Mobile Robot Path Planning Based on Improved Ant Colony Algorithm

Abstract

Aiming at the problem that traditional ant colony algorithm has path redundancy in mobile robots and is easy to fall into local optimal solutions, an improved ant colony algorithm is designed. First of all, analysis in the process of the ants moving, because they choose the path according to the roulette, the path has redundancy, retreat, and wave-like progress. It is difficult to find the optimal path. To solve this problem, this paper adopts path correction. The method to modify the path to the target point can effectively improve the convergence of the ant colony algorithm, and the optimal path obtained is shorter, while avoiding the pheromone update of some redundant paths from affecting the probability of the ant path selection in the later circle. Aiming at the obtained optimal path, optimize the path node to improve the path smoothness. It is verified by simulation that the improved ant colony algorithm has better convergence than traditional ant colony algorithm, reduces the number of nodes, and is more in line with the actual demands of robot movement.