A Study on the Path Planning Algorithm of the Unmanned Aerial Vehicle

The path planning of the unmanned aerial vehicle refers to the computation of the optimum or suboptimum executable flight path of the unmanned aerial vehicle from the starting position to the final position under the condition of meeting corresponding performance indexes and their dynamic constraints. Since the actual flight environment of the unmanned aerial vehicle, there are more constraint conditions that need to be met, and the key factors of solving the path planning of the unmanned aerial vehicle are how to conduct accurate modeling on environment and design the effective path planning algorithm. The path planning of the unmanned aerial vehicle is studied in this paper. A PSO-SA algorithm is proposed against the defect of the particle swarm optimization being easily trapped into local best, in which the particle state is updated through the simulated annealing probabilistic leap strategy. The simulation result indicates that the global search capability of the path can be enhanced, and the path planning time can be reduced through the algorithm, thereby optimizing the path.