10 citations · 12 across the 3 of their papers we have counts for
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cs.RO2022★ 2 cited
Differentiable Physics Simulation of Dynamics-Augmented Neural Objects
Simon Le Cleac'h, Hong-Xing Yu, Michelle Guo +5
We present a differentiable pipeline for simulating the motion of objects that represent their geometry as a continuous density field parameterized as a deep network. This includes…
cs.RO2022★ 10 cited
Dojo: A Differentiable Physics Engine for Robotics
Taylor A. Howell, Simon Le Cleac'h, Jan Brüdigam +5
We present Dojo, a differentiable physics engine for robotics that prioritizes stable simulation, accurate contact physics, and differentiability with respect to states, actions, a…