Mobile Robot Path Planning Based on Triangular Clip Ant Colony Algorithm

Abstract

In the running process of mobile robot equipment, the path planning to reach the specified target under the condition of known map modeling is an important topic. Traditional ant colony algorithm is an eight-degree-of-freedom search probabilistic algorithm derived from the foraging behavior of ant colony. Ant colony belongs to a class of intelligent path planning, which has good implementation effect in raster map path planning. However, the traditional ant colony algorithm has a simple choice of step size, which limits the efficiency of path planning of mobile robots. In this article, the triangular pruning ant colony algorithm is proposed, which introduces the guiding factor φ of target points and the inducing factor μ of obstacles, and effectively changes the way of path search. Experimental results show that compared with the traditional ant colony algorithm, it can improve convergence speed, improve the search efficiency and shorten the optimal path length under different grid environments.