Particle Swarm Network Design for UCAV Intelligence System Path Planning

Abstract

In military battle, the unmanned combat aerial vehicle (UCAV) plays a critical role. The UCAV avoids the fatal military zone as well as radars. If there is just a narrow path between the defensive areas, it is dan-gerous. It chooses the quickest and safest path. The balance evolution technique is used to improve the path planning of UCAV in this study, which results in a novel artificial bee colony. To regulate the position of a swarm of UCAVs, a particle swarm network is used to communicate between the UCAVs in the swarm. According to simulation data, the particle swarm network technique is more efficient than the ABC ap-proach. The intelligence system is taught via an artificial neural network.