Path planning of an elongated undulating fin using mutant particle swarm optimization

Abstract

This paper proposes a mutant particle swarm optimization algorithm (M-PSO) to optimize the power energy of a bio-mimetic robotic fish that comprises sixteen undulating fin-rays equipped to a fish robot. The main objective is to obtain the shortest path for the fish robot to achieve the desired position while minimizing power consumption. The proposed MPSO is a recent generation of particle swarm optimization (PSO) that employs the removal of the worst particles to accelerate the swarm, enabling particles to escape local minima and improve the propulsive efficiency of the fish robot. Simulation results demonstrate that the developed M-PSO consumes less energy and requires less time compared to the original PSO and genetic algorithm (GA). Moreover, the M-PSO was tested on a robotic fish navigating an unknown environment characterized by complex spatiotemporal parameters, showcasing its superiority over other methods in all case studies.