Sim-to-Real for Soft Robots Using Differentiable FEM: Recipes for Meshing, Damping, and Actuation

被引:28
作者
Dubied, Mathieu [1 ]
Michelis, Mike Yan [1 ]
Spielberg, Andrew [2 ]
Katzschmann, Robert Kevin [1 ]
机构
[1] Swiss Fed Inst Technol, Soft Robot Lab, Dept Mech & Proc Engn, CH-8092 Zurich, Switzerland
[2] MIT, Comp Sci & Artificial Intelligence Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA
关键词
Modeling; control; and learning for soft robots; dynamics; optimization and optimal control; simulation and animation; OPTIMIZATION; DESIGN;
D O I
10.1109/LRA.2022.3154050
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
An accurate, physically-based, and differentiable model of soft robots can unlock downstream applications in optimal control. The Finite Element Method (FEM) is an expressive approach for modeling highly deformable structures such as dynamic, elastomeric soft robots. In this paper, we compare virtual robot models simulated using differentiable FEM with measurements from their physical counterparts. In particular, we examine several soft structures with different morphologies: a clamped soft beam under external force, a pneumatically actuated soft robotic arm, and a soft robotic fish tail. We benchmark and analyze different meshing resolutions and elements (tetrahedra and hexahedra), numerical damping, and the efficacy of differentiability for parameter calibration using a simulator based on the fast Differentiable Projective Dynamics (DiffPD). We also advance FEM modeling in application to soft robotics by proposing a predictive model for pneumatic soft robotic actuation. Through our recipes and case studies, we provide strategies and algorithms for matching real-world physics in simulation, making FEM useful for soft robots.
引用
收藏
页码:5015 / 5022
页数:8
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