Optimal UAV flight path planning using skeletonization and Particle Swarm Optimizer
The purpose of this paper is to search the best flight route efficiently for unmanned aerial vehicle (UAV) in the 3-dimention complicated topography. The proposed method for the best flight route is mainly utilizing evolutionary algorithm, and give the proper initial population of evolutionary algorithm through skeletonization, efficient pre-processing procedure. In order to provide a smooth flight route for UAV, this paper adopts B-spline Curve method. Several control points of B-spline Curve method must be determined to generate flight route. The best control points can be calculated by Particle Swarm Optimizer (PSO). In this paper, the initial population of PSO is provided by skeletonization. The skeletonization of pre-processing procedure mainly includes two parts: one is Skeletonization and the other is candidate path searching. The purpose of pre-processing procedure is to reduce computation time, to prevent search the best solutions aimless, and execute evolutionary process efficiently. This paper uses Matlab as the experiment environment. The results of the experiments present the proposed method can provide the best flight route for UAV efficiently.