Research on path planning of mobile robot based on improved multi-step ant colony algorithm

Improved multi-step ant colony algorithm was proposed to solve the problems of traditional ant colony algorithm in path planning, such as poor practicability, slow convergence speed and local optimization. All the direct nodes in the field of view of the mobile robot for the improved algorithm were taken as the next optional node set, the multi-step moving method was used to find the next node in any direction and at any step length, and the optimization efficiency of the algorithm and the diversity of path planning was improved. The initial pheromones among nodes were unevenly distributed according to the distance between each node and the connecting line between current and target node, the blindness of ant colony search in the initial stage of the algorithm was reduced. By increasing the pheromone update gap between the high-quality path and the low-quality path through the path length, the heuristic function and the convergence speed of the algorithm was improved. The simulation results show that the improved algorithm has the advantages of short length, high smoothness and less steps, which are more in line with the actual needs of mobile robots. The convergence speed and the effect of path planning are significantly improved.