Hierarchical Task Assignment for Multi-UAV System in Large-Scale Group-to-Group Interception Scenarios

The multi-UAV task assignment problem in large-scale group-to-group interception scenarios presents challenges terms of large computational complexity and the lack accurate evaluation models. This paper proposes an effective model hierarchical framework to address these challenges. incorporates dynamics constraints specific fixed-wing UAVs improves Apollonius circle accurately describe cooperative effectiveness multiple UAVs. By evaluating during process, scheme could be given based on model. To optimize configuration targets, a network flow algorithm is employed. utilizes clustering method feature similarity advantage decompose into smaller, complete submodels. Following assignment, Dubins curves are planned optimal points, ensuring task. Simulation results demonstrate feasibility proposed scheme. With increase scale, has greater descending rate runtime. In scenario involving 200 100 runtime reduced by 84.86%.