A Dynamic Task Allocation Algorithm for Heterogeneous UUV Swarms

Abstract

Aiming at the task allocation problem of heterogeneous unmanned underwater vehicle (UUV) swarms, this paper proposes a dynamic extended consensus-based bundle algorithm (DECBBA) based on consistency algorithm. Our algorithm considers the multi-UUV task allocation problem that each UUV can individually complete multiple tasks, constructs a “UUV-task” matching matrix and designs new marginal utility, reward and cost functions for the influence of time, path and UUV voyage. Furthermore, in view of the unfavorable factors that restrict the underwater acoustic communication range between UUVs in the real environment, our algorithm complete dynamic task allocation of UUV swarms with optimization in load balance indicator by the update of the UUV individual and the task completion status in the discrete time stage. The performance indicators (including global utility and task completion rate) of the dynamic task allocation algorithm in the scenario with communication constraints can be well close to the static algorithm in the ideal scenario without communication constraints. The simulation experiment results show that the algorithm proposed in this paper can quickly and efficiently obtain the dynamic and conflict-free task allocation assignment of UUV swarms with great performance.