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A Multi-User Collaborative AR System for Industrial Applications

Augmented reality (AR) applications are increasingly being used in various fields (e.g., design, maintenance, assembly, repair, training, etc.), as AR techniques help improve efficiency and reduce costs. Moreover, collaborative AR systems extend applicability, allowing for collaborative environments...

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Detalles Bibliográficos
Autores principales: Wang, Junyi, Qi, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878014/
https://www.ncbi.nlm.nih.gov/pubmed/35214221
http://dx.doi.org/10.3390/s22041319
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author Wang, Junyi
Qi, Yue
author_facet Wang, Junyi
Qi, Yue
author_sort Wang, Junyi
collection PubMed
description Augmented reality (AR) applications are increasingly being used in various fields (e.g., design, maintenance, assembly, repair, training, etc.), as AR techniques help improve efficiency and reduce costs. Moreover, collaborative AR systems extend applicability, allowing for collaborative environments for different roles. In this paper, we propose a multi-user collaborative AR system (aptly called the “multi-user collaborative system”, or MUCSys); it is composed of three ends—MUCStudio, MUCView, and MUCServer. MUCStudio aims to construct industrial content with CAD model transformation, simplification, database update, marker design, scene editing, and exportation, while MUCView contains sensor data analysis, real-time localization, scene loading, annotation editing, and virtual–real rendering. MUCServer—as the bridge between MUCStudio and MUCView—presents collaborative and database services. To achieve this, we implemented the algorithms of local map establishment, global map registration, optimization, and network synchronization. The system provides AR services for diverse industrial processes via three collaborative ways—remote support, collaborative annotation, and editing. According to the system, applications for cutting machines were presented to improve efficiency and reduce costs, covering cutting head designs, production line sales, and cutting machine inspections. Finally, a user study was performed to prove the usage experience of the system.
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spelling pubmed-88780142022-02-26 A Multi-User Collaborative AR System for Industrial Applications Wang, Junyi Qi, Yue Sensors (Basel) Article Augmented reality (AR) applications are increasingly being used in various fields (e.g., design, maintenance, assembly, repair, training, etc.), as AR techniques help improve efficiency and reduce costs. Moreover, collaborative AR systems extend applicability, allowing for collaborative environments for different roles. In this paper, we propose a multi-user collaborative AR system (aptly called the “multi-user collaborative system”, or MUCSys); it is composed of three ends—MUCStudio, MUCView, and MUCServer. MUCStudio aims to construct industrial content with CAD model transformation, simplification, database update, marker design, scene editing, and exportation, while MUCView contains sensor data analysis, real-time localization, scene loading, annotation editing, and virtual–real rendering. MUCServer—as the bridge between MUCStudio and MUCView—presents collaborative and database services. To achieve this, we implemented the algorithms of local map establishment, global map registration, optimization, and network synchronization. The system provides AR services for diverse industrial processes via three collaborative ways—remote support, collaborative annotation, and editing. According to the system, applications for cutting machines were presented to improve efficiency and reduce costs, covering cutting head designs, production line sales, and cutting machine inspections. Finally, a user study was performed to prove the usage experience of the system. MDPI 2022-02-09 /pmc/articles/PMC8878014/ /pubmed/35214221 http://dx.doi.org/10.3390/s22041319 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Junyi
Qi, Yue
A Multi-User Collaborative AR System for Industrial Applications
title A Multi-User Collaborative AR System for Industrial Applications
title_full A Multi-User Collaborative AR System for Industrial Applications
title_fullStr A Multi-User Collaborative AR System for Industrial Applications
title_full_unstemmed A Multi-User Collaborative AR System for Industrial Applications
title_short A Multi-User Collaborative AR System for Industrial Applications
title_sort multi-user collaborative ar system for industrial applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878014/
https://www.ncbi.nlm.nih.gov/pubmed/35214221
http://dx.doi.org/10.3390/s22041319
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