Mobile Robot Path Planning Based on Improved Ant Colony Algorithm and DWA

Abstract

In view of the traditional ant colony algorithm in the mobile robot path planning in slow convergence speed, easy to trap into local optimum and weak dynamic programming problem, an improved ant colony algorithm fusion dynamic window approach (DWA) path planning method was proposed. Firstly, the heuristic function and pheromone update method were optimized to improve the path search ability. Secondly, the adaptive evaporation factor update strategy was introduced to dynamically adjust it, accelerate the convergence speed and search rate of the algorithm, and realize the global path planning of the mobile robot. Then, the improved ant colony algorithm was integrated with DWA to enhance the local dynamic obstacle avoidance ability of the robot. Finally, the redundant point deletion strategy and the secondary polyline optimization were used to effectively reduce the path turning point and improve the smoothness. The simulation results show that the improved fusion algorithm has improved convergence speed, path length and path smoothness, and can effectively avoid static and dynamic obstacles.