UAV Path Planning Based on an Improved Ant Colony Algorithm

Liu Huan, Ning Zhang, Qiang Li · 2021

In order to improve operational efficiency and survival probability, the optimal path of an UAV should be designed before the UAV performs a mission. The basic ant colony algorithm is easy to fall into the local optimum, and slow convergence speed. This paper improves the basic algorithm from two aspects: guidance factor and node pheromone update. The improved algorithm proposed in this paper can overcome the problems of the basic ant colony algorithm. The simulation results show that the improved ant colony algorithm is feasible for UAV path planning and the flight path optimization ability of UAV is improved.

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