AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2024
Rosati, R.; Senesi, P.; Lonzi, B.; Mancini, A.; Mandolini, M.
An automated CAD-to-XR framework based on generative AI and Shrinkwrap modelling for a User-Centred design approach Journal Article
In: Advanced Engineering Informatics, vol. 62, 2024, ISSN: 14740346 (ISSN).
Abstract | Links | BibTeX | Tags: Adversarial networks, Artificial intelligence, CAD-to-XR, Computer aided design models, Computer aided logic design, Computer-aided design, Computer-aided design-to-XR, Design simplification, Digital elevation model, Digital storage, Extended reality, Flow visualization, Generative adversarial networks, Guns (armament), Helmet mounted displays, Intellectual property core, Mixed reality, Photo-realistic, Shrinkfitting, Structural dynamics, User centered design, User-centered design, User-centered design approaches, User-centred, Virtual Prototyping, Work-flows
@article{rosati_automated_2024,
title = {An automated CAD-to-XR framework based on generative AI and Shrinkwrap modelling for a User-Centred design approach},
author = {R. Rosati and P. Senesi and B. Lonzi and A. Mancini and M. Mandolini},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204897460&doi=10.1016%2fj.aei.2024.102848&partnerID=40&md5=3acce73b986bed7a9de42e6336d637ad},
doi = {10.1016/j.aei.2024.102848},
issn = {14740346 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Advanced Engineering Informatics},
volume = {62},
abstract = {CAD-to-XR is the workflow to generate interactive Photorealistic Virtual Prototypes (iPVPs) for Extended Reality (XR) apps from Computer-Aided Design (CAD) models. This process entails modelling, texturing, and XR programming. In the literature, no automatic CAD-to-XR frameworks simultaneously manage CAD simplification and texturing. There are no examples of their adoption for User-Centered Design (UCD). Moreover, such CAD-to-XR workflows do not seize the potentialities of generative algorithms to produce synthetic images (textures). The paper presents a framework for implementing the CAD-to-XR workflow. The solution consists of a module for texture generation based on Generative Adversarial Networks (GANs). The generated texture is then managed by another module (based on Shrinkwrap modelling) to develop the iPVP by simplifying the 3D model and UV mapping the generated texture. The geometric and material data is integrated into a graphic engine, which allows for programming an interactive experience with the iPVP in XR. The CAD-to-XR framework was validated on two components (rifle stock and forend) of a sporting rifle. The solution can automate the texturing process of different product versions in shorter times (compared to a manual procedure). After each product revision, it avoids tedious and manual activities required to generate a new iPVP. The image quality metrics highlight that images are generated in a “realistic” manner (the perceived quality of generated textures is highly comparable to real images). The quality of the iPVPs, generated through the proposed framework and visualised by users through a mixed reality head-mounted display, is equivalent to traditionally designed prototypes. © 2024 The Author(s)},
keywords = {Adversarial networks, Artificial intelligence, CAD-to-XR, Computer aided design models, Computer aided logic design, Computer-aided design, Computer-aided design-to-XR, Design simplification, Digital elevation model, Digital storage, Extended reality, Flow visualization, Generative adversarial networks, Guns (armament), Helmet mounted displays, Intellectual property core, Mixed reality, Photo-realistic, Shrinkfitting, Structural dynamics, User centered design, User-centered design, User-centered design approaches, User-centred, Virtual Prototyping, Work-flows},
pubstate = {published},
tppubtype = {article}
}
CAD-to-XR is the workflow to generate interactive Photorealistic Virtual Prototypes (iPVPs) for Extended Reality (XR) apps from Computer-Aided Design (CAD) models. This process entails modelling, texturing, and XR programming. In the literature, no automatic CAD-to-XR frameworks simultaneously manage CAD simplification and texturing. There are no examples of their adoption for User-Centered Design (UCD). Moreover, such CAD-to-XR workflows do not seize the potentialities of generative algorithms to produce synthetic images (textures). The paper presents a framework for implementing the CAD-to-XR workflow. The solution consists of a module for texture generation based on Generative Adversarial Networks (GANs). The generated texture is then managed by another module (based on Shrinkwrap modelling) to develop the iPVP by simplifying the 3D model and UV mapping the generated texture. The geometric and material data is integrated into a graphic engine, which allows for programming an interactive experience with the iPVP in XR. The CAD-to-XR framework was validated on two components (rifle stock and forend) of a sporting rifle. The solution can automate the texturing process of different product versions in shorter times (compared to a manual procedure). After each product revision, it avoids tedious and manual activities required to generate a new iPVP. The image quality metrics highlight that images are generated in a “realistic” manner (the perceived quality of generated textures is highly comparable to real images). The quality of the iPVPs, generated through the proposed framework and visualised by users through a mixed reality head-mounted display, is equivalent to traditionally designed prototypes. © 2024 The Author(s)
2023
Nazareth, I.; Gao, K.
(Un)real Estates Proceedings Article
In: ACM Int. Conf. Proc. Ser., pp. 179–186, Association for Computing Machinery, 2023, ISBN: 979-840071635-5 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Commercialisation, Counterfactuals, Digital counterparts, Digital storage, Digital Twins, Metaverse, Metaverses, Platform Technology, Probability distributions, Real-estates, Search terms, Spatial configuration, Spatial Internet, Stochastic systems, Web 3
@inproceedings{nazareth_real_2023,
title = {(Un)real Estates},
author = {I. Nazareth and K. Gao},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190513559&doi=10.1145%2f3627611.3636265&partnerID=40&md5=ce9c77aaa6f6b09ab2895dfc28c7ef1d},
doi = {10.1145/3627611.3636265},
isbn = {979-840071635-5 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {ACM Int. Conf. Proc. Ser.},
pages = {179–186},
publisher = {Association for Computing Machinery},
abstract = {(Un)real Estates is a project and platform that explores a counterfactual narrative of the physical city and its digital counterpart. It is a provocation about the commercialisation of the infrastructure of the spatial internet. (Un)real Estates presents a proto-architectural sequence and experience between particles and pixels, matter, and event. In virtual jumpspace, machines and search terms hallucinate spatial configurations, while random probability distributions and large language models generate new topologies. This creates a stochastic architecture that is the inadvertent realisation of an architectural fantasy - architecture without architecture. The project integrates digital media techniques and architectural design syntax to explore an immersive architectural experience where the physical and virtual are fused as seamless interfaces. The project provides new ways of engaging with the built environment, and operates at limits of material practice, extending the spaces open to the architectural imagination. (Un)real Estates forestalls the terminal end of the metropolitan experiment and is an epistle to the post-urban technotopia, with all its manifold tensions and misgivings. It is a postscript for the city on the cusp of a technological singularity. By presenting a near-future scenario, (Un)real Estates serves as a cautionary tale to consider the potential consequences of the unabridged networked speculative enterprise. The project responds to the theme of (dis)engagement, and utilises AI, Machine Learning, explores subjects of data extractivism, data governance, physical and digital artefacts, and decentralised blockchain and digital ledger technologies. © 2023 ACM.},
keywords = {Artificial intelligence, Commercialisation, Counterfactuals, Digital counterparts, Digital storage, Digital Twins, Metaverse, Metaverses, Platform Technology, Probability distributions, Real-estates, Search terms, Spatial configuration, Spatial Internet, Stochastic systems, Web 3},
pubstate = {published},
tppubtype = {inproceedings}
}
(Un)real Estates is a project and platform that explores a counterfactual narrative of the physical city and its digital counterpart. It is a provocation about the commercialisation of the infrastructure of the spatial internet. (Un)real Estates presents a proto-architectural sequence and experience between particles and pixels, matter, and event. In virtual jumpspace, machines and search terms hallucinate spatial configurations, while random probability distributions and large language models generate new topologies. This creates a stochastic architecture that is the inadvertent realisation of an architectural fantasy - architecture without architecture. The project integrates digital media techniques and architectural design syntax to explore an immersive architectural experience where the physical and virtual are fused as seamless interfaces. The project provides new ways of engaging with the built environment, and operates at limits of material practice, extending the spaces open to the architectural imagination. (Un)real Estates forestalls the terminal end of the metropolitan experiment and is an epistle to the post-urban technotopia, with all its manifold tensions and misgivings. It is a postscript for the city on the cusp of a technological singularity. By presenting a near-future scenario, (Un)real Estates serves as a cautionary tale to consider the potential consequences of the unabridged networked speculative enterprise. The project responds to the theme of (dis)engagement, and utilises AI, Machine Learning, explores subjects of data extractivism, data governance, physical and digital artefacts, and decentralised blockchain and digital ledger technologies. © 2023 ACM.