Abstract
This paper focuses on the task planning problem for unmanned aerial vehicle (UAV) swarm. Considering the diverse requirements of different tasks, the variety of the execution capabilities of UAVs, and the effect of task execution sequence, the multi-type task allocation (MTTA) model is proposed with the objective of maximizing the global task execution reward, subject to the maximum flight length and limited operation ability of different UAVs, as well as the resource requirements and execution time window of different tasks. Moreover, the auction mechanism-based task allocation (AMTA) algorithm is proposed to allocate the conflict-free task sequences for UAVs. Simulation results demonstrate that the proposed AMTA algorithm outperforms the reference algorithm on performance in terms of total reward, path length, completion time, and energy consumption.
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