DeepMind’s Open Source MuJoCo Is Available On GitHub

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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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