Review of bioinspired aquatic jumping robots

Tao Zhang , Jiawei Dong , Qianqian Chen , Xiongqian Wu , Shuqi Wang , Yisheng Guan

Biomimetic Intelligence and Robotics ›› 2025, Vol. 5 ›› Issue (2) : 100204

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Biomimetic Intelligence and Robotics ›› 2025, Vol. 5 ›› Issue (2) : 100204 DOI: 10.1016/j.birob.2024.100204
Review

Review of bioinspired aquatic jumping robots

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Abstract

In natural, aquatic and amphibians creatures have evolved exceptional impulsive-based, momentum-based, and mixed water-air cross domain locomotion capabilities through long-term natural selection, providing significant reference and inspiration for the design of aquatic jumping robots. In recent years, inspired by nature and biology, researchers have turned to jumping as a potential mode of locomotion for aquatic robots, aiming to improve their adaptability across water-air environment. However, the performance of these robots remains significantly limited, far from meeting practical application requirements, due to issues like inadequate propulsion efficiency, high structural resistance, and excessive weight. This paper summarizes the key features of bioinspired aquatic jumping robots, including their bioinspired structural designs, jumping mechanisms, and actuators, while evaluating their jumping performance. Finally, the current challenges are analyzed, and future prospects for development are discussed.

Keywords

Aquatic and amphibians / Aquatic jumping robots / Water-air environment / Bioinspired structural

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Tao Zhang, Jiawei Dong, Qianqian Chen, Xiongqian Wu, Shuqi Wang, Yisheng Guan. Review of bioinspired aquatic jumping robots. Biomimetic Intelligence and Robotics, 2025, 5(2): 100204 DOI:10.1016/j.birob.2024.100204

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CRediT authorship contribution statement

Tao Zhang: Writing - review & editing, Writing - original draft. Jiawei Dong: Writing - review & editing, Writing - original draft. Qianqian Chen: Investigation, Data curation. Xiongqian Wu: Data curation. Shuqi Wang: Writing - review & editing, Data curation. Yisheng Guan: Investigation, Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was support by the National Natural Science Foundation of China (52275011), Natural Science Foundation of Guangdong Province (2023B1515020080), Young Elite Scientists Sponsorship Program by CAST (2021QNRC001), Guangdong Basic and Applied Basic Research Foundation (2023A1515011253), Higher Education Institution Featured Innovation Project of Department of Education of Guangdong Province (2023KTSCX138), Natural Science Foundation of Guangzhou (2024A04J2552) and Fundamental Research Funds for the Central Universities.

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