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Open-sourcing MuJoCo


In October 2021, we introduced that we acquired the MuJoCo physics simulator, and made it freely obtainable for everybody to assist analysis in all places. We additionally dedicated to creating and sustaining MuJoCo as a free, open-source, community-driven mission with best-in-class capabilities. At present, we’re thrilled to report that open sourcing is full and the complete codebase is on GitHub

Right here, we clarify why MuJoCo is a good platform for open-source collaboration and share a preview of our roadmap going ahead.

A platform for collaboration

Physics simulators are important instruments in trendy robotics analysis and sometimes fall into these two classes: 

  1. Closed-source, industrial software program.
  2. Open-source software program, typically created in academia. 

The primary class is opaque to the person, and though generally free to make use of, can’t be modified and is difficult to know. The second class typically has a smaller person base and suffers when its builders and maintainers graduate.

MuJoCo is without doubt one of the few full-featured simulators backed by a longtime firm, which is really open supply. As a research-driven organisation, we view MuJoCo as a platform for collaboration, the place roboticists and engineers can be part of us to develop one of many world’s finest robotic simulators.

Options that make MuJoCo notably engaging for collaboration are:

  • Full-featured simulator that may model complex mechanisms
  • Readable, performant, moveable code.
  • Simply extensible codebase.
  • Detailed documentation: each user-facing and code feedback.

We hope that colleagues throughout academia and the OSS group profit from this platform and contribute to the codebase, enhancing analysis for everybody.

Efficiency

As a C library with no dynamic reminiscence allocation, MuJoCo may be very quick. Sadly, uncooked physics pace has traditionally been hindered by Python wrappers, which made batched, multi-threaded operations non-performant as a result of presence of the World Interpreter Lock (GIL) and non-compiled code. In our roadmap beneath, we handle this situation going ahead. 

For now, we’d wish to share some benchmarking outcomes for 2 widespread fashions. The outcomes have been obtained on a regular AMD Ryzen 9 5950X machine, operating Home windows 10.

These values have been obtained from our testspeed sample code. Notably, management noise is injected into the actuators stopping the system from settling into a hard and fast state, and are due to this fact consultant of real-world efficiency.

Roadmap

Right here’s our near-term roadmap for MuJoCo:

  • Unlock MuJoCo’s pace potential with batched, multi-threaded simulation.
  • Help bigger scenes with enhancements to inside reminiscence administration.
  • New incremental compiler with higher mannequin composability.
  • Help for higher rendering by way of Unity integration.
  • Native assist for physics derivatives, each analytical and finite-differenced.

Be taught extra

Useful sources about MuJoCo:

We sit up for receiving your contributions!


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