Genesis – a generative physics engine for general-purpose robotics
genesis-world.readthedocs.io
Genesis – a generative physics engine for general-purpose robotics
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Re: Genesis – a generative physics engine for general-purpose robotics
#2Re: Genesis – a generative physics engine for general-purpose robotics
#3GitHub: https://github.com/Genesis-Embodied-AI/Genesis
academic project page: https://genesis-embodied-ai.github.io
Re: Genesis – a generative physics engine for general-purpose robotics
#4Re: Genesis – a generative physics engine for general-purpose robotics
#5Super exciting!
Re: Genesis – a generative physics engine for general-purpose robotics
#6Re: Genesis – a generative physics engine for general-purpose robotics
#7The automatic differentiation seems to be intended for compatibility with Pytorch. Will Genesis be able to interface with JAX as well?
The project looks interesting, but the website is somewhat light on details. In any case, all the best to the developers! It's great to hear about various efforts in the space of differentiable simulators.
Re: Genesis – a generative physics engine for general-purpose robotics
#8Re: Genesis – a generative physics engine for general-purpose robotics
#9Re: Genesis – a generative physics engine for general-purpose robotics
#10> Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. ... Nvidia brought GPU acceleration to robotic simulation, speeding up simulation speed by more than one order of magnitude compared to CPU-based simulation. ... Genesis pushes up this speed by another order of magnitude.
I can believe that setting up some kind of compute pipeline in a high level language such as Python could be fast, but the marketing materials aren't explaining any of the "how", if it's real it must be GPU-accelerated, but they almost imply that it isn't. Looks neat, hope it works great!