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Chen D, Wang B, Xiong Y, Zhang J, Tong R, Meng Y, Yu J. Design and Analysis of a Novel Bionic Tensegrity Robotic Fish with a Continuum Body. Biomimetics (Basel) 2024; 9:19. [PMID: 38248593 PMCID: PMC11154324 DOI: 10.3390/biomimetics9010019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 12/22/2023] [Accepted: 12/25/2023] [Indexed: 01/23/2024] Open
Abstract
Biological fish exhibit remarkable adaptability and exceptional swimming performance through their powerful and flexible bodies. Therefore, designing a continuum flexible body is significantly important for the development of a robotic fish. However, it is still challenging to replicate these functions of a biological body due to the limitations of actuation and material. In this paper, based on a tensegrity structure, we propose a bionic design scheme for a continuum robotic fish body with a property of stiffness variation. Its detailed structures and actuation principles are also presented. A mathematical model was established to analyze the bending characteristics of the tensegrity structure, which demonstrates the feasibility of mimicking the fish-like oscillation propulsion. Additionally, the stiffness variation mechanism is also exhibited experimentally to validate the effectiveness of the designed tensegrity fish body. Finally, a novel bionic robotic fish design scheme is proposed, integrating an electronic module-equipped fish head, a tensegrity body, and a flexible tail with a caudal fin. Subsequently, a prototype was developed. Extensive experiments were conducted to explore how control parameters and stiffness variation influence swimming velocity and turning performance. The obtained results reveal that the oscillation amplitude, frequency, and stiffness variation of the tensegrity robotic fish play crucial roles in swimming motions. With the stiffness variation, the developed tensegrity robotic fish achieves a maximum swimming velocity of 295 mm/s (0.84 body length per second, BL/s). Moreover, the bionic tensegrity robotic fish also performs a steering motion with a minimum turning radius of 230 mm (0.68 BL) and an angular velocity of 46.6°/s. The conducted studies will shed light on the novel design of a continuum robotic fish equipped with stiffness variation mechanisms.
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Affiliation(s)
- Di Chen
- State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China; (D.C.); (B.W.); (Y.X.); (Y.M.)
| | - Bo Wang
- State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China; (D.C.); (B.W.); (Y.X.); (Y.M.)
| | - Yan Xiong
- State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China; (D.C.); (B.W.); (Y.X.); (Y.M.)
| | - Jie Zhang
- School of Aeronautics and Astronautics, Sun Yat-sen University, Shenzhen 518107, China;
| | - Ru Tong
- Laboratory of Cognitive and Decision Intelligence for Complex System, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
| | - Yan Meng
- State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China; (D.C.); (B.W.); (Y.X.); (Y.M.)
| | - Junzhi Yu
- State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China; (D.C.); (B.W.); (Y.X.); (Y.M.)
- Science and Technology on Integrated Information System Laboratory, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
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Chen B, Zhang J, Meng Q, Dong H, Jiang H. Complex Modal Characteristic Analysis of a Tensegrity Robotic Fish's Body Waves. Biomimetics (Basel) 2023; 9:6. [PMID: 38248580 PMCID: PMC11154480 DOI: 10.3390/biomimetics9010006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 12/14/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024] Open
Abstract
A bionic robotic fish based on compliant structure can excite the natural modes of vibration, thereby mimicking the body waves of real fish to generate thrust and realize undulate propulsion. The fish body wave is a result of the fish body's mechanical characteristics interacting with the surrounding fluid. Thoroughly analyzing the complex modal characteristics in such robotic fish contributes to a better understanding of the locomotion behavior, consequently enhancing the swimming performance. Therefore, the complex orthogonal decomposition (COD) method is used in this article. The traveling index is used to quantitatively describe the difference between the real and imaginary modes of the fish body wave. It is defined as the reciprocal of the condition number between the real and imaginary components. After introducing the BCF (body and/or caudal fin) the fish's body wave curves and the COD method, the structural design and parameter configuration of the tensegrity robotic fish are introduced. The complex modal characteristics of the tensegrity robotic fish and real fish are analyzed. The results show that their traveling indexes are close, with two similar complex mode shapes. Subsequently, the relationship between the traveling index and swimming performance is expressed using indicators reflecting linear correlation (correlation coefficient (Rc) and p value). Based on this correlation, a preliminary optimization strategy for the traveling index is proposed, with the potential to improve the swimming performance of the robotic fish.
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Affiliation(s)
- Bingxing Chen
- School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; (B.C.); (J.Z.); (Q.M.)
| | - Jie Zhang
- School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; (B.C.); (J.Z.); (Q.M.)
| | - Qiuxu Meng
- School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; (B.C.); (J.Z.); (Q.M.)
| | - Hui Dong
- School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; (B.C.); (J.Z.); (Q.M.)
| | - Hongzhou Jiang
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
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Li G, Liu G, Leng D, Fang X, Li G, Wang W. Underwater Undulating Propulsion Biomimetic Robots: A Review. Biomimetics (Basel) 2023; 8:318. [PMID: 37504206 PMCID: PMC10807579 DOI: 10.3390/biomimetics8030318] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 07/07/2023] [Accepted: 07/17/2023] [Indexed: 07/29/2023] Open
Abstract
The traditional propeller-based propulsion of underwater robots is inefficient and poorly adapted to practice. By contrast, underwater biomimetic robots show better stability and maneuverability in harsh marine environments. This is particularly true of undulating propulsion biomimetic robots. This paper classifies the existing underwater biomimetic robots and outlines their main contributions to the field. The propulsion mechanisms of underwater biomimetic undulating robots are summarized based on theoretical, numerical and experimental studies. Future perspectives on underwater biomimetic undulating robots are also presented, filling the gaps in the existing literature.
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Affiliation(s)
| | - Guijie Liu
- Department of Mechanical and Electrical Engineering, Ocean University of China, Qingdao 266000, China; (G.L.)
| | - Dingxin Leng
- Department of Mechanical and Electrical Engineering, Ocean University of China, Qingdao 266000, China; (G.L.)
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Tong R, Feng Y, Wang J, Wu Z, Tan M, Yu J. A Survey on Reinforcement Learning Methods in Bionic Underwater Robots. Biomimetics (Basel) 2023; 8:168. [PMID: 37092420 PMCID: PMC10123646 DOI: 10.3390/biomimetics8020168] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 04/25/2023] Open
Abstract
Bionic robots possess inherent advantages for underwater operations, and research on motion control and intelligent decision making has expanded their application scope. In recent years, the application of reinforcement learning algorithms in the field of bionic underwater robots has gained considerable attention, and continues to grow. In this paper, we present a comprehensive survey of the accomplishments of reinforcement learning algorithms in the field of bionic underwater robots. Firstly, we classify existing reinforcement learning methods and introduce control tasks and decision making tasks based on the composition of bionic underwater robots. We further discuss the advantages and challenges of reinforcement learning for bionic robots in underwater environments. Secondly, we review the establishment of existing reinforcement learning algorithms for bionic underwater robots from different task perspectives. Thirdly, we explore the existing training and deployment solutions of reinforcement learning algorithms for bionic underwater robots, focusing on the challenges posed by complex underwater environments and underactuated bionic robots. Finally, the limitations and future development directions of reinforcement learning in the field of bionic underwater robots are discussed. This survey provides a foundation for exploring reinforcement learning control and decision making methods for bionic underwater robots, and provides insights for future research.
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Affiliation(s)
- Ru Tong
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yukai Feng
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jian Wang
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhengxing Wu
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Tan
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junzhi Yu
- State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China
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