Study on the fish robot locomotion based on biomimetic method

doi:10.11835/j.issn.1000-582X.2015.06.019

Home > Archive>Volume 38, Issue 6, 2015 >138-146. DOI:10.11835/j.issn.1000-582X.2015.06.019

Study on the fish robot locomotion based on biomimetic method
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                        10.11835/j.issn.1000-582X.2015.06.019
                    
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                        WANG JinWANG Jin
Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065， P. R. China;
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JIANG DingliJIANG Dingli
Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065， P. R. China;
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DENG XinDENG Xin
Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065， P. R. China;
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CHEN QiaosongCHEN Qiaosong
Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065， P. R. China;
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ZENG XiangjingZENG Xiangjing
State Grid Electric Power Company Hengyang, Hunan Province Power Supply Branch, Hengyang 421002, Hunan, P. R. China;
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LUO YanLUO Yan
Department of Art, Chongqing Normal University, Chongqing 401331,P. R. China
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Fund Project:Supported by National Science Foundation of China(61403054；61403053), Chongqing Natural Science Foundation(cstc2014jcyjA4002),and the Science Foundation Project of CQ Education Commison under Grant(KJ1400436).

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Abstract:

Locomotion behavior modeling is a key and difficult problem in the research field of robotic fish. In this paper, a novel biomimetic learning approach is applied to the movement patterns generation of a multi-joint robotic fish. Firstly, the real fish behaviors are recorded by video system. By analyzing the recorded data, three basic swimming patterns, “cruise”, “cruise in turning” and “C sharp turn”, are extracted. Then the general internal model (GIM) is employed to learn the swimming patterns of carangiform fishes. Based on the approximation ability and the temporal-spatial scalabilities of GIM, robotic fish owns the capability of learning, modifying and regenerating the similar swimming patterns of the real fish. Finally, autonomous obstacle avoidance behavior of the robotic fish is realized by combining infrared sensors and obstacle avoidance algorithm. The experiment result verifies the validity of the proposed biomimetic learning approach.

Key words:biomimetic learning; robotic fish; general internal model; obstacle avoidance

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王进,蒋定立,邓欣,陈乔松,曾向璟,罗燕.仿生学习的机器鱼运动模式分析[J].重庆大学学报,2015,38(6):138~146

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Received:July 11,2015
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Online: January 04,2016
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