Coordinated Optimization Algorithm Combining GA with Cluster for Multi-UAVs to Multi-tasks Task Assignment and Path Planning

Abstract

With the rapid development of UAVs, the application of UAVs in civil and military fields has greatly expanded. UAVs are often used to perform tasks in hazardous areas. In order to ensure the rapid execution of critical tasks, it is critical to determine the number of UAVs to be dispatched and to find the path for each UAV to perform tasks. This paper proposes a coordinated optimization algorithm combing the GA and cluster algorithm to resolve the problem of multi-UAVs to multi-tasks task assignment and path planning, which can effectively determine the amount of UAVs satisfies with the mission time constraint and find the best task flight path for each UAV simultaneously. The simulation results demonstrate that the coordination optimization algorithm is effective to resolve this kind of task assignment problem. The comparison between the coordinated optimization algorithm and GA is performed, and the result shows that the coordinated optimization algorithm is more effective than GA.