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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/34979

Title: Decentralised vs partially centralised self-organisation model for mobile robots in large structure assembly
Authors: Ljasenko, Spartak
Ferreira, Pedro
Justham, Laura M.
Lohse, Niels
Keywords: Self-organisation
Mobile robots
Large structure assembly
Multi-agent systems
Issue Date: 2018
Publisher: Elsevier © The Authors
Citation: LJASENKO, S. ... et al., 2018. Decentralised vs partially centralised self-organisation model for mobile robots in large structure assembly. Computers in Industry, 104, pp.141-154.
Abstract: Currently, manufacturing companies are heavily investing into the automation of manufacturing processes. The push to improve productivity and efficiency is increasing the demand for more flexible and adaptable solutions than the currently common dedicated automation systems. In this paper, the planning problem for mobile robots in large structure assembly was addressed. Despite near-optimal results, the previously developed hybrid agent behaviour model was found to lack responsiveness and scalability. For that reason, an alternative, fully decentralised agent behaviour model was developed and compared to the hybrid one. Through simulated experiments, it was found that the decentralised agent behaviour model achieved much higher responsiveness; however, it required additional spare capacity to compensate for its decision-making imperfections.
Description: This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International licence (CC BY). Full details of this licence are available at https://creativecommons.org/licenses/by/4.0/
Sponsor: The authors acknowledge support from the EPSRC Centre for Innovative Manufacturing in Intelligent Automation, in undertaking this research work under grant reference number EP/IO33467/1.
Version: Published
DOI: 10.1016/j.compind.2018.09.002
URI: https://dspace.lboro.ac.uk/2134/34979
Publisher Link: https://doi.org/10.1016/j.compind.2018.09.002
ISSN: 0166-3615
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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