  We present a waypoint planning algorithm for an unmanned aerial vehicle (UAV)
that is teamed with an unmanned ground vehicle (UGV) for the task of search and
rescue in a subterranean environment. The UAV and UGV are teamed such that the
localization of the UAV is conducted on the UGV via the multi-sensor fusion of
a fish-eye camera, 3D LIDAR, ranging radio, and a laser altimeter. Likewise,
the trajectory planning of the UAV is conducted on the UGV, which is assumed to
have a 3D map of the environment (e.g., from Simultaneous Localization and
Mapping). The goal of the planning algorithm is to satisfy the mission's
exploration criteria while reducing the localization error of the UAV by
evaluating the belief space for potential exploration routes. The presented
algorithm is evaluated in a relevant simulation environment where the planning
algorithm is shown to be effective at reducing the localization errors of the
UAV.
