Target Search on Road Networks with Range-Constrained UAVs and Ground-Based Mobile Recharging Vehicles

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.