Intelligent flight task algorithm for unmanned aerial vehicle

This paper proposes an intelligent flight task algorithm for unmanned aerial vehicles (UAV) to effectively determine and search the best flight routes in three-dimensional and complicated topographies, where the topography data includes the height of the object on the earth and the aerial imagery map of the earth is obtained by the Satellite. The proposed method is composed mainly of the particle swarm optimizer (PSO), skeletonization, and B-spline curve. Skeletonization is regarded as a pre-processing procedure for topography data to reduce complexity of the searching space and inhibit aimless searches of solutions. B-spline curve method is adopted to provide a smooth flight route for UAV. The best control points of a B-spline curve are determined by PSO. In this paper, the initial population of PSO is acquired through skeletonization to improve the efficiency of the search for the best flight route. The results of the simulation demonstrate the abilities of the proposed method to provide the best flight routes efficiently for UAV.