Mechanism Selection for Multi-Robot Task Allocation

被引：15

作者：

Schneider, Eric ^{[1
,2
]}

Sklar, Elizabeth I. ^{[1
]}

Parsons, Simon ^{[1
]}

机构：

[1] Kings Coll London, Dept Informat, London, England

[2] Univ Liverpool, Dept Comp Sci, Liverpool, Merseyside, England

来源：

TOWARDS AUTONOMOUS ROBOTIC SYSTEMS (TAROS 2017) | 2017年 / 10454卷

关键词：

Multi-robot team; Auction mechanism; Task allocation;

D O I：

10.1007/978-3-319-64107-2_33

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The work presented here investigates how environmental features can be used to help select a task allocation mechanism from a portfolio in a multi-robot exploration scenario. In particular, we look at clusters of task locations and the positions of team members in relation to cluster centres. In a data-driven approach, we conduct experiments that use two different task allocation mechanisms on the same set of scenarios, providing comparative performance data. We then train a classifier on this data, giving us a method for choosing the best mechanism for a given scenario. We show that selecting a mechanism via this method, compared to using a single state-of-the-art mechanism only, can improve team performance in certain environments, according to our metrics.

引用

页码：421 / 435

页数：15