  Multi Agent Path Finding (MAPF) seeks the optimal set of paths for multiple
agents from respective start to goal locations such that no paths conflict. We
address the MAPF problem for a fleet of hybrid-fuel unmanned aerial vehicles
which are subject to location-dependent noise restrictions. We solve this
problem by searching a constraint tree for which the subproblem at each node is
a set of shortest path problems subject to the noise and fuel constraints and
conflict zone avoidance. A labeling algorithm is presented to solve this
subproblem, including the conflict zones which are treated as dynamic
obstacles. We present the experimental results of the algorithms for various
graph sizes and number of agents.
