Embedded IPC: Fast and Intersection-Free Simulation in Reduced Subspace for Robot Manipulation
Wenxin Du, Chang Yu, Siyu Ma, Ying Jiang, Zeshun Zong, Yin Yang, Joseph Masterjohn, Alejandro M. Castro
Abstract
Physics-based simulation is essential for developing and evaluating robot manipulation policies, particularly in scenarios involving deformable objects and complex contact interactions. However, existing simulators often struggle to balance computational efficiency with numerical accuracy, especially when modeling deformable materials with frictional contact constraints. We introduce an efficient subspace representation for the Incremental Potential Contact (IPC) method, leveraging model reduction to decrease the number of degrees of freedom. Our approach decouples simulation complexity from the resolution of the input model by representing elasticity in a low-resolution subspace while maintaining collision constraints on an embedded high-resolution surface. Our barrier formulation ensures intersection-free trajectories and configurations regardless of material stiffness, time step size, or contact severity. We validate our simulator through quantitative experiments with a soft bubble gripper grasping and qualitative demonstrations of placing a plate on a dish rack. The results demonstrate our simulator's efficiency, physical accuracy, computational stability, and robust handling of frictional contact, making it well-suited for generating demonstration data and evaluating downstream robot training applications. More details and supplementary material are on the website: https://sites.google.com/view/embedded-ipc.
BibTeX
@inproceedings{icra2025_embeddedipcfasta,
title = {Embedded IPC: Fast and Intersection-Free Simulation in Reduced Subspace for Robot Manipulation},
author = {Wenxin Du and Chang Yu and Siyu Ma and Ying Jiang and Zeshun Zong and Yin Yang and Joseph Masterjohn and Alejandro M. Castro and Xuchen Han and Chenfanfu Jiang},
booktitle = {ICRA 2025},
year = {2025}
}