A Transition-Aware Method for the Simulation of Compliant Contact with Regularized Friction release_rdst3ysvqveijirsz6wepeyzhy

by Alejandro M. Castro, Ante Qu, Naveen Kuppuswamy, Alex Alspach, and Michael Sherman

Released as a article .

2019  

Abstract

Multibody simulation with frictional contact has been a challenging subject of research for the past thirty years. Rigid-body assumptions are commonly used to approximate the physics of contact, and together with Coulomb friction, lead to challenging-to-solve nonlinear complementarity problems (NCP). On the other hand, robot grippers often introduce significant compliance. Compliant contact, combined with regularized friction, can be modeled entirely with ODEs, avoiding NCP solves. Unfortunately, regularized friction introduces high-frequency stiff dynamics and even implicit methods struggle with these systems, especially during slip-stick transitions. To improve the performance of implicit integration for these systems we introduce a Transition-Aware Line Search (TALS), which greatly improves the convergence of the Newton-Raphson iterations performed by implicit integrators. We find that TALS works best with semi-implicit integration, but that the explicit treatment of normal compliance can be problematic. To address this, we develop a Transition-Aware Modified Semi-Implicit (TAMSI) integrator that has similar computational cost to semi-implicit methods but implicitly couples compliant contact forces, leading to a more robust method. We evaluate the robustness, accuracy and performance of TAMSI and demonstrate our approach alongside a sim-to-real manipulation task.
In text/plain format

Archived Files and Locations

application/pdf  2.0 MB
file_kdvrgt3tenat7ltatsjm6ojfey
arxiv.org (repository)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article
Stage   submitted
Date   2019-09-17
Version   v2
Language   en ?
arXiv  1909.05700v2
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: b554a6ba-cca1-42e7-8fea-61e6b9d44374
API URL: JSON