Globally Optimal Assignment Algorithm for Collective Object Transport Using Air-Ground Multirobot Teams

Abstract

We consider the problem of collectively transporting multiple objects using air-ground multirobot teams. The objective is to find the optimal matching between the objects and aerial/ground robots that minimizes the energy of the overall system. We reveal the local optimality criteria for this combinatorial problem and prove that combining a branch and bound algorithm with a negative-cycle canceling algorithm (NCCA) yields an efficient algorithm that provides the globally optimal solution of the problem. Numerical experiments demonstrate the performance on practical problems.