It is difficult for swarm robots to allocate tasks efficiently by self-organization in a dynamic unknown environment. The computational cost of swarm robots will be significantly increased for large-scale tasks, and the unbalanced task allocation of robots will also lead to a decrease in system efficiency. To address these issues, we propose a dynamic task allocation method of swarm robots based on optimal mass transport theory. The problem of large-scale tasks is solved by grouping swarm robots to complete regional tasks. The task reallocation mechanism realizes the balanced task allocation of individual robots. This paper solves the symmetric assignment between robot and task and between the robot groups and the regional tasks. Our simulation and experimental results demonstrate that the proposed method can make the swarm robots self-organize to allocate large-scale dynamic tasks effectively. The tasks can also be balanced allocated to each robot in the swarm of robots.

中文翻译：

---

基于最优传质理论的群机器人动态任务分配方法

群体机器人很难在动态未知环境中通过自组织有效地分配任务。对于大规模任务，群体机器人的计算成本会显着增加，机器人任务分配的不平衡也会导致系统效率的下降。为了解决这些问题，我们提出了一种基于最优质量传输理论的群机器人动态任务分配方法。大规模任务的问题是通过分组集群机器人完成区域任务来解决的。任务重分配机制实现了个体机器人的均衡任务分配。本文解决了机器人与任务之间、机器人组与区域任务之间的对称分配问题。我们的仿真和实验结果表明，所提出的方法可以使群机器人自组织以有效地分配大规模动态任务。任务也可以平衡分配给机器人群中的每个机器人。