Efficient thrust generation in robotic fish caudal fins using policy search

Yixi Shan, Yagiz E. Bayiz, Bo Cheng

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)38-44
Number of pages7
JournalIET Cyber-systems and Robotics
Volume1
Issue number1
DOIs
StatePublished - Jun 2019

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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