tfgbestneal / parkour

[CoRL 2023] Robot Parkour Learning

Home Page:https://robot-parkour.github.io

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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

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

TODO

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 pipeline in simulation
  • 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}
}

About

[CoRL 2023] Robot Parkour Learning

https://robot-parkour.github.io

License:MIT License


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