Bio-inspired multimodal soft actuator with environmental self-adaptation

Chi Chen, Zixiao Liu, Pengju Shi, Yusen Zhao, Sidi Duan, Yingjie Du, Yichen Yan, Muqing Si, Tetsuya Iwasaki and Ximin He ()
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Chi Chen: Department of Material Science and Engineering, University of California
Zixiao Liu: Department of Material Science and Engineering, University of California
Pengju Shi: Department of Material Science and Engineering, University of California
Yusen Zhao: Department of Material Science and Engineering, University of California
Sidi Duan: Department of Material Science and Engineering, University of California
Yingjie Du: Department of Material Science and Engineering, University of California
Yichen Yan: Department of Material Science and Engineering, University of California
Muqing Si: Department of Material Science and Engineering, University of California
Tetsuya Iwasaki: Department of Mechanical and Aerospace Engineering, University of California
Ximin He: Department of Material Science and Engineering, University of California

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract Autonomous soft robots with built-in feedback can achieve self-sustained motion under constant, untethered stimuli. However, these systems are constrained to single-mode actuation within a fixed structure under the same type of stimulus and require human intervention to switch modes, lacking the robust and efficient self-adaptation of living organisms in changing environments. Inspired by Gymnura micrura, we developed a light-responsive soft actuator with engineered asymmetry and a dynamic structure, integrating two distinct built-in feedback mechanisms governed by intrinsic bifurcation. Thus, the actuator can seamlessly switch between three different motion modes—tracking, undulation, and oscillation—exhibiting self-adaptation to environmental changes (e.g., light intensity, viscosity, temperatures, and physical contact). Furthermore, this multimodal capability facilitates unique environmental interactions, expanding applications beyond locomotion to include fluid dynamics, electronics, and environmental monitoring. Such an advancement in physical intelligence represents a pivotal step toward next-generation autonomous soft robotic systems, unlocking higher-level autonomy and unprecedented adaptive behaviors.

Date: 2025
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DOI: 10.1038/s41467-025-62328-2

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