Abstract
Fast moving unmanned aerial vehicles (UAVs) are well suited for aerial surveillance, but are limited by their battery capacity. To increase their endurance UAVs can be refueled on slow moving unmanned ground vehicles (UGVs). The cooperative routing of UAV-UGV to survey vast regions within their speed and fuel constraints is a computationally challenging problem, but can be simplified with heuristics. Here we present multiple heuristics to enable feasible and sufficiently optimal solutions to the problem. Using the UAV fuel limits and the minimum set cover algorithm, the UGV refueling stops are determined. These refueling stops enable the allocation of mission points to the UAV and UGV. A standard traveling salesman formulation and a vehicle routing formulation with time windows, dropped visits, and capacity constraints is used to solve for the UGV and UAV route, respectively. Experimental validation of the approach on a small-scale testbed shows the efficacy of the approach.
Abstract (translated)
快速移动的无人飞行器(UAVs)非常适合空中监视,但受限于电池容量。为了增加它们的耐力,UAVs可以在缓慢移动的无人地面飞行器(UGVs)上充电。在UAV-UGV的合作路由中,探索在它们的速度和燃料限制内的广阔地区是一项计算密集型问题,但可以使用启发式方法简化这个问题。在这里,我们介绍了多个启发式方法,以使其能够找到可行的和足够最优的解决方案。使用UAVs的燃料限制和最小覆盖算法,确定了UGV的充电点。这些充电点使能够将任务点分配给UAV和UGV。使用标准的旅行推销员方案和具有时间窗口、辍学访问和容量限制的车辆路由方案,分别解决了UGV和UAV的路径。在小规模的测试床上进行了实验验证,证明了该方法的有效性。
URL
https://arxiv.org/abs/2303.02315
