Mujoco Playground

A simple and efficient library for training humanoid locomotion in MJX and MuJoCo.

Getting Started

Clone our Mujoco Playground repository:

git clone https://github.com/kscalelabs/mujoco_playground.git
cd mujoco_playground

Install the package:

pip install -e .

Running ZBot experiments

You can train a standing policy within 20 min on RTX 4090

python playground/runner.py --env ZbotJoystickFlatTerrain

You can inpect the training performance through the reward plot or videos of evaluated policy.

If you have access to Google Colab you can try running the notebook:

ipython playground/.ipynb

Evaluation (WIP)

You can inspect the training results through the output.mp4 file or running sim2sim evaluation through

python sim2sim.py --model_path 

🚧

Sim2Real pipeline WIP