Similarity Evaluation Rule and Motion Posture Optimization for a Manta Ray Robot

Abstract

The current development of manta ray robots is usually based on functional bionics, and there is a lack of bionic research to enhance the similarity of motion posture. To better exploit the characteristics of bionic, a similarity evaluation rule is constructed herein by a Dynamic Time Warping (DTW) algorithm to guide the optimization of the control parameters of a manta ray robot. The Central Pattern Generator (CPG) network with time and space asymmetry oscillation characteristics is improved to generate coordinated motion control signals for the robot. To optimize similarity, the CPG network is optimized with the genetic algorithm and particle swarm optimization (GAPSO) to solve the problems of multiple parameters, high non-linearity, and uncertain parameter coupling in the CPG network. The experimental results indicate that the similarity between the forward motion pose of the optimized manta ray robot and the manta ray is improved to 88.53%.