Application of Improved Ant Colony Algorithm in the Path Planning Problem of Mobile Robot
Min Cao, Yang Yang, Lianqing Wang · 2019
In this paper a global path planning method for mobile robots based on improved ant colony algorithm was proposed. Which overcome the problem that the traditional ant colony algorithm was prone to deadlock, may not get the global optimal solution and easily get into the local optimal problem. The transfer probability of ants in the traditional ant colony algorithm was adjusted to improve the occurrence of deadlock in the paper. And the roulette wheel algorithm in genetic algorithm was introduced to avoid the ant colony algorithm falling into the local optimal solution. At last the optimal parameter combination of the improved ant colony algorithm was obtained through simulation experiment. It could be seen from the simulation experimental data that the number of iterations to find the shortest path under the same conditions was reduced to 47.8%, which proved that the adoption of improved ant colony algorithm for path planning of mobile robot greatly improves the operating efficiency.