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Auction-Based Task Allocation for Multi-robot Teams in Dynamic Environments

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Towards Autonomous Robotic Systems (TAROS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9287))

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Abstract

There has been much research on the use of auction-based methods to provide a distributed approach to task allocation for robot teams. Team members bid on tasks based on their locations, and the allocation is based on these bids. The focus of prior work has been on the optimality of the allocation, establishing that auction-based methods perform well in comparison with optimal allocation methods, with the advantage of scaling better. This paper compares several auction-based methods not on the optimality of the allocation, but on the efficiency of the execution of the allocated tasks giving a fuller picture of the practical use of auction-based methods. Our results show that the advantages of the best auction-based methods are much reduced when the robots are physically dispersed throughout the task space and when the tasks themselves are allocated over time.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Liverpool, Liverpool, UK

    Eric Schneider, Elizabeth I. Sklar & Simon Parsons

  2. Department of Informatics, King’s College London, London, UK

    Elizabeth I. Sklar

  3. Department of Computer Science, Graduate Center, City University of New York, New York, USA

    A. Tuna Özgelen

Authors
  1. Eric Schneider
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  2. Elizabeth I. Sklar
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  3. Simon Parsons
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  4. A. Tuna Özgelen
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Corresponding author

Correspondence to Eric Schneider .

Editor information

Editors and Affiliations

  1. University of Liverpool, Liverpool, United Kingdom

    Clare Dixon

  2. University of Liverpool, Liverpool, United Kingdom

    Karl Tuyls

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Schneider, E., Sklar, E.I., Parsons, S., Özgelen, A.T. (2015). Auction-Based Task Allocation for Multi-robot Teams in Dynamic Environments. In: Dixon, C., Tuyls, K. (eds) Towards Autonomous Robotic Systems. TAROS 2015. Lecture Notes in Computer Science(), vol 9287. Springer, Cham. https://doi.org/10.1007/978-3-319-22416-9_29

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  • DOI: https://doi.org/10.1007/978-3-319-22416-9_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22415-2

  • Online ISBN: 978-3-319-22416-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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