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HomeRoboticsDeepMind's open-source model of MuJoCo accessible on GitHub

DeepMind’s open-source model of MuJoCo accessible on GitHub


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The Shadow hand from Open AI was constructed partially utilizing the MuJoCo physics engine. | Credit score: OpenAI

DeepMind, an AI analysis lab and subsidiary of Alphabet, in October 2021 acquired the MuJoCo physics engine for robotics analysis and improvement. The plan was to open-source the simulator and keep it as a free, open-source, community-driven mission. In line with DeepMind, the open sourcing is now full, and your entire codebase is on GitHub.

MuJoCo, which stands for Multi-Joint Dynamics with Contact, is a physics engine that goals to facilitate R&D in robotics, biomechanics, graphics and animation, and different areas the place quick and correct simulation is required. MuJoCo can be utilized to implement model-based computations resembling management synthesis, state estimation, system identification, mechanism design, knowledge evaluation by means of inverse dynamics, and parallel sampling for machine studying functions. It will also be used as a extra conventional simulator, together with for gaming and interactive digital environments.

DeepMind stated the next are a few of the options that make MuJoCo enticing for collaboration:

  • Full-featured simulator that may mannequin advanced mechanisms
  • Readable, performant, transportable code
  • Simply extensible codebase
  • Detailed documentation: each user-facing and code feedback
  • We hope that colleagues throughout academia and the OSS neighborhood profit from this platform and contribute to the codebase, enhancing analysis for everybody.

Right here is extra from DeepMind:

“As a C library with no dynamic reminiscence allocation, MuJoCo may be very quick. Sadly, uncooked physics velocity has traditionally been hindered by Python wrappers, which made batched, multi-threaded operations non-performant as a result of presence of the International Interpreter Lock (GIL) and non-compiled code. In our roadmap beneath, we deal with this subject 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, working Home windows 10.”

As for the near-term roadmap, DeepMind stated it should unlock MuJoCo’s velocity potential with batched, multi-threaded simulation, help bigger scenes with enhancements to inner reminiscence administration and introduce a brand new incremental compiler with higher mannequin composability. DeepMind additionally stated it should construct out help for higher rendering by way of Unity integration and add native help for physics derivatives, each analytical and finite-differenced.

Earlier than the acquisition, DeepMind used MuJoCo as a simulation platform for varied initiatives, largely by way of its dm_control Python stack. It highlighted just a few robotics examples, which you’ll watch by way of the playlist beneath.



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