An emergency refuelling problem over a dynamically changing environment in the context of Unmanned Aerial Vehicles

In general routing problems are adapted to the application domain while incorporating constraints and special conditions. Depending on the problem, the classical static shortest path algorithm may be proved unrealized due to insufficient energy reserves. Motivated from the analysis in (Economou et al., 2007) where graph theory tools were utilized in the UAV (unmanned aerial vehicle) context for the static routing problem. The paper presents methods for determining the shortest path while conserving propulsion energy for the overall mission when a dynamically changing environment is concerned. Additional constraints can be incorporated when an adequate refuelling station is also needed in order to reach a goal, thus including real world conditions in the methodology. The later is considered using location theory tools. The overall methodology is illustrated through a simple simulation example where a UAV, with finite fuel reserves, has a task to traverse a dynamically changing environment from a particular starting point towards a goal and passing through an intermediate refuelling point, while minimizing energy requirements.