Development of Swarm Intelligence Leader-Vicsek-Model for Multi-AGV Path Planning

Lin, S; Liu, A; Kong, X; Wang, J

Development of Swarm Intelligence Leader-Vicsek-Model for Multi-AGV Path Planning

Lin, S Liu, A Kong, X

Wang, J

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2021 20th International Symposium on Communications and Information Technologies (ISCIT), 2021, 00, pp. 49-54
Issue Date:: 2021-11-13

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Full metadata record

Field	Value	Language
dc.contributor.author	Lin, S
dc.contributor.author	Liu, A
dc.contributor.author	Kong, X https://orcid.org/0000-0001-7855-858X
dc.contributor.author	Wang, J https://orcid.org/0000-0002-6282-0456
dc.date	2021-10-19
dc.date.accessioned	2022-06-26T03:38:54Z
dc.date.available	2022-06-26T03:38:54Z
dc.date.issued	2021-11-13
dc.identifier.citation	2021 20th International Symposium on Communications and Information Technologies (ISCIT), 2021, 00, pp. 49-54
dc.identifier.isbn	9781665449588
dc.identifier.uri	http://hdl.handle.net/10453/158368
dc.description.abstract	Automatic guided vehicle (AGV) is the mobile robot widely used in the industry, and multiple AGVs are usually involved for industrial intelligence. Path planning for multi-AGV is essential for automatic transportation, and we propose a swarm-based approach that is inspired by biological subjects. The dynamic virtual leader is assigned for updating the locations and angles for the Leader-Vicsek-Model, and multiple agents are assigned through the centralized approach while the path planning is achieved through the decentralized method.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2021 20th International Symposium on Communications and Information Technologies (ISCIT)
dc.relation.ispartof	2021 20th International Symposium on Communications and Information Technologies
dc.relation.isbasedon	10.1109/iscit52804.2021.9590578
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Development of Swarm Intelligence Leader-Vicsek-Model for Multi-AGV Path Planning
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Tottori, Japan
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/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	embargoed	*
utslib.copyright.embargo	2023-11-30T00:00:00+1000Z
dc.date.updated	2022-06-26T03:38:53Z
pubs.finish-date	2021-10-22
pubs.publication-status	Published
pubs.start-date	2021-10-19
pubs.volume	00

Abstract:

Automatic guided vehicle (AGV) is the mobile robot widely used in the industry, and multiple AGVs are usually involved for industrial intelligence. Path planning for multi-AGV is essential for automatic transportation, and we propose a swarm-based approach that is inspired by biological subjects. The dynamic virtual leader is assigned for updating the locations and angles for the Leader-Vicsek-Model, and multiple agents are assigned through the centralized approach while the path planning is achieved through the decentralized method.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/158368