In October 2021, we introduced that we acquired the MuJoCo physics simulator, and made it freely obtainable for everybody to help analysis all over the place. We additionally dedicated to creating and sustaining MuJoCo as a free, open-source, community-driven mission with best-in-class capabilities. As we speak, we’re thrilled to report that open sourcing is full and your 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 essential instruments in fashionable robotics analysis and sometimes fall into these two classes:
- Closed-source, business software program.
- Open-source software program, usually created in academia.
The primary class is opaque to the consumer, and though generally free to make use of, can’t be modified and is tough to grasp. The second class usually has a smaller consumer 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 a part of us to develop one of many world’s finest robotic simulators.
Options that make MuJoCo significantly enticing for collaboration are:
- Full-featured simulator that may model complex 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.
Efficiency
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 because of the presence of the World Interpreter Lock (GIL) and non-compiled code. In our roadmap under, we handle this concern going ahead.
For now, we’d wish to share some benchmarking outcomes for 2 widespread fashions. The outcomes had been obtained on an ordinary AMD Ryzen 9 5950X machine, operating Home windows 10.
Roadmap
Right here’s our near-term roadmap for MuJoCo:
- Unlock MuJoCo’s velocity potential with batched, multi-threaded simulation.
- Assist bigger scenes with enhancements to inside reminiscence administration.
- New incremental compiler with higher mannequin composability.
- Assist for higher rendering through Unity integration.
- Native help for physics derivatives, each analytical and finite-differenced.
Study extra
Useful assets about MuJoCo:
We stay up for receiving your contributions!
