Sharing the load
Sharing the load
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分担负载
DOI：
10.1109/mra.2009.932528
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发表时间：
2009
影响因子：
5.7
通讯作者：
Emilio Frazzoli
中科院分区：
文献类型：
--
作者：
M. Pavone;K. Savla;Emilio Frazzoli
在本文中，我们讨论了在分区策略框架中使用各种空间细分来确定移动机器人网络中的最佳工作负载共享。我们还提出了高效和空间分布的算法来实现这些细分，并且在代理之间最少或没有通信。由于篇幅限制，我们在本文中没有报道数值实验的结果，但提供了包含这些结果的出版物的参考书目和进一步的细节。有趣的是，当考虑相同基本问题（DTRP）的不同变体时，这些镶嵌出现了。因此，研究单一目标函数的存在性是很自然的，其最优值对应于这些不同变化下的各种镶嵌。博弈论的方法似乎很有前途。
In this article, we discussed the use of various spatial tessellations to determine, in the framework of partitioning policies, optimal workload share in a mobile robotic network. We also proposed efficient and spatially distributed algorithms for achieving some of these tessellations with minimum or no communication between the agents. Because of space limitations, we have not reported results of numerical experiments in this article but provided bibliographic references to publications containing such results and further details. It is interesting to note that these tessellations appear while considering different variations of the same basic problem (DTRP). It is then natural to investigate the existence of a single objective function, whose optima correspond to the various tessellations under these different variations. The game theory approach seems to be a promising one.