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Task Partitioning in Swarms of Robots: Reducing Performance Losses Due to Interference at Shared Resources

机译:机器人群中的任务划分:减少由于共享资源的干扰而导致的性能损失

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The performance of large groups of robots is often limited by a commonly shared resource. This effect, termed interference, can have a large impact on robotic swarms. This article studies the issue of interference in a swarm of robots working on a harvesting task. The environment of the robots is spatially constrained, i.e., there is a commonly shared resource, the nest, which limits the group's performance when used without any arbitration mechanism. The article studies the use of task partitioning for reducing concurrent accesses to the resource, and therefore limiting the impact of interference on the group's performance. In our study, we spatially partition the environment into two subparts, thereby partitioning the corresponding harvesting task as well. We employ a simple method to allocate individuals to the partitions. The approach is empirically studied both in an environment with a narrow nest area and an environment without this constraint. The results of the task partitioning strategy are analyzed and compared to the case in which task partitioning is not employed.
机译:大型机器人的性能通常受共享资源的限制。这种影响称为干扰,会对机器人群产生重大影响。本文研究了一群从事收割任务的机器人的干扰问题。机器人的环境在空间上受到限制,即存在一个共同共享的资源,即巢,这在不使用任何仲裁机制的情况下会限制组的性能。本文研究了任务分区的使用,以减少对资源的并发访问,从而限制了干扰对组性能的影响。在我们的研究中,我们将环境在空间上分为两个子部分,从而也将相应的收获任务也进行了划分。我们采用一种简单的方法将个人分配到分区。在嵌套区域狭窄的环境和没有此限制的环境中都对这种方法进行了经验研究。分析了任务划分策略的结果,并与未采用任务划分的情况进行了比较。

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