For the large-scale operations of unmanned aerial vehicle (UAV) swarm and the large number of UAVs, this paper proposes a twolayer\ntask and resource assignment algorithm based on feature weight clustering. According to the numbers and types of task\nresources of each UAV and the distances between different UAVs, the UAV swarm is divided into multiple UAV clusters, and\nthe large-scale allocation problem is transformed into several related small-scale problems. A two-layer task assignment\nalgorithm based on the consensus-based bundle algorithm (CBBA) is proposed, and this algorithm uses different consensus\nrules between clusters and within clusters, which ensures that the UAV swarm gets a conflict-free task assignment solution in\nreal time. The simulation results show that the algorithm can assign tasks effectively and efficiently when the number of UAVs\nand targets is large.
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