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We investigate the problem of energy-constrained planning for a cooperativesystem of an Unmanned Ground Vehicles (UGV) and an Unmanned Aerial Vehicle(UAV). In scenarios where the UGV serves as a mobile base to ferry the UAV andas a charging station to recharge the UAV, we formulate a novelenergy-constrained routing problem. To tackle this problem, we design anenergy-aware routing algorithm, aiming to minimize the overall mission durationunder the energy limitations of both vehicles. The algorithm first solves aTraveling Salesman Problem (TSP) to generate a guided tour. Then, it employsthe Monte-Carlo Tree Search (MCTS) algorithm to refine the tour and generatepaths for the two vehicles. We evaluate the performance of our algorithmthrough extensive simulations and a proof-of-concept experiment. The resultsshow that our algorithm consistently achieves near-optimal mission time andmaintains fast running time across a wide range of problem instances.

Energy-Aware Routing Algorithm for Mobile Ground-to-Air Charging