Research on multi-UAV hierarchical task allocation in large-scale scenarios

Abstract

Abstract The task allocation problem of multiple UAVs in large-scale scenarios has the characteristics of large amount of computation, poor real-time performance, non-convergence or slow convergence. Therefore, this paper designs a hierarchical task allocation method to solve the task allocation problem when multiple UAVs perform large-scale tasks. The problem is divided into two sub-problems, task clustering and task ranking, by using a hierarchical structure, which effectively reduces the scale of solution. The high-level task clustering is used to determine which UAV performs which tasks, and the clustering algorithm based on auction criteria is used to perform task clustering; the bottom-level task sorting is used to obtain the best task execution sequence for the UAV to perform its corresponding tasks. The ant colony algorithm(ACO) is used to sort tasks. The simulation results show that the proposed algorithm can effectively solve the multi-UAV large-scale task allocation problem, and has good realtime performance and convergence.