A Dual-Layer Weight-Leader-Vicsek Model for Multi-AGV Path Planning in Warehouse.

Lin, S; Liu, A; Wang, J

A Dual-Layer Weight-Leader-Vicsek Model for Multi-AGV Path Planning in Warehouse.

Lin, S Liu, A Wang, J

Permalink

Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Biomimetics (Basel), 2023, 8, (7), pp. 549
Issue Date:: 2023-11-15

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (1.21 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Lin, S
dc.contributor.author	Liu, A
dc.contributor.author	Wang, J https://orcid.org/0000-0002-6282-0456
dc.date.accessioned	2024-01-19T04:19:46Z
dc.date.available	2023-11-14
dc.date.available	2024-01-19T04:19:46Z
dc.date.issued	2023-11-15
dc.identifier.citation	Biomimetics (Basel), 2023, 8, (7), pp. 549
dc.identifier.issn	2313-7673
dc.identifier.issn	2313-7673
dc.identifier.uri	http://hdl.handle.net/10453/174802
dc.description.abstract	Multiple automatic guided vehicles are widely involved in industrial intelligence. Path planning is crucial for their successful application. However, achieving robust and efficient path planning of multiple automatic guided vehicles for real-time implementation is challenging. In this paper, we propose a two-layer strategy for multi-vehicle path planning. The approach aims to provide fast computation and operation efficiency for implementation. The start-destination matrix groups all the vehicles, generating a dynamic virtual leader for each group. In the first layer, the hybrid A* algorithm is employed for the path planning of the virtual leaders. The second layer is named leader-follower; the proposed Weight-Leader-Vicsek model is applied to navigate the vehicles following their virtual leaders. The proposed method can reduce computational load and achieve real-time navigation by quickly updating the grouped vehicles' status. Collision and deadlock avoidance is also conducted in this model. Vehicles in different groups are treated as dynamic obstacles. We validated the method by conducted simulations through MATLAB to verify its path-planning functionality and experimented with a localization sensor.
dc.format	Electronic
dc.language	eng
dc.publisher	MDPI
dc.relation.ispartof	Biomimetics (Basel)
dc.relation.isbasedon	10.3390/biomimetics8070549
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A Dual-Layer Weight-Leader-Vicsek Model for Multi-AGV Path Planning in Warehouse.
dc.type	Journal Article
utslib.citation.volume	8
utslib.location.activity	Switzerland
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 - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-19T04:19:44Z
pubs.issue	7
pubs.publication-status	Published online
pubs.volume	8
utslib.citation.issue	7

Abstract:

Multiple automatic guided vehicles are widely involved in industrial intelligence. Path planning is crucial for their successful application. However, achieving robust and efficient path planning of multiple automatic guided vehicles for real-time implementation is challenging. In this paper, we propose a two-layer strategy for multi-vehicle path planning. The approach aims to provide fast computation and operation efficiency for implementation. The start-destination matrix groups all the vehicles, generating a dynamic virtual leader for each group. In the first layer, the hybrid A* algorithm is employed for the path planning of the virtual leaders. The second layer is named leader-follower; the proposed Weight-Leader-Vicsek model is applied to navigate the vehicles following their virtual leaders. The proposed method can reduce computational load and achieve real-time navigation by quickly updating the grouped vehicles' status. Collision and deadlock avoidance is also conducted in this model. Vehicles in different groups are treated as dynamic obstacles. We validated the method by conducted simulations through MATLAB to verify its path-planning functionality and experimented with a localization sensor.

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

http://hdl.handle.net/10453/174802