamics Randomization Revisited:A Case Study for Quadrupedal Locomotion: project, paper, video

  • [2021] GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model: project, paper

  • [CoRL2020] Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion: paper, video, project, blog

  • [RAL2021] Learning a State Representation and Navigation in Cluttered and Dynamic Environments: paper

  • HumanoidVerse: A Multi-simulator Framework for Humanoid Robot Learning (2024)

    • Features multi-simulator support (Isaac Gym, Flex, MuJoCo)
    • Includes diverse humanoid models and environments
    • Provides comprehensive benchmarking tools
    • Enables efficient parallel training across simulators
  • HIMLoco: Hierarchical Imitation Learning for Robust Humanoid Locomotion (2024)

    • Paper
    • Features hierarchical imitation learning framework
    • Enables robust humanoid locomotion in challenging environments
    • Demonstrates successful real-world deployment
  • ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills (2025)

    • Paper
    • Features two-stage framework for sim-to-real transfer
    • Enables highly agile humanoid motions like kicks and jumps
    • Successfully deployed on real Unitree G1 humanoid robot
    • Demonstrates significant improvement over SysID and DR baselines

Blogs


📑 Research Papers

Core Papers

Robot Manipulation

Localization & Control

Others

🛠 Tools & Libraries

RL Frameworks

Related GitHub Repos

Community Projects


Conference Sessions and Talks


🌟 Contributing

Contributions are welcome! Please read our contribution guidelines before submitting a pull request.

📄 License

This repository is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Special thanks to all contributors and the NVIDIA Isaac team for making these resources available to the robotics community.