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An Untethered, Autonomous and Sustainable Soft Crawler

ORAL

Abstract

Crawling is an essential mode of locomotion for many natural organisms, such as caterpillars, allowing them to navigate complex terrains and escape predators, which inspires scientists to develop soft crawling robots capable of navigating challenging environments based on stimuli-responsive materials. However, existing crawling systems are often limited by their dependence on specially tailored friction interactions, dynamic non-uniform stimuli control, complex fabrication involving heterogeneous materials, or extremely slow crawling speeds, which hinder practical applications. In this study, using experiments and finite element analyses, we present an autonomous, unidirectional, untethered, and sustainable soft crawler made of photothermal liquid crystal elastomers (LCEs), which can undergo large and reversible deformation in response to light. By incorporating different concentrations of a light absorber, reduced graphene oxide (rGO), into different regions of an LCE strip, we are able to tune the spatiotemporal bending of each region on the ground under light illumination, which results in distinct frictional forces at the two ends of the strip, leading to unidirectional movement. This approach enables unidirectional crawling with a simple material system under constant light illumination, avoiding the complexity of fabrication and controls. Furthermore, experimental results and finite element analyses are employed to determine the optimal geometric and material compositions for maximizing crawling displacement, thereby providing valuable insights into developing more efficient autonomous soft robots. Additionally, multiple cycles of sustainable crawling motion were achieved by applying cyclic illumination, demonstrating the capability for continuous locomotion. This work provides guidelines on using simple material systems and simple control strategies to achieve crawling motion, contributing to the advancement of sustainable and efficient soft robots.

Presenters

  • Boliang Wu

    University of California, Los Angeles

Authors

  • Boliang Wu

    University of California, Los Angeles

  • Lihua Jin

    University of California, Los Angeles