O'Keefe, James, Tarapore, Danesh Sarosh orcid.org/0000-0002-3226-6861, Millard, Alan Gregory orcid.org/0000-0002-4424-5953 et al. (1 more author) (2018) Adaptive Online Fault Diagnosis in Autonomous Robot Swarms. Frontiers in Robotics and AI. 131. ISSN 2296-9144
Abstract
Previous work has shown that robot swarms are not always tolerant to the failure of individual robots, particularly those that have only partially failed and continue to contribute to collective behaviors. A case has been made for an active approach to fault tolerance in swarm robotic systems, whereby the swarm can identify and resolve faults that occur during operation. Existing approaches to active fault tolerance in swarms have so far omitted fault diagnosis, however we propose that diagnosis is a feature of active fault tolerance that is necessary if swarms are to obtain long-term autonomy. This paper presents a novel method for fault diagnosis that attempts to imitate some of the observed functions of natural immune system. The results of our simulated experiments show that our system is flexible, scalable, and improves swarm tolerance to various electro-mechanical faults in the cases examined
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 O’Keeffe, Tarapore, Millard and Timmis |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 30 Nov 2018 09:30 |
Last Modified: | 16 Oct 2024 15:17 |
Published Version: | https://doi.org/10.3389/frobt.2018.00131 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.3389/frobt.2018.00131 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139442 |
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Filename: frobt_05_00131.pdf
Description: Adaptive Online Fault Diagnosis in Autonomous Robot Swarms
Licence: CC-BY 2.5