Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish

doi:10.1109/TMECH.2024.3408036

	Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish
	Tong, Ru1,2 ; Wu, Zhengxing2,3 ; Li, Sijie 2,3; Chen, Di1,2 ; Wang, Jian2,3 ; Tan, Min2,3 ; Yu, Junzhi1,2
发表期刊	IEEE-ASME TRANSACTIONS ON MECHATRONICS
ISSN	1083-4435
	2024-06-13
页码	11
通讯作者	Yu, Junzhi(junzhi.yu@ia.ac.cn)
摘要	Tail flexibility optimization is crucial for improving the speed and efficiency of robotic fish. However, reliable flexible tail structures and accessible modeling methods are still in the exploratory stage. This article proposes a novel integral molding flexible fish tail (IMFFT) characterized by continuous flexibility, a hollow air cavity, and an embedded skeletal structure. These features empower the tail with continuous flexible propulsion capabilities, neutral buoyancy for stable fish posture, and limited compressibility for withstanding water pressure. In addition, a predictive-network-based model for the IMFFT is developed through thrust data acquisition, dynamic analysis, and predictive network training. Specifically, the predictive network enables the prediction of pattern parameters of passive angles on the flexible tail. Deploying the IMFFT on our self-developed robotic tuna, performance tests demonstrate significant improvements, including a high swimming speed of 3.28 body lengths per second, an average speed improvement of 25.30%, an average cost of transport (COT) reduction of 24.45%, and a 57.12% reduction in roll angle fluctuation range due to the neutral buoyancy of the fish tail, which competes favorably with rigid fish tails and other flexible tail structures. This study provides novel guidance for optimizing the flexibility of underwater bioinspired robots.
关键词	Data-driven modeling flexibility optimization integral molding flexible tail predictive network robotic fish underwater robot
DOI	10.1109/TMECH.2024.3408036
关键词[WOS]	BODY STIFFNESS ; PERFORMANCE
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China
项目资助者	National Natural Science Foundation of China
WOS研究方向	Automation & Control Systems ; Engineering
WOS类目	Automation & Control Systems ; Engineering, Manufacturing ; Engineering, Electrical & Electronic ; Engineering, Mechanical
WOS记录号	WOS:001248177600001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/58731
专题	复杂系统认知与决策实验室_水下机器人
通讯作者	Yu, Junzhi
作者单位	1.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China 2.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Tong, Ru,Wu, Zhengxing,Li, Sijie,et al. Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2024:11.
APA	Tong, Ru.,Wu, Zhengxing.,Li, Sijie.,Chen, Di.,Wang, Jian.,...&Yu, Junzhi.(2024).Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish.IEEE-ASME TRANSACTIONS ON MECHATRONICS,11.
MLA	Tong, Ru,et al."Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2024):11.