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Towards fault diagnosis in robot swarms: an online behaviour characterisation approach

Towards fault diagnosis in robot swarms: an online behaviour characterisation approach
Towards fault diagnosis in robot swarms: an online behaviour characterisation approach
Although robustness has been cited as an inherent advantage of swarm robotics systems, it has been shown that this is not always the case. Fault diagnosis will be critical for future swarm robotics systems if they are to retain their advantages (robustness, flexibility and scalability). In this paper, existing work on fault detection is used as a foundation to propose a novel approach for fault diagnosis in swarms based on a behavioural feature vector approach. Initial results show that behavioural feature vectors can be used to reliably diagnose common electro-mechanical fault types in most cases tested.
393-407
Springer
O’Keeffe, James
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Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4
Millard, Alan G
58064324-77bf-4ec7-ba6d-7c2763e02954
Timmis, Jon
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O’Keeffe, James
9c4912d0-fc1c-40c3-be76-b9c305c968d9
Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4
Millard, Alan G
58064324-77bf-4ec7-ba6d-7c2763e02954
Timmis, Jon
b68f4b8e-6192-4caf-858d-8185f6e7c66f

O’Keeffe, James, Tarapore, Danesh, Millard, Alan G and Timmis, Jon (2017) Towards fault diagnosis in robot swarms: an online behaviour characterisation approach. In Conference Towards Autonomous Robotic Systems. vol. 10454, Springer. pp. 393-407 . (doi:10.1007/978-3-319-64107-2_31).

Record type: Conference or Workshop Item (Paper)

Abstract

Although robustness has been cited as an inherent advantage of swarm robotics systems, it has been shown that this is not always the case. Fault diagnosis will be critical for future swarm robotics systems if they are to retain their advantages (robustness, flexibility and scalability). In this paper, existing work on fault detection is used as a foundation to propose a novel approach for fault diagnosis in swarms based on a behavioural feature vector approach. Initial results show that behavioural feature vectors can be used to reliably diagnose common electro-mechanical fault types in most cases tested.

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fault-diagnosis-robot - Accepted Manuscript
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e-pub ahead of print date: 20 July 2017
Published date: 2017

Identifiers

Local EPrints ID: 412673
URI: https://eprints.soton.ac.uk/id/eprint/412673
PURE UUID: 5b074b4b-396a-4ff0-8c03-a6d09ea340e4
ORCID for Danesh Tarapore: ORCID iD orcid.org/0000-0002-3226-6861

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Date deposited: 25 Jul 2017 16:31
Last modified: 12 Nov 2019 01:28

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Contributors

Author: James O’Keeffe
Author: Danesh Tarapore ORCID iD
Author: Alan G Millard
Author: Jon Timmis

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