Improved ant colony algorithm of path planning for mobile robot

Abstract

An improved ant colony optimization algorithm – a differential evolution chaos ant colony optimization(DEACO) algorithm is proposed to plan the optimal collision-free path for a mobile robot in a complicated static environment.It utilizes differential evolution algorithm to update the pheromone,and appends the chaos disturbance factor in the updating process to avoid the possible stagnation phenomenon.Finally,a new evaluation criterion is employed to enhance the escaping capability of algorithm,avoid the path-locked situations and improve the efficiency in planning the optimal path.Simulation results indicate that an optimal and safe path which the robot moves on can be rapidly obtained even in a complicated geographical environment.The results are very satisfactory.