2024 | Xiaorui Zhou, Guancong Chen, Binjie Jin, Haijun Feng, Zike Chen, Mengqi Fang, Bo Yang, Rui Xiao, Tao Xie, and Ning Zheng*
This study presents a liquid crystal elastomer (LCE) robot capable of achieving self-sustained multimodal locomotion, with the specific motion mode controlled via substrate adhesion or remote light stimulation. The LCE is mechanically trained to undergo repeated snapping actions, ensuring its self-sustained rolling motion in a constant gradient thermal field. By fine-tuning the substrate adhesion, the robot exhibits reversible transitions between rolling and jumping modes. Additionally, the rolling motion can be manipulated in real-time through light stimulation to perform various diverse motions, including turning, decelerating, stopping, backing up, and steering around complex obstacles. The introduction of on-demand gate control offers a new approach for designing future autonomous soft robots. The LCE robot's ability to switch between different modes and perform complex functions with real-time light control demonstrates the potential for advanced applications in autonomous robotics.This study presents a liquid crystal elastomer (LCE) robot capable of achieving self-sustained multimodal locomotion, with the specific motion mode controlled via substrate adhesion or remote light stimulation. The LCE is mechanically trained to undergo repeated snapping actions, ensuring its self-sustained rolling motion in a constant gradient thermal field. By fine-tuning the substrate adhesion, the robot exhibits reversible transitions between rolling and jumping modes. Additionally, the rolling motion can be manipulated in real-time through light stimulation to perform various diverse motions, including turning, decelerating, stopping, backing up, and steering around complex obstacles. The introduction of on-demand gate control offers a new approach for designing future autonomous soft robots. The LCE robot's ability to switch between different modes and perform complex functions with real-time light control demonstrates the potential for advanced applications in autonomous robotics.