Abstract:Task allocation is crucial to improve the efficiency when UUV performs large-scale searching tasks. This paper solves the task allocation problem of UUV swarm in multi-area searching, so that the completion time of area searching is minimized. Aiming at the problem that the traditional Hungarian algorithm cannot solve the problem of unbalanced task allocation, an improved Hungarian multi-round allocation algorithm is proposed. This algorithm achieves efficient utilization of idle UUVs and allocating multiple UUVs to target areas in multiple rounds. By introducing the marginal cost and conservative estimating time in the cost function, the completion time of area searching is greatly reduced. The simulation experiment results show that the algorithm proposed in this article can allocate idle UUVs and improve allocation efficiency compared with the traditional Hungarian algorithm. In addition, compared with the algorithm only using the search time as the cost function, our algorithm can shorten the search time as much as possible for long-time-consuming areas, ensuring that the completion time of area searching decreases monotonically as the number of UUVs increases.
