Various missions carried out by Unmanned Aerial Vehicles (UAVs) are concerned with permanent monitoring of a predefined set of ground targets under relative deadline constraints, i.e., the targets have to be revisited 'indefinitely' and there is an upper bound on the time between two consecutive successful scans of each target. A solution to the problem is a set of routes-one for each UAV-that jointly satisfy these constraints. Our goal is to find a solution with the least number of UAVs. We show that the decision version of the problem (given k, is there a solution with k UAVs?) is PSPACE-complete. On the practical side, we propose a portfolio approach that combines the strengths of constraint solving and model checking. We present an empirical evaluation of the different solution methods on several hundred randomly generated instances.
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