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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8878014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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