  We address the problem of achieving persistent surveillance over an
environment by using energy-constrained unmanned aerial vehicles (UAVs), which
are supported by unmanned ground vehicles (UGVs) serving as mobile charging
stations. Specifically, we plan the trajectories of all vehicles and the
charging schedule of UAVs to minimize the long-term maximum age, where age is
defined as the time between two consecutive visits to regions of interest in a
partitioned environment. We introduce a scalable planning strategy based on 1)
creating UAV- UGV teams, 2) decomposing the environment into optimal partitions
that can be covered by any of the teams in a single fuel cycle, 3) uniformly
distributing the teams over a cyclic path traversing those partitions, and 4)
having the UAVs in each team cover their current partition and be transported
to the next partition while being recharged by the UGV. We show some results
related to the safety and performance of the proposed strategy.
