Mechanism Selection for Multi-Robot Task Allocation
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 d...
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| Published in | Lecture notes in computer science pp. 421 - 435 |
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| Main Authors | , , |
| Format | Book Chapter |
| Language | English |
| Published |
Cham
Springer International Publishing
01.01.2017
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| Series | Lecture Notes in Computer Science |
| Subjects | |
| Online Access | Get full text |
| ISBN | 3319641069 9783319641065 |
| ISSN | 0302-9743 1611-3349 1611-3349 |
| DOI | 10.1007/978-3-319-64107-2_33 |
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| Summary: | 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. |
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| ISBN: | 3319641069 9783319641065 |
| ISSN: | 0302-9743 1611-3349 1611-3349 |
| DOI: | 10.1007/978-3-319-64107-2_33 |