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Collective self-detection scheme for adaptive error detection in a foraging swarm of robots: 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings
University of York.
University of York.
Mälardalen University, School of Innovation, Design and Engineering. University of York. (Mälardalen Real-Time Research Centre)ORCID iD: 0000-0003-2415-8219
2011 (English)In: Artificial Immune Systems: 10th International Conference, ICARIS 2011, Cambridge, UK, July 18-21, 2011. Proceedings, Springer Berlin/Heidelberg, 2011, 254-267 p.Chapter in book (Other academic)
Abstract [en]

In this paper we present a collective detection scheme using receptor density algorithm to self-detect certain types of failure in swarm robotic systems. Key to any fault-tolerant system, is its ability to be robust to failure and have appropriate mechanisms to cope with a variety of such failures. In this work we present an error detection scheme based on T-cell signalling in which robots in a swarm collaborate by exchanging information with respect to performance on a given task, and self-detect errors within an individual. While this study is focused on deployment in a swarm robotic context, it is possible that our approach could possibly be generalized to a wider variety of multi-agent systems.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2011. 254-267 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 6825
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-23821DOI: 10.1007/978-3-642-22371-6_23ISBN: 978-3-642-22370-9 (print)OAI: oai:DiVA.org:mdh-23821DiVA: diva2:682429
Available from: 2013-12-27 Created: 2013-12-19 Last updated: 2014-01-20Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Language
  • de-DE
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Output format
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