Bioinspired underwater soft robots: from biology to robotics and back
Lei Li, Boyang Qin, Wenzhuo Gao, Yanyu Li, Yiyuan Zhang, Bo Wang, Shihan Kong, Jian Wang, Dekui He, Junzhi Yu
- 发表年份
- 2025
- 访问权限
- 开放获取
摘要
The ocean vast unexplored regions and diverse soft-bodied marine organisms have spurred interest in bio-inspired underwater soft robotics. Recent advances have enabled new capabilities in underwater movement, sensing, and interaction. However, these efforts are largely unidirectional, with biology guiding robotics while insights from robotics rarely feed back into biology. Here we propose a holistic, bidirectional framework that integrates biological principles, robotic implementation, and biological validation. We show that soft robots can serve as experimental tools to probe biological functions and even test evolutionary hypotheses. Their inherent compliance also allows them to outperform rigid systems in unstructured environments, supporting applications in marine exploration, manipulation, and medicine. Looking forward, we introduce bio-universal-inspired robotics, a paradigm that transcends species-specific mimicry by identifying convergent principles across species to inspire more adaptable designs. Despite rapid progress, challenges persist in material robustness, actuation efficiency, autonomy, and intelligence. By uniting biology and engineering, soft robots can advance ocean exploration and deepen scientific discovery.
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