PhysCoRe: Physics-Corrected Residual World Models for Material-Aware Deformable Dynamics
Predicting how deformable objects evolve under robotic manipulation is a longstanding challenge. Existing approaches typically rely on per-object optimization to fit material parameters, which can be slow and cannot generalize, while end-to-end learned alternatives extrapolate poorly and often violate basic physical structure. We present PhysCoRe, a physics-corrected residual world model that couples a differentiable Material Point Method (MPM) simulator with two feed-forward neural networks. A material refinement module, Material from Motion (MfM), infers per-particle elasticity from visual observations, grounding the simulator in object-specific physics. A residual correction module, Re...
| Authors | Haocheng Yin, Shuohan Tao, Yongsheng Chen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 July 2026 |
| Last updated at source | 9 October 2026 |
Models and datasets referencing this paper
- GeorgiaTech/PhysCoReDataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.