Optimizing Fuel-Constrained UAV-UGV Routes for Large Scale Coverage: Bilevel Planning in Heterogeneous Multi-Agent Systems

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). This cooperative routing of UAV-UGV multi-agent system to survey vast regions within their speed and fuel constraints is a computationally challenging problem, but can be simplified with heuristics. In this study, we utilize heuristic approaches to obtain feasible and near-optimal solutions to the problem, leveraging the fuel limitations of the UAV with the minimum set cover algorithm to identify the UGV refueling points. 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 are used to solve for the UGV and UAV route, respectively. Experimental validation on a smallscale testbed (http://tiny.cc/vancvz) underscores the effectiveness of our multi-agent approach.