Optimization based coordinated UGV-MAV exploration for 2D augmented mapping

This paper presents a novel optimization formulation for coordinated exploration between unmanned ground vehicles (UGV) and micro-aerial vehicles (MAV). The exploration is posed as an Integer Programming (IP) problem and the allotment of these vehicles(agents) to frontier locations is specified as an integer constraint. The optimization provides a one shot solution for the allotment of all such active agents to possible frontier locations thereby guaranteeing substantial performance gain over previous approaches where the allotment proceeds in an incremental fashion. We also show a practical realization of such an exploration where an UGV-MAV team efficiently builds a map of an indoor environment.