Wu Xiaojun, Gao Zhiyuan, Yuan Sheng, Hu Qiao, Dang Zerui
School of Software Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Shaanxi Key Laboratory of Intelligent Robots, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel). 2022 Mar 9;22(6):2122. doi: 10.3390/s22062122.
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.
针对异构无人水下航行器（UUV）集群的任务分配问题，本文提出了一种基于一致性算法的动态扩展共识束算法（DECBBA）。我们的算法考虑了每个UUV可以单独完成多个任务的多UUV任务分配问题，构建了一个“UUV-任务”匹配矩阵，并针对时间、路径和UUV航行的影响设计了新的边际效用、奖励和成本函数。此外，鉴于实际环境中限制UUV之间水声通信范围的不利因素，我们的算法通过在离散时间阶段更新UUV个体和任务完成状态，在负载平衡指标方面进行优化，完成了UUV集群的动态任务分配。在有通信约束的场景下，动态任务分配算法的性能指标（包括全局效用和任务完成率）能够很好地接近无通信约束理想场景下的静态算法。仿真实验结果表明，本文提出的算法能够快速有效地获得具有良好性能的UUV集群动态无冲突任务分配方案。
