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arXiv AI By Ruixiang Ouyang, Guanren Qiao, Fansen Meng, Yueci Deng, Ruixing Jin, Kui Jia, Guiliang Liu

RiCo: Neural Simulation of Rigid-Body Interactions via Local Contact Reasoning

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RiCo is a neural simulation framework that models rigid‑body interactions by focusing on sparse neighborhoods of contact surface points. It integrates each point’s state with the geometry, motion, and physical properties of nearby surfaces, enabling local reasoning that preserves fine‑grained interaction details without modeling every pair of scene points. Experiments on the MOVi benchmark show that RiCo reduces 100‑frame position and orientation errors by 31‑35% and 38%, respectively, while achieving high contact fidelity and zero‑shot generalization to scenes with 270 objects.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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