  We present a hybrid compositional approach for real-time mission planning for
multi-rotor unmanned aerial vehicles (UAVs) in a time critical search and
rescue scenario. Starting with a known environment, we specify the mission
using Metric Temporal Logic (MTL) and use a hybrid dynamical model to capture
the various modes of UAV operation. We then divide the mission into several
sub-tasks by exploiting the invariant nature of safety and timing constraints
along the way, and the different modes (i.e., dynamics) of the UAV. For each
sub-task, we translate the MTL specifications into linear constraints and solve
the associated optimal control problem for desired path, using a Mixed Integer
Linear Program (MILP) solver. The complete path for the mission is constructed
recursively by composing the individual optimal sub-paths. We show by
simulations that the resulting suboptimal trajectories satisfy the mission
specifications, and the proposed approach leads to significant reduction in
computational complexity of the problem, making it possible to implement in
real-time. Our proposed method ensures the safety of UAVs at all times and
guarantees finite time mission completion. It is also shown that our approach
scales up nicely for a large number of UAVs.
