Cooperative Task Assignment and Path Planning of Multiple UAVs Using Genetic Algorithm

Abstract

This paper addresses the task assignment and path planning problem of multiple UAVs. As one of the strategies for a SEAD(Suppressions of Enemy Air Defense) mission, an efficiency strategy for assignment and path planning of homogeneous UAVs is developed. There are many path planning methods (e.g. potential function method or probabilistic roadmap method) to avoid obstacles, but the Voronoi diagram is used for the path planning with avoiding the “No fly zones” in this study. Since several candidate-paths are needed to solve the problem of timing constraints, the flyable paths in the shape of net is generated by using Voronoi diagram and multiple paths are found as the candidate paths from each UAV to each target. The objective function is determined as accumulated sum of the required time to finish the tasks on each target and the optimization is achieved by using genetic algorithm with appropriate representation of chromosome and genetic operators.