Not sure why this is hitting the home page right now but people may also be interested in Mujoco Playground [1] which is the latest RL environment wrapper of mujoco, implementing both classic deepmind-control benchmarks, and some very new interesting ones!

[1] https://playground.mujoco.org/

MuJoCo is great. I have it running in the browser for robotics simulation. See for example https://visibot.com/sheet/examples/humanoid_walking.v

This is what StuffMadeHere used in his latest video to simulate a mini-golf course! https://www.youtube.com/watch?v=2OfjZ3ORJfc&t=368s

The physics engine I'm using is called MuJoCo. And if you're wondering why I didn't write my own physics engine, it's basically because I don't have 20 years.

We are using MuJoCo to train a G1 humanoid robot right now. The best thing is that we do not need to fight with NVIDIA software and that it runs on macOS.

PS: I just finished a first draft for agentic skills around working with MuJoCo in Python. Feel free to check them out here: https://github.com/prathje/agentic_mujoco_skills

Mujoco is also key part of nvidias Newton physics system

https://github.com/newton-physics/newton

This makes me so happy and excited! Often my mind wanders into the unknown, imagining what would happy to X if it did this? Would it have friction, etc?

I am looking forward to a way I can easily describe a scenario and have an LLM build a legitimate simulation for it. No more hypothetical talk! Next best thing to actual experimentation (can be a useful tool in convincing others to join you/support you in said real experiment - “see? I tested it in a simulation and it behaves exactly that way! We need to try this..”).

People have made cool racing education simulators with this too: https://github.com/FT-Autonomous/ft_grandprix.

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