UAV Path Planning Based on Improved Double Layer Ant Colony Evolutionary Algorithm
Aiming at the shortcomings of traditional ant colony algorithm in UAV path planning,such as initial blind search,slow convergence speed,and excessive number of turns,an improved double layer ant colony evo-lutionary algorithm is proposed,which divides ants into a guidance layer and an optimization layer.In the initial search stage of the algorithm,the suboptimal path is obtained by using A* algorithm,and the pheromones are distributed unevenly along this path.Next,a double layer search pattern is designed.Heuristic functions for the double layers of ants are designed separately.The base layer searches for the arrival path,while the optimiza-tion layer further searches for the optimization path.In the process of updating pheromones,the idea of evolu-tionary algorithms is incorporated to improve the diversity of ant populations.A pheromone enhancement and weakening factor is added to enhance the positive feedback mechanism of ant colony algorithms.Finally,the in-itial path is optimized to remove redundant nodes in both directions.The experiment results show that compared to the traditional ant colony algorithm,the improved algorithm has significant improvements in terms of iteration times,optimized path length,and turning times.
UAVpath planningdouble layer ant colony algorithmA*algorithmevolutionary algorithms
国家科技期刊平台
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