In October 2021, we introduced that we acquired the MuJoCo physics simulator, and made it freely out there for everybody to help analysis all over the place. We additionally dedicated to growing and sustaining MuJoCo as a free, open-source, community-driven venture with best-in-class capabilities. Immediately, 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 superb platform for open-source collaboration and share a preview of our roadmap going ahead.
A platform for collaboration
Physics simulators are vital instruments in trendy robotics analysis and infrequently fall into these two classes:
- Closed-source, business software program.
- Open-source software program, typically 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 typically has a smaller consumer base and suffers when its builders and maintainers graduate.
MuJoCo is among 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 significantly enticing for collaboration are:
- Full-featured simulator that may mannequin complicated 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 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 could be very quick. Sadly, uncooked physics pace has traditionally been hindered by Python wrappers, which made batched, multi-threaded operations non-performant because of the presence of the International Interpreter Lock (GIL) and non-compiled code. In our roadmap beneath, we tackle this problem going ahead.
For now, we’d wish to share some benchmarking outcomes for 2 widespread fashions. The outcomes have been obtained on a normal AMD Ryzen 9 5950X machine, working Home windows 10.
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 inner reminiscence administration.
- New incremental compiler with higher mannequin composability.
- Help for higher rendering by way of Unity integration.
- Native help for physics derivatives, each analytical and finite-differenced.
Be taught extra
Useful assets about MuJoCo:
We look ahead to receiving your contributions!