关键词: 蚁群算法, A*算法, 路径规划, 启发函数, ACS算法

Abstract: In view of the problem that the ant colony algorithm has a slow convergence speed and easily falls into the local optimal, an improved ant colony algorithm is proposed to solve the problem of robot path planning by combining the A star algorithm and ant colony algorithm. Adaptive adjustment of the heuristic function, in the later stage, using the evaluation function of the A star algorithm to extract the direction information in the heuristic function of the Ant Colony System（ACS） algorithm, and the search efficiency of the algorithm is improved. The direction information of the target is dynamic changed in the process of the ants moving to balance the relationship of the ACS algorithm between the diversity and the slow convergence rate. Simulation results show that the proposed algorithm not only improves the convergence rate, but also achieves good results in improving the quality of the solution.

Key words: ant colony algorithm, A star algorithm, path planning, heuristic information function, Ant Colony System（ACS） algorithm