Technology Category
Search and Optimization: Sampling/Simulation-based SearchIntelligent Robots: ManipulationPlanning, Routing, and Scheduling: Replanning and Plan Repair
A Convex Formulation of Material Points and Rigid Bodies with GPU-Accelerated Async-Coupling for Interactive Simulation
🤖 AI Summary
This work addresses the challenge of efficient weak coupling between the Material Point Method (MPM) and rigid-body dynamics under frictional contact. We propose the first asynchronous time-splitting convex optimization framework: contact mechanics is convexified to enable asynchronous integration of MPM and rigid-body subsystems; a globally convergent parallel quasi-Newton solver is designed and GPU-accelerated (500× faster than CPU execution); and we release the first open-source, interactive MPM–rigid-body coupled simulator integrated into Drake. Our method achieves stable real-time performance (>30 FPS) in robotic manipulation scenarios—such as granular and fabric handling—while delivering significantly higher accuracy and robustness compared to state-of-the-art MPM simulators. This establishes a scalable, high-fidelity paradigm for real-time simulation of deformable objects.
Technology Category
Application Category
📝 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 500x 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.
Problem
Research questions and friction points this paper is trying to address.
Weakly couples Material Point Method with rigid body dynamics.
Enables interactive-rate simulations of robotic manipulation tasks.
Achieves significant speedup with strong convergence guarantees.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Convex formulation for MPM and rigid bodies
Asynchronous time-splitting for GPU optimization
Globally convergent quasi-Newton solver for speedup
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