针对多无人机任务分配与协同航路规划问题，以分布式合同网拍卖算法为基础，构建无人机集群任务拍卖架构与拍卖收益函数，结合模拟退火算法协调任务执行次序，采用A*算法完成两任务点间航程预估，在任务分配阶段同步完成多无人机间协同航路的初规划，确定最佳任务执行次序，实现任务分配与协同航路规划的紧耦合。仿真结果表明，在考虑禁飞区、障碍威胁情况下，该算法能够有效完成多架无人机不同类型任务的分配，且目标分配、执行次序合理，总执行代价小，各机间负载均衡；在任务分配阶段考虑协同航路规划具有明显的效果，能够有效提高任务分配的合理性。
To solve the problem of task allocation and cooperative route planning for multiple unmanned aerial vehicles (UAVs), this paper takes the distributed contract network auction algorithm as the basis, designs auction architecture and auction revenue function of UAVs cluster, combines the simulated annealing algorithm to coordinate the task execution order, predicts the range between two task points using the A* algorithm, completes the initial planning of cooperative route among multiple unmanned aerial vehicles synchronously in the task allocation phase, determines the optimal task execution order, and achieves the tight coupling between the task allocation and cooperative route planning. The simulation results show that, considering the threat of no-fly zones and obstacles, this algorithm can effectively complete the assignment of different targets with reasonable target assignments and execution orders, low total execution cost, and balanced loads among the aircraft. In the stage of task assignment, it has obvious effect to consider cooperative route planning and can effectively improve the rationality of task allocation.
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