Research Papers

A Study on Kinematic Pattern of Fish Undulatory Locomotion Using a Robot Fish

[+] Author and Article Information
Yong Zhong

Department of Biomedical Engineering,
National University of Singapore,
Block E6, Level 7,
5 Engineering Drive 1,
Singapore 117608
e-mail: zhongyong_hust@foxmail.com

Jialei Song

Department of Mechanical
and Automation Engineering,
The Chinese University of Hong Kong,
Rm 110 William M.W.Mong Eng.Bldg,
Shatin 999077, N.T., Hong Kong, China
e-mail: songjialei_1989@163.com

Haoyong Yu

Department of Biomedical Engineering,
National University of Singapore,
Block E6, Level 7,
5 Engineering Drive 1,
Singapore 117608
e-mail: bieyhy@nus.edu.sg

Ruxu Du

Fellow ASME
Department of Mechanical
and Automation Engineering,
The Chinese University of Hong Kong,
Room 209, William M.W. Mong
Engineering Building,
Shatin 999077, N.T., Hong Kong, China
e-mail: rdu@mae.cuhk.edu.hk

1Present address: Department of Biomedical Engineering, National University of Singapore, Block E6, Level 7, 5 Engineering Drive 1, Singapore 117608.

Contributed by the Mechanisms and Robotics Committee of ASME for publication in the JOURNAL OF MECHANISMS AND ROBOTICS. Manuscript received May 5, 2017; final manuscript received May 16, 2018; published online June 25, 2018. Assoc. Editor: Byung-Ju Yi.

J. Mechanisms Robotics 10(4), 041013 (Jun 25, 2018) (11 pages) Paper No: JMR-17-1134; doi: 10.1115/1.4040434 History: Received May 05, 2017; Revised May 16, 2018

Recent state-of-art researches on robot fish focus on revealing different swimming mechanisms and developing control methods to imitate the kinematics of the real fish formulated by the so-called Lighthill's theory. However, the reason why robot fish must follow this formula has not been fully studied. In this paper, we adopt a biomimetic untethered robot fish to study the kinematics of fish flapping. The robot fish consists of a wire-driven body and a soft compliant tail, which can perform undulatory motion using one motor. A dynamic model integrated with surrounding fluid is developed to predict the cruising speed, static thrust, dynamic thrust, and yaw stability of the robot fish. Three driving patterns of the motor are experimented to achieve three kinematic patterns of the robot fish, e.g., triangular pattern, sinusoidal pattern, and an over-cambered sinusoidal pattern. Based on the experiment results, it is found that the sinusoidal pattern generated the largest average static thrust and steady cruising speed, while the triangular pattern achieved the best yaw stability. The over-cambered sinusoidal pattern was compromised in both metrics. Moreover, the kinematics study has shown that the body curves of the robot fish were similar to the referenced body curves presented by the formula when using the sinusoidal pattern, especially the major thrust generation area. This research provides a guidance on the kinematic optimization and motor control of the undulatory robot fish.

Copyright © 2018 by ASME
Topics: Kinematics , Robots , Thrust , Yaw
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Fig. 3

Three selected types of kinematic patterns

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Fig. 2

The kinematic patterns of the active body in one cycle under different B

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Fig. 1

Robot fish overview: (a) is the design model; (b) shows the undulatory motion of the ACPM, (c) illustrates the diagram of each joint of the ACPM; (d) depicts the molds of the compliant tail; (e) shows the finished compliant tail with a tuna-like caudal fin embedded carbon fibers, and the fin span is b, the projected fin area is SC; and (f) shows the prototype of the robot fish

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Fig. 4

Control system for the robot fish

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Fig. 5

Schematic representations of robot fish modeling

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Fig. 8

(a) Experimental setup for measuring static thrust and (b) experimental setup for cruising

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Fig. 9

Static thrust under different types of kinematic pattern. The red curve, blue curve, and black curve denote the results corresponding to the triangular pattern, sinusoidal pattern, and over-cambered sinusoidal pattern, respectively.

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Fig. 10

The average static thrusts of different actuation frequencies and amplitudes

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Fig. 15

The measured average static thrusts and yaw angles. The x-axis denotes the flapping amplitude of the ACPM, here, we set Ф = 30 deg, 45 deg, and 60 deg.

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Fig. 6

Velocity of the end point of the active body

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Fig. 7

The static thrusts, dynamic thrusts, cruising velocities, and yaw angle variations of the robot fish under three kinematic patterns

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Fig. 11

The average static thrusts of different actuation frequencies and amplitudes

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Fig. 12

The kinematics extraction process from video frames

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Fig. 13

The extracted body curves of the robot fish in real time. The red curve, blue curve, and black curve denote the results corresponding to the triangular pattern, sinusoidal pattern, and over-cambered sinusoidal pattern, respectively. The flapping frequency is 2.0 Hz, the flapping amplitude is 60 deg, and the video speed is 240 frames/s.

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Fig. 14

The first picture shows the body curves of fish expressed by formula (21), where c0=0.06,c1=−0.25,c2=0.35,k = 7, and ω = π. The second picture depicts the real body curves of the robot fish indicated by the red curves.

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Fig. 16

The comparison of the average velocities between the simulated results and the experimental results calculated from Figs. 6 and 10



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