Fast, accurate physics engine for contact-rich robotics: soft-contact convex solver trusted for manipulation and locomotion research, with MJX (JAX) for massively parallel GPU/TPU simulation — Apache-2.0 since DeepMind open-sourced it.
Fast, accurate physics engine for contact-rich robotics: soft-contact convex solver trusted for manipulation and locomotion research, with MJX (JAX) for massively parallel GPU/TPU simulation — Apache-2.0 since DeepMind open-sourced it.
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MuJoCo (Multi-Joint dynamics with Contact) is a physics engine purpose-built for fast, accurate simulation of articulated systems in contact — the property that made it the default for manipulation, locomotion and reinforcement-learning research. Its convex soft-contact model delivers stable, differentiable-friendly dynamics; models are described in MJCF XML; and MJX reimplements the pipeline in JAX for thousands of parallel environments on GPU/TPU. Acquired and open-sourced by DeepMind (Apache-2.0) in 2022, it is under active development (3.x line) with Python bindings, interactive viewer, and the Menagerie library of validated robot models.
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