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Unitree RL Lab

IsaacSim Isaac Lab License

Overview

This project provides a set of reinforcement learning environments for Unitree robots, built on top of IsaacLab.

Currently supports Unitree Go2, H1 and G1-29dof robots.

Isaac Lab
Mujoco
Physical

Installation

  • Install Isaac Lab by following the installation guide.

  • Install the Unitree RL IsaacLab standalone environments.

    • Clone or copy this repository separately from the Isaac Lab installation (i.e. outside the IsaacLab directory):

      git clone https://github.com/unitreerobotics/unitree_rl_lab.git
    • Use a python interpreter that has Isaac Lab installed, install the library in editable mode using:

      conda activate env_isaaclab
      python -m pip install -e source/unitree_rl_lab
  • Download unitree usd files

    • Download unitree usd files from unitree_model, keeping folder structure

      git clone https://huggingface.co/datasets/unitreerobotics/unitree_model
    • Config UNITREE_MODEL_DIR in source/unitree_rl_lab/unitree_rl_lab/assets/robots/unitree.py.

      UNITREE_MODEL_DIR = "</home/user/projects/unitree_usd>"
  • Verify that the environments are correctly installed by:

    • Listing the available tasks:

      python scripts/list_envs.py
    • Running a task:

      python scripts/rsl_rl/train.py --headless --task Unitree-G1-29dof-Velocity
    • Inference with a trained agent:

      python scripts/rsl_rl/play.py --task Unitree-G1-29dof-Velocity

Deploy

After the model training is completed, we need to perform sim2sim on the trained strategy in Mujoco to test the performance of the model. Then deploy sim2real.

Setup

# Install dependencies
sudo apt install -y libyaml-cpp-dev libboost-all-dev libeigen3-dev libspdlog-dev
# Install unitree_sdk2
git clone [email protected]:unitreerobotics/unitree_sdk2.git
cd unitree_sdk2
mkdir build && cd build
cmake .. -DBUILD_EXAMPLES=OFF # Install on the /usr/local directory
sudo make install
# Compile the robot_controller
cd deploy/robots/g1_29dof # or other robots
mkdir build && cd build
cmake .. && make

Sim2Sim

Installing the unitree_mujoco.

  • Set the robot at /simulate/config.yaml to g1
  • Set domain_id to 0
  • Set enable_elastic_hand to 1
  • Set use_joystck to 1.
# start simulation
cd unitree_mujoco/simulate/build
./unitree_mujoco
cd unitree_rl_lab/deploy/robots/g1_29dof/build
./g1_ctrl
# 1. press [L2 + Up] to set the robot to stand up
# 2. Click the mujoco window, and then press 8 to make the robot feet touch the ground.
# 3. Press [R1 + X] to run the policy.
# 4. Click the mujoco window, and then press 9 to disable the elastic band.

Sim2Real

You can use this program to control the robot directly, but make sure the on-borad control program has been closed.

./g1_ctrl --network eth0 # eth0 is the network interface name.

Acknowledgements

This repository is built upon the support and contributions of the following open-source projects. Special thanks to:

  • IsaacLab: The foundation for training and running codes.
  • mujoco: Providing powerful simulation functionalities.
  • robot_lab: Referenced for project structure and parts of the implementation.

About

This is a repository for reinforcement learning implementation for Unitree robots, based on IsaacLab.

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