Research on UAV Searching Path Planning Based on Improved Ant Colony Optimization Algorithm

Abstract

Aiming at the problems of slow convergence speed and easy to fall into local optimum when traditional ant colony algorithm is used in 3D path planning, a path planning method based on improved ant colony algorithm is proposed. The algorithm adjusts the initial pheromone content according to the distance between the node and the connection between the initial point and the target point and adopts an adaptive pheromone update strategy during the search process. The globality of the algorithm is effectively improved, and introducing distance heuristics and path safety factors into transition probability can improve the search efficiency and convergence speed of ants. Finally, the improved ant colony algorithm, dynamic programming algorithm and traditional ant colony algorithm are numerically simulated. The experimental results show that the improved ant colony algorithm converges faster and has a stronger ability to find the optimal solution. The research provides a solution for the optimization plan of UAV path planning.