Path Planning for Deep Sea Mining Robot Based on ACO-PSO Hybrid Algorithm

Abstract

A ACO-PSO hybrid algorithm is proposed in order to resolve the path planning problem for deep-sea mining robots. In this study, the environment model was established by Bitmap method, and robot movement was simplified into particle movement by using Framework Space method. Ant colony optimization (ACO) is used to establish the corresponding solution, and some material algorithm steps are set out. Particle swarm optimization (PSO) is applied to optimize the parameters in ACO, and parameters can be selected self-adaptively. Results of simulation experiment demonstrate that this method can satisfy the precision demand of robots’ mining work in deep sea.