Research on Dynamic Path Planning Algorithm of UAV

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. For the purpose of adjusting the path of the unmanned aerial vehicle timely in the case of emergency during flight, the PSO-AFSA algorithm is proposed in this paper, in which the artificial fish swarm optimizing strategy is introduced to the particle swarm optimization, the behavioral pattern of particles is selected through the behavior evaluation strategy of the artificial fish swarm, and the global best of particles is continuously updated through the bulletin board. The simulation result indicates that the algorithm can overcome the prematurity phenomenon of the particle swarm effectively, the rate of convergence is higher, and the simplified and safe flight path of the unmanned aerial vehicle can be planned quickly in three-dimensional dynamic environment.