Mobile robot path planning in three-dimensional environment based on ACO-PSO hybrid algorithm

Abstract

A ACO-PSO hybrid algorithm is proposed in order to solve mobile robots path planning problem in three-dimensional environment. In this study, firstly, proposed a simple regulation for obstacles compartmentation in three-dimensional (3-D) environment, through which non-configurable terrain could be transformed into configurable terrain; established the environment model through Bitmap method based on the regulation, and divided 3-D movement domain for robots into transitable domain and impedient domain. Secondly, planed the paths of mobile robots through swarm intelligence algorithm. Ant colony optimization (ACO) was used to plan paths in robots transitable territory; particle swarm optimization (PSO) was applied to optimize the parameters of ACO, thus through ACO-PSO hybrid algorithm to deal with path planning problem. At last, carried on simulation experiments under two kinds of 3-D terrain; the results show that the method is efficient and feasible.