Unmanned Areal Vehicles (UAVs) can provide signicant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specic target locations within the area of interest. In order to improve the eectiveness of a reconnaissance mission, it is important to visit the largest number of interesting target locations possible, taking into consideration operational constraints related to fuel usage between target locations, weather conditions and endurance of the UAV. We model this planning problem as the well-known orienteering problem, which is a generalization of the traveling salesman problem. Given the uncertainty in the military operational environment, robust planning solutions are required. As such, our model takes into account uncertainty in the fuel usage between targets (for instance due to weather conditions) as well as uncertainty in the importance of visiting specic target locations. We report results using dierent uncertainty sets that specify the degree of uncertainty against which any feasible solution will be protected. We also compare the probability that a solution is feasible for the robust solution on one hand and the solution found with average fuel usage and expected value of information on the other. In doing so, we show how the sustainability of a UAV mission can be signicantly improved.
['Lanah Evers', 'Twan Dollevoet', 'Ana Isabel Barros', 'Herman Monsuur']
Robust UAV mission planning