Robot Parkour Learning

Project website: https://robot-parkour.github.io/
Authors: Ziwen Zhuang*, Zipeng Fu*, Jianren Wang, Christopher Atkeson, Sören Schwertfeger, Chelsea Finn, Hang Zhao
Conference on Robot Learning (CoRL) 2023, Oral, Best Systems Paper Award Finalist (top 3)

Repository Structure

• legged_gym: contains the isaacgym environment and config files.
  • legged_gym/legged_gym/envs/a1/: contains all the training config files.
  • legged_gym/legged_gym/envs/base/: contains all the environment implementation.
  • legged_gym/legged_gym/utils/terrain/: contains the terrain generation code.
• rsl_rl: contains the network module and algorithm implementation. You can copy this folder directly to your robot.
  • rsl_rl/rsl_rl/algorithms/: contains the algorithm implementation.
  • rsl_rl/rsl_rl/modules/: contains the network module implementation.

Training in Simulation

To install and run the code for training A1 in simulation, please clone this repository and follow the instructions in legged_gym/README.md.

Hardware Deployment

To deploy the trained model on your real robot, please follow the instructions in Deploy.md.

Trouble Shooting

If you cannot run the distillation part or all graphics computing goes to GPU 0 dispite you have multiple GPUs and have set the CUDA_VISIBLE_DEVICES, please use docker to isolate each GPU.

To Do (will be done before Nov 2023)

• Go1 training configuration (not from scratch)
• A1 deployment code
• Go1 deployment code

Citation

If you find this project helpful to your research, please consider cite us! This is really important to us.

@inproceedings{
    zhuang2023robot,
    title={Robot Parkour Learning},
    author={Ziwen Zhuang and Zipeng Fu and Jianren Wang and Christopher G Atkeson and S{\"o}ren Schwertfeger and Chelsea Finn and Hang Zhao},
    booktitle={Conference on Robot Learning {CoRL}},
    year={2023}
}