Investigating the effects of material ratio scenarios on soft robot design based on morphology–material–control coevolution

Abstract

This study explores the influence of material selection scenarios on the evolutionary design of soft robots. Soft robots have vast potential applications that rigid robots cannot accomplish due to their lightweight and flexible nature. Despite rapid development of soft robotics in recent years, its effective automatic design method remains undeveloped. To combat this, evolutionary computation has been proposed for automatic soft robot design. Material selection has been identified as crucial in influencing the outcomes of autonomously designed soft robots, yet understanding of its impacts remains limited, particularly in changing material selection scenarios across generations. In this study, we hypothesized that these changing scenarios could influence the evolved robots. Initial experiments, based on travel distance and energy efficiency, suggested material selection could greatly impact the final robot. Further experiments, adjusting material ratio and rewarding specific material use, identified how certain material selection scenarios led to changes in the structure and performance of the evolved soft robots. These findings contribute to automatic design methodologies in soft robotics.