Vehicle routing problem for persistent uav service

Abstract

The duration of missions that can be accomplished by unmanned aerial vehicles (UAVs) is limited by the battery or fuel capacity of its constituent UAVs. However, a system of UAVs that is supported by auto-mated refueling bases may support long term or even indefinite duration missions in a near autonomous mode. The UAVs can return to a base, replenish their resources and resume their duties. We develop a mixed integer linear program model to formalize the problem of scheduling such a system that includes multiple bases in disparate geographic locations that are shared between the UAVs. The system consists of a heterogeneous fleet of UAVs (each with different travel speed and distance capabilities), refuel stations and mission trajectories that must be followed by at least one UAV. A UAV may hand off the mission to another in order to return to base for a fuel recharge. For our persistent UAV observing service, we introduce new VRP that is distance constrained heterogeneous VRP with time window, multi-depot route and multiple trips. For the small size example problems, a state of-the-art MILP solver such as CPLEX is sufficient to create a schedule for the model. However, for the large size example problems or dynamic environment, CPLEX turned out that it is not sufficient to create a schedule due to the complexity of this problem. Therefore, to overcome the computation limit of CPLEX, RHTAm was developed and the results are compared with that of CPLEX. This is the first time that a generic scheduling model has been developed that allows mobile agents to return to service after refueling across multiple bases. In practice, the approach allows for a long-term mission to receive uninterrupted UAV service by successively handing off the task to replacement UAVs served by geographically distributed shared bases.

A fleet of unmanned aerial vehicles (UAVs) supported by logistics infrastructure, such as automated service stations, may be capable of long-term persisten...