Topology Optimization of Skeleton-Reinforced Soft Pneumatic Actuators for Desired Motions
Shitong Chen, Feifei Chen, Zizheng Cao, Yusheng Wang, Yunpeng Miao, Guoying Gu, Xiangyang Zhu
Abstract
Multimaterials with different modulus can endow soft robots with embodied intelligence that deliver spatially varying deformation upon actuation. There is an increasing need for design tools that can rigorously and efficiently generate material layouts for desired motions. Here, we present a design paradigm for soft pneumatic multimaterial actuators by attaching a stiffer material layer as skeleton to softer inflated rubber, and develop a topology optimization based framework to automatically generate the skeleton layout that leads the actuator to achieve desired motions such as bending or twisting. Our method is enabled by a dynamic level set function to describe and track the topological change of the skeleton, large-deformation analysis compatible with the varying skeleton layout, and a gradient-based optimizer to govern the evolution of material layout, with the geometric and material nonlinearities taken into account. A forward geometric mapping and a backward design velocity mapping are constructed to allow manipulating the level sets on the planar space. We show that the design methodology is capable of generating high-performance bending and twisting actuators of cylindrical or customized cone shape. The simulation and experiment results show that, the bending actuator achieves a free bending angle 73° and blocking force 2.05 N, and the twisting actuator achieves a large rotation angle of 143°.