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Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish | |
Tong, Ru1,2; Wu, Zhengxing2,3; Li, Sijie2,3; 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. |
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