Bioinspired soft robots for deep-sea exploration
Guorui Li, Tuck‐Whye Wong, Benjamin Shih, Chunyu Guo, Luwen Wang, Jiaqi Liu, Tao Wang, Xiaobo Liu, Jiayao Yan, Baosheng Wu, Fajun Yu, Yunsai Chen, Yiming Liang, Yaoting Xue, Chengjun Wang, Shunping He, Li Wen, Michael T. Tolley, A‐Man Zhang, Cecilia Laschi
- Year
- 2023
- Citations
- 199
- Access
- Open access
Abstract
The deep ocean, Earth's untouched expanse, presents immense challenges for exploration due to its extreme pressure, temperature, and darkness. Unlike traditional marine robots that require specialized metallic vessels for protection, deep-sea species thrive without such cumbersome pressure-resistant designs. Their pressure-adaptive forms, unique propulsion methods, and advanced senses have inspired innovation in designing lightweight, compact soft machines. This perspective addresses challenges, recent strides, and design strategies for bioinspired deep-sea soft robots. Drawing from abyssal life, it explores the actuation, sensing, power, and pressure resilience of multifunctional deep-sea soft robots, offering game-changing solutions for profound exploration and operation in harsh conditions.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991