Demonstrating MuJoCo Playground
We introduce MuJoCo Playground, a fully opensource framework for robot learning built with MJX, with the express goal of streamlining simulation, training, and simto-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.
Authors
- Yuval Tassa (ORCID: https://orcid.org/0000-0002-1197-288X)
- Qiayuan Liao
- Kevin Zakka
- Carmelo Sferrazza (ORCID: https://orcid.org/0000-0002-7432-7634)
- Lüder A. Kahrs (ORCID: https://orcid.org/0000-0001-5506-2768)
- Baruch Tabanpour
- Pieter Abbeel
- Koushil Sreenath (ORCID: https://orcid.org/0000-0002-5346-3637)
- Erik Frey
- Mustafa Haiderbhai (ORCID: https://orcid.org/0000-0002-0443-0118)
- Samuel Holt
- Jing Yuan Luo
- Arthur Allshire
Publication Details
- Published
- 2025-06-21
- DOI
- https://doi.org/10.15607/rss.2025.xxi.020
- Citations
- 3
- Primary Topic
- Digital Games and Media
- Type
- article
- Field-Weighted Citation Impact
- 12.60