Collaborative Target Search for Multiple UAVs Based on Collaborative Particle Swarm Optimization Genetic Algorithm

Abstract

AbstractIn order to solve the problem of poor target and low efficiency of multi-UAV search in uncertain environment, this paper proposes a multi-UAV collaborative path search algorithm based on collaborative search and particle swarm optimization. First, a regional raster map environment and a search probability map model are established, then a rolling prediction method is adopted, and a collaborative particle swarm genetic algorithm is used to generate a prediction path. Finally, the optimal prediction search path is calculated by the fitness function. The path satisfies the minimum turning radius constraint of the UAV, while avoiding the threat area and strengthening the search for key areas. The UAV moves a waypoint along the optimal prediction search path, and enters the next search path. Before each waypoint path search, it updates the raster map probability according to Bayesian formula until the end of the task. Simulation results verify the effectiveness of the proposed algorithm.KeywordsMultiple UAVsCollaborative searchCollaborative particle swarm optimization genetic algorithmSearch probability graph