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Collective Self-detection Scheme for Adaptive Error Detection in a Foraging Swarm of Robots

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Artificial Immune Systems (ICARIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6825))

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Abstract

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.

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Lau, H., Timmis, J., Bate, I. (2011). Collective Self-detection Scheme for Adaptive Error Detection in a Foraging Swarm of Robots. In: Liò, P., Nicosia, G., Stibor, T. (eds) Artificial Immune Systems. ICARIS 2011. Lecture Notes in Computer Science, vol 6825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22371-6_23

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  • DOI: https://doi.org/10.1007/978-3-642-22371-6_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22370-9

  • Online ISBN: 978-3-642-22371-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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