持续情报监视和侦察任务的多无人机路由
Multi-UAV Routing for Persistent Intelligence Surveillance & Reconnaissance Missions
摘要：
我们认为一个持久的情报，监视和侦察（PISR）路由问题，其中包括收集数据从一组指定的任务位置，并提供该数据的控制站。每个任务都根据其优先级分配一个刷新率，其中优先级较高的任务需要较高的刷新率。无人机团队的目标是最大限度地减少所有任务的数据到控制站的交付时间，同时满足每个任务的重访期约束。这个PISR路由问题的集中式路径规划问题，制定使用混合整数线性规划和使用分支和切割算法解决。启发式的次优可行解，需要更少的计算时间。该算法进行了测试，在几个实例和它们的性能进行了比较方面的最佳成本和计算时间。
英文摘要：
We consider a Persistent Intelligence, Surveillance and Reconnaissance (PISR) routing problem, which includes collecting data from a set of specified task locations and delivering that data to a control station. Each task is assigned a refresh rate based on its priority, where higher priority tasks require higher refresh rates. The UAV team's objective is to minimize the maximum of the delivery times of all the tasks' data to the control station, while simultaneously, satisfying each task's revisit period constraint. The centralized path planning problem for this PISR routing problem is formulated using mixed integer linear programming and solved using a branch-and-cut algorithm. Heuristics are presented to find sub-optimal feasible solutions that require much less computation time. The algorithms are tested on several instances and their performance is compared with respect to the optimal cost and computation time.
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