Paper ID: 2203.02054

Collision-Aware Fast Simulation for Soft Robots by Optimization-Based Geometric Computing

Guoxin Fang, Yingjun Tian, Andrew Weightman, Charlie C. L. Wang

Soft robots can safely interact with environments because of their mechanical compliance. Self-collision is also employed in the modern design of soft robots to enhance their performance during different tasks. However, developing an efficient and reliable simulator that can handle the collision response well, is still a challenging task in the research of soft robotics. This paper presents a collision-aware simulator based on geometric optimization, in which we develop a highly efficient and realistic collision checking / response model incorporating a hyperelastic material property. Both actuated deformation and collision response for soft robots are formulated as geometry-based objectives. The collision-free body of a soft robot can be obtained by minimizing the geometry-based objective function. Unlike the FEA-based physical simulation, the proposed pipeline performs a much lower computational cost. Moreover, adaptive remeshing is applied to achieve the improvement of the convergence when dealing with soft robots that have large volume variations. Experimental tests are conducted on different soft robots to verify the performance of our approach.

Submitted: Mar 3, 2022