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      Efficient thrust generation in robotic fish caudal fins using policy search

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          Abstract

          Thrust generation is a crucial aspect of fish locomotion that depends on a variety of morphological and kinematic parameters. In this work, the kinematics of caudal fin motion of a robotic fish are optimised experimentally. The robotic fish actuates its caudal fin with flapping and rotation motion, and also measures the fin hydrodynamic force and torque. Total nine designs of the caudal fins are investigated, with three different shapes (or inclination angles) and three stiffness. The optimisation is based on a policy search (PS) algorithm, which is used to maximise the thrust-generation efficiency of the caudal fins. The authors first parametrise fin spanwise-rotation as a sinusoidal function using rotation amplitude and phase delay and test whether it is beneficial to thrust-generation efficiency. The result shows that the rotation does not contribute to the efficiency, as the efficiency is maximised at zero amplitude. Next, the authors optimise flapping amplitude and trajectory profile without fin rotation. Results show that smaller flapping amplitude results in higher efficiency and linear flapping trajectories are preferred over sinusoidal ones. Fins that have the highest flexibility are more efficient in thrust generation although they generate less thrust, while an inclination angle of 30° yields the most efficient fin shape.

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          Most cited references 27

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          Review of fish swimming modes for aquatic locomotion

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            PASSIVE AND ACTIVE FLOW CONTROL BY SWIMMING FISHES AND MAMMALS

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              Wake mechanics for thrust generation in oscillating foils

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                Author and article information

                Contributors
                Journal
                IET-CSR
                IET Cyber-systems and Robotics
                IET Cyber-Syst. Robot.
                The Institution of Engineering and Technology
                2631-6315
                1 March 2019
                2 April 2019
                June 2019
                : 1
                : 1
                : 38-44
                Affiliations
                Department of Mechanical Engineering, The Pennsylvania State University, State College , USA
                Article
                IET-CSR.2018.0005 CSR.2018.0005.R1
                10.1049/iet-csr.2018.0005

                This is an open access article published by the IET and Zhejiang University Press under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                Page count
                Pages: 0
                Product
                Funding
                Funded by: National Science Foundation
                Award ID: CMMI 1554429
                Funded by: Army Research Office
                Award ID: W911NF1610272
                Categories
                Research Article

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