FUZZY LOGIC CONTROL FOR MULTI-ROBOT NAVIGATION AND ARRIVAL-TIME CONTROL IN A CLUTTERED ENVIRONMENT

Chang, Y-C; Shi, Y; Dostovalova, A; Lin, C-T; Kim, J; Gibbons, D

FUZZY LOGIC CONTROL FOR MULTI-ROBOT NAVIGATION AND ARRIVAL-TIME CONTROL IN A CLUTTERED ENVIRONMENT

Chang, Y-C Shi, Y Dostovalova, A Lin, C-T Kim, J Gibbons, D

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 International Conference on Machine Learning and Cybernetics (ICMLC), 2022, 2021-December, pp. 33-38
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Chang, Y-C
dc.contributor.author	Shi, Y
dc.contributor.author	Dostovalova, A
dc.contributor.author	Lin, C-T
dc.contributor.author	Kim, J
dc.contributor.author	Gibbons, D
dc.date	2021-12-04
dc.date.accessioned	2023-03-23T04:13:23Z
dc.date.available	2023-03-23T04:13:23Z
dc.date.issued	2022-01-01
dc.identifier.citation	2021 International Conference on Machine Learning and Cybernetics (ICMLC), 2022, 2021-December, pp. 33-38
dc.identifier.isbn	9781665466080
dc.identifier.issn	2160-133X
dc.identifier.issn	2160-1348
dc.identifier.uri	http://hdl.handle.net/10453/168193
dc.description.abstract	Coordination in multi-robot systems has attracted much attention in recent years. This study presents a hierarchical fuzzy controller (HiFC) to navigate a robot team and coordinate their moving speed and path for arrival time control. The proposed HiFC consists of multilayered architecture to reduce the number of free parameters and improve the scalability. The multilayered architecture includes a lower-level rule-embedded controller serving as behaviour selector and a higher-level fuzzy-logic-based coordinator to adjust each robot's moving speed and direction in the team. The HiFC is trained with a multi-objective multi-swarm evolutionary PSO (MMEPSO). Simulation results demonstrate the effectiveness of this technique in reliably solving the proposed navigation problem
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2021 International Conference on Machine Learning and Cybernetics (ICMLC)
dc.relation.ispartof	International Conference on Machine Learning and Cybernetics
dc.relation.ispartofseries	International Conference on Machine Learning and Cybernetics
dc.relation.isbasedon	10.1109/ICMLC54886.2021.9737264
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	FUZZY LOGIC CONTROL FOR MULTI-ROBOT NAVIGATION AND ARRIVAL-TIME CONTROL IN A CLUTTERED ENVIRONMENT
dc.type	Conference Proceeding
utslib.citation.volume	2021-December
utslib.location.activity	Adelaide, Australia
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-03-23T04:13:18Z
pubs.finish-date	2021-12-05
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2021-12-04
pubs.volume	2021-December
dc.location	Piscataway, USA

Abstract:

Coordination in multi-robot systems has attracted much attention in recent years. This study presents a hierarchical fuzzy controller (HiFC) to navigate a robot team and coordinate their moving speed and path for arrival time control. The proposed HiFC consists of multilayered architecture to reduce the number of free parameters and improve the scalability. The multilayered architecture includes a lower-level rule-embedded controller serving as behaviour selector and a higher-level fuzzy-logic-based coordinator to adjust each robot's moving speed and direction in the team. The HiFC is trained with a multi-objective multi-swarm evolutionary PSO (MMEPSO). Simulation results demonstrate the effectiveness of this technique in reliably solving the proposed navigation problem

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http://hdl.handle.net/10453/168193