A Convex Formulation of Material Points and Rigid Bodies with GPU-Accelerated Async-Coupling for Interactive Simulation

Chang Yu, Wenxin Du, Zeshun Zong, Alejandro Castro, Chenfanfu Jiang, Xuchen Han

Attend In Person: Yes

Keywords: Deformable Object Simulation, Robotic Manipulation, Convex Contact Formulation, GPU Acceleration, Material Point Method

TL;DR: We propose a GPU-parallelizable convex formulation that couples MPM with rigid body dynamics for fast and robust simulation of deformable object manipulation in robotics.

Abstract: We present a novel convex formulation that weakly couples the Material Point Method (MPM) with rigid body dynamics through frictional contact, optimized for efficient GPU parallelization. Our approach features an asynchronous time-splitting scheme to integrate MPM and rigid body dynamics under different time step sizes. We develop a globally convergent quasi-Newton solver tailored for massive parallelization, achieving up to 500× speedup over previous convex formulations without sacrificing stability. Our method enables interactive-rate simulations of robotic manipulation tasks with diverse deformable objects including granular materials and cloth, with strong convergence guarantees. We detail key implementation strategies to maximize performance and validate our approach through rigorous experiments, demonstrating superior speed, accuracy, and stability compared to state-of-the-art MPM simulators for robotics. We make our method available in the open-source robotics toolkit, Drake.

Submission Number: 5