Research on Route Planning based on improved Ant Colony Algorithm

Abstract

Abstract In order to enhance the safe flight performance of UAV and better complete complex tasks, it is extremely necessary to study route planning. Firstly, the feature points of the landform landform are extracted as the flight track points of the UAV, and the track planning problem is transformed into the traveling salesman problem. Secondly, an adaptive pheromone update method is proposed, and an improved ant colony algorithm for optimizing the local pheromone is proposed to avoid the basic ant colony algorithm from falling into the local optimal solution and improve the global search ability. Finally, the proposed algorithm is verified by simulation experiments. The experimental results show that the improved ant colony algorithm is practical and superior, and can effectively solve the problem of route planning and obtain the optimal path of route planning.