Energy-Aware Collaborative Teaming and Route Planning for Unmanned Ground Vehicles

Given a list of unordered spatial tasks to be completed by a team of unmanned ground vehicles (UGVs), this paper outlines a mission planning formulation that solves for task assignments, charging rendezvous between worker UGVs and a mobile charging host UGV, and plans routes that minimize overall energy usage and task completion time for the team. When energy capacity constraints are imposed for the charging host, which is allowed to only re-charge at the depot, we find that mixed-integer solvers for the mission planner fail to converge to exact solutions even for small team sizes and number of tasks. To reduce the computational burden of the mission planner, we incorporate a k-means clustering algorithm for the pre-assignment of tasks to specific UGV sub-teams. Demonstrative results are included showing the benefits of this approach against a less formal rule-based approach.