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DOI: http://dx.doi.org/10.7551/978-0-262-31050-5-ch043
Pages 325-332
First published 2 July 2012

Evolutionary Design and Experimental Validation of a Flexible Caudal Fin for Robotic Fish

Anthony J. Clark, Jared M. Moore, Jianxun Wang, Xiaobo Tan, Philip K. McKinley

Abstract

Designing a robotic fish is a challenging endeavor due to the non-linear dynamics of underwater environments. In this paper, we present an evolutionary computation approach for designing the caudal fin of a carangiform robotic fish. Evolutionary experiments are performed in a simulated environment utilizing a mathematical model to approximate the hydrodynamic motion of a flexible caudal fin. With this model, time-consuming computational fluid dynamic simulations can be avoided while maintaining a physically realistic simulation. Two approaches are employed to maximize a robotic fish's average velocity. First, a hill-climbing algorithm is applied to find the optimal stiffness for a fixed shape caudal fin. Next, both fin stiffness and shape are simultaneously optimized with a genetic algorithm. Additionally, simulated caudal fins are compared to physically validated fins, which were fabricated with the aid of a 3D printer and tested on a robotic fish prototype. Results show a correlation between evolved results, model predicted behavior, and physical robot performance with some disparity due to the difficulty in accurately approximating real world performance in a simulation environment. Despite the disparity, evolutionary design is shown to be a viable process.