Energy-aware aerial vehicle deployment via bipartite graph matching

This paper proposes a multi-robot path planning and optimal deployment strategy for a team of micro air vehicles with limited energy reserves and finite recharge times. We focus on deployments which seek to balance individual and cooperative vehicle task requirements with overall travel and energy costs and charging station availability toward enabling extended duration operation. We formulate the deployment approach as a matching problem that builds upon a deterministic navigation graph of both edge and vertex weighted. By relating the charging stations to the weighting policy of graph vertices, a set of navigation paths transiting nearby charging stations can be obtained for those low energy aerial vehicles. Simulation results validate the proposed deployment approach and analyze performance variability due to changes in available energy resources and team size.