关键词: 蚁群算法, 路径规划, 启发函数, 拐点评价函数

Abstract:

An improved ant colony algorithm for robot path planning is proposed based on the defects of the ant colony algorithm, such as slow convergence speed, easy to get into local optimization, and weak optimization ability in complex environment. An initial favorable pheromone matrix is established on the basis of pre-planned paths to effectively avoid blind search in the early stage of the algorithm to improve the directionality. The improved colony algorithm is fused with A* algorithm to further improve the directionality and convergence speed of algorithm search. The pheromone update rule introduces a turning evaluation function to improve the smoothness of the search path, improve the safety of robots and reduce energy consumption. A rollback strategy is proposed to effectively reduce the number of dead ants and improve the robustness of the algorithm search. Simulation experiments show that in the same environment, the improved ant colony algorithm performs better than other algorithms in search efficiency and convergence speed during the process of robot path planning.

Key words: ant colony algorithm, path planning, heuristic function, inflection point evaluation function