DeepMind’s Open Source MuJoCo Is Available On GitHub


DeepMind, an Alphabet subsidiary and AI research lab, acquired the MuJoCo physics engine for robotics research and development in October 2021. The simulator was to be open-sourced and maintained as a free, open source, community-driven project. DeepMind claims that the open sourcing is now complete, with the entire codebase available on GitHub.

MuJoCo, which stands for Multi-Joint Dynamics with Contact, is a physics engine designed to aid research and development in robotics, biomechanics, graphics and animation, and other fields that require fast and accurate simulation. MuJoCo can be used to implement model-based computations for machine learning applications such as control synthesis, state estimation, system identification, mechanism design, data analysis through inverse dynamics, and parallel sampling. It can also be used as a standard simulator, such as for gaming and interactive virtual environments.

According to DeepMind, the following are some of the features that make MuJoCo appealing for collaboration:

  • Comprehensive simulator capable of simulating complex mechanisms
  • Readable, performant, portable code
  • Codebase that is easily extensible
  • Extensive documentation, including both user-facing and code comments – We hope that colleagues from academia and the OSS community will use this platform and contribute to the codebase, thereby improving research for all.

DeepMind has more to say:

“As a C library with no dynamic memory allocation, MuJoCo is very fast. Unfortunately, raw physics speed has historically been hindered by Python wrappers, which made batched, multi-threaded operations non-performant due to the presence of the Global Interpreter Lock (GIL) and non-compiled code. In our roadmap below, we address this issue going forward.

“For now, we’d like to share some benchmarking results for two common models. The results were obtained on a standard AMD Ryzen 9 5950X machine, running Windows 10.”


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