We study a range-constrained variant of the multi-UAV target search problem where commercially available UAVs are used for target search in tandem with ground-based mobile recharging vehicles (MRVs) that can travel, via the road network, to meet up with and recharge a UAV. We propose a pipeline for representing the problem on real-world road networks, starting with a map of the road network and yielding a final routing graph that permits UAVs to recharge via rendezvous with MRVs. The problem is then solved using mixed-integer linear programming (MILP) and constraint programming (CP). We conduct a comprehensive simulation of our methods using real-world road network data from Scotland. The assessment investigates accumulated search reward compared to ideal and worst-case scenarios and briefly explores the impact of UAV speeds. Our empirical results indicate that CP is able to provide better solutions than MILP, overall, and that the use of a fleet of MRVs can improve the accumulated reward of the UAV fleet, supporting their inclusion for surveillance tasks.

中文翻译：

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航程受限无人机和陆基移动充电车道路网络目标搜索

我们研究了多无人机目标搜索问题的范围受限变体，其中商用无人机与地面移动充电车 (MRV) 一起用于目标搜索，后者可以通过道路网络行驶，以满足和给无人机充电。我们提出了一个管道来表示现实世界道路网络上的问题，从道路网络地图开始，并产生最终的路线图，允许无人机通过与 MRV 会合进行充电。然后使用混合整数线性规划 (MILP) 和约束规划 (CP) 解决该问题。我们使用来自苏格兰的真实道路网络数据对我们的方法进行全面模拟。该评估调查了与理想和最坏情况相比的累积搜索奖励，并简要探讨了无人机速度的影响。