MJLab Adaptor

This repository contains a UniEnv adaptor for mjlab.

Installation

pip install unienv_mjlab

Usage

import mjlab.tasks
from mjlab.envs import ManagerBasedRlEnv
from mjlab.tasks.registry import load_env_cfg

from unienv_mjlab import FromMJLabEnv

cfg = load_env_cfg("Mjlab-Velocity-Flat-Unitree-G1")
cfg.scene.num_envs = 4

mjlab_env = ManagerBasedRlEnv(cfg=cfg, device="cpu", render_mode=None)
env = FromMJLabEnv(mjlab_env)

ctx, obs, info = env.reset(seed=0)
for _ in range(10):
    action = env.sample_action()
    obs, reward, terminated, truncated, info = env.step(action)

Notes

• mjlab environments are vectorized by default.
• mjlab.step() auto-resets done environments before returning observations. This means that you don't need to call reset() after an episode ends.