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A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing

I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging mixed-reality technologies. This paper presents novel advances in the development of the interaction platform to generate 3D model...

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Detalles Bibliográficos
Autores principales: Malik, Ammar, Lhachemi, Hugo, Shorten, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374011/
https://www.ncbi.nlm.nih.gov/pubmed/37498853
http://dx.doi.org/10.1371/journal.pone.0289207
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author Malik, Ammar
Lhachemi, Hugo
Shorten, Robert
author_facet Malik, Ammar
Lhachemi, Hugo
Shorten, Robert
author_sort Malik, Ammar
collection PubMed
description I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging mixed-reality technologies. This paper presents novel advances in the development of the interaction platform to generate 3D models using both constructive solid geometry and artificial intelligence. In specific, by taking advantage of the generative capabilities of deep neural networks, the system has been automated to generate 3D models inferred from a single 2D image captured by the user. Furthermore, a novel generative neural architecture, SliceGen, has been proposed and integrated with the system to overcome the limitation of single-type genus 3D model generation imposed by differentiable-rendering-based deep neural architectures. The system also enables the user to adjust the dimensions of the 3D models with respect to their physical workspace. The effectiveness of the system is demonstrated by generating 3D models of furniture (e.g., chairs and tables) and fitting them into the physical space in a mixed reality environment. The presented developmental advances provide a novel and immersive form of interaction to facilitate the inclusion of a consumer into the design process for personal fabrication.
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spelling pubmed-103740112023-07-28 A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing Malik, Ammar Lhachemi, Hugo Shorten, Robert PLoS One Research Article I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging mixed-reality technologies. This paper presents novel advances in the development of the interaction platform to generate 3D models using both constructive solid geometry and artificial intelligence. In specific, by taking advantage of the generative capabilities of deep neural networks, the system has been automated to generate 3D models inferred from a single 2D image captured by the user. Furthermore, a novel generative neural architecture, SliceGen, has been proposed and integrated with the system to overcome the limitation of single-type genus 3D model generation imposed by differentiable-rendering-based deep neural architectures. The system also enables the user to adjust the dimensions of the 3D models with respect to their physical workspace. The effectiveness of the system is demonstrated by generating 3D models of furniture (e.g., chairs and tables) and fitting them into the physical space in a mixed reality environment. The presented developmental advances provide a novel and immersive form of interaction to facilitate the inclusion of a consumer into the design process for personal fabrication. Public Library of Science 2023-07-27 /pmc/articles/PMC10374011/ /pubmed/37498853 http://dx.doi.org/10.1371/journal.pone.0289207 Text en © 2023 Malik et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Malik, Ammar
Lhachemi, Hugo
Shorten, Robert
A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing
title A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing
title_full A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing
title_fullStr A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing
title_full_unstemmed A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing
title_short A cyber-physical system to design 3D models using mixed reality technologies and deep learning for additive manufacturing
title_sort cyber-physical system to design 3d models using mixed reality technologies and deep learning for additive manufacturing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374011/
https://www.ncbi.nlm.nih.gov/pubmed/37498853
http://dx.doi.org/10.1371/journal.pone.0289207
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