State-space search for improved autonomous UAVs assignment algorithm

This paper describes an algorithm that generates vehicle task assignments for autonomous uninhabited air vehicles in cooperative missions. The algorithm uses a state-space best-first search of a tree that incorporates all of the constraints of the assignment problem. Using this algorithm a feasible solution is generated immediately, that monotonically improves and eventually converges to the optimal solution. Using Monte Carlo simulations the performance of the search algorithm is analyzed and compared to the desirable assignment algorithm attributes. It is shown that the proposed deterministic search method can be implemented for given run times, providing good feasible solutions.