Robotics: Science and Systems XXI

Demonstrating MuJoCo Playground

Kevin Zakka, Baruch Tabanpour, Qiayuan Liao, Mustafa Haiderbhai, Samuel Holt, Jing Yuan Luo, Arthur Allshire, Erik Frey, Koushil Sreenath, Lueder Alexander Kahrs, Carmelo Sferrazza, Yuval Tassa, Pieter Abbeel

Abstract:

We introduce MuJoCo Playground, a fully open-source framework for robot learning built with MJX, with the express goal of streamlining simulation, training, and sim-to-real transfer onto robots. With a simple 'pip install playground', researchers can train policies in minutes on a single GPU. Playground supports diverse robotic platforms, including quadrupeds, humanoids, dexterous hands, and robotic arms, enabling zero-shot sim-to-real transfer from both state and pixel inputs. This is achieved through an integrated stack comprising a physics engine, batch renderer, and training environments. Along with video results, the entire framework is freely available at playground.mujoco.org.

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Bibtex:

  
@INPROCEEDINGS{ZakkaK-RSS-25, 
    AUTHOR    = {Kevin Zakka AND Baruch Tabanpour AND Qiayuan Liao AND Mustafa Haiderbhai AND Samuel Holt AND Jing Yuan Luo AND Arthur Allshire AND Erik Frey AND Koushil Sreenath AND Lueder Alexander Kahrs AND Carmelo Sferrazza AND Yuval Tassa AND Pieter Abbeel}, 
    TITLE     = {{Demonstrating MuJoCo Playground}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2025}, 
    ADDRESS   = {LosAngeles, CA, USA}, 
    MONTH     = {June}, 
    DOI       = {10.15607/RSS.2025.XXI.020} 
}