Path guidance method for unmanned vehicle based on improved potential field ant colony algorithm

In order to overcome the problems of traditional path guidance methods such as long-time consumption and many intermediate nodes in path planning results, a path guidance method for unmanned vehicles based on improved potential field ant colony algorithm is designed in this paper. From improved potential field function, pheromone update process and heuristic function three-angle improved potential field of ant colony algorithm, improve the obstacle avoidance ability of ant colony individuals and search capabilities, and then by determining the starting point and focus of elliptic search scope, in order to improve the optimal planning path searching efficiency and can achieve the optimal guide path. Experimental results show that the maximum time to generate the path guidance scheme is only 3.7 s, the maximum TPI of the road is only 0.27, and the intermediate nodes of the planned path are the least and all paths are the shortest.