1,721,166 research outputs found
Bistolfi Leonardo, Calandra Davide, Grandi Giuseppe, Monteverde Giulio, Tabacchi Odoardo, Ximenes Ettore, Vela Vincenzo
No full textVoci "Bistolfi Leonardo", "Calandra Davide", "Grandi Giuseppe", "Monteverde Giulio", "Tabacchi Odoardo", "Ximenes Ettore", "Vela Vincenzo" nel McMillan Dictionary of Ar
Interaction in Virtual Reality Simulations
Full text linkL'abstract è presente nell'allegato / the abstract is in the attachmen
A testbed for studying cybersickness and its mitigation in immersive virtual reality
Full text linkCybersickness (CS) represents one of the oldest problems affecting Virtual Reality (VR) technology. In an attempt to resolve or at least limit this form of discomfort, an increasing number of mitigation techniques have been proposed by academic and industrial researchers. However, the validation of such techniques is often carried out without grounding on a common methodology, making the comparison between the various works in the state of the art difficult. To address this issue, the present paper proposes a novel testbed for studying CS in immersive VR and, in particular, methods to mitigate it. The testbed consists of four virtual scenarios, which have been designed to elicit CS in a targeted and predictable manner. The scenarios, grounded on available literature, support the extraction of objective metrics about user's performance. The testbed additionally integrates an experimental protocol that employs standard questionnaires as well as measurements typically adopted in state-of-the-art practice to assess levels of CS and other subjective aspects regarding User Experience. The paper shows a possible use case of the testbed, concerning the evaluation of a CS mitigation technique that is compared with the absence of mitigation as baseline condition
Artificial Reality: Immersive but Factually Dishonest AR Experience
Full text linkAs commonly known, technology is a double-edged sword, and augmented reality (AR) is no exception. This article raises concerns and promotes awareness of the use of AR in mass media, in particular in those industries, such as news reporting, that aspire to report facts. Our main message is that the standard workflow for creating AR content, albeit having no mala fide intent, might lead to artificial reality. This titular term was introduced by the first author during a talk organized by a technical committee of IEEE Consumer Technology Society (CTSoc), where we decided that we should urge more ethics and standard discussions on the issue through this article
Improving AR-powered remote assistance: A new approach aimed to foster operator’s autonomy and optimize the use of skilled resources
Full text linkAugmented Reality (AR) has a number of applications in industry, but remote assistance represents one of the most prominent and widely studied use cases. Notwithstanding, although the set of functionalities supporting the communication between remote experts and on-site operators grew over time, the way in which remote assistance is delivered has not evolved yet to unleash the full potential of AR technology. The expert typically guides the operator step-by-step, and basically uses AR-based hints to visually support voice instructions. With this approach, skilled human resources may go under-utilized, as the time an expert invests in the assistance corresponds to the time needed by the operator to execute the requested operations. The goal of this work is to introduce a new approach to remote assistance that takes advantage of AR functionalities separately proposed in academic works and commercial products to re-organize the guidance workflow, with the aim to increase the operator's autonomy and, thus, optimize the use of expert's time. An AR-powered remote assistance platform able to support the devised approach is also presented. By means of a user study, this approach was compared to traditional step-by-step guidance, with the aim to estimate what is the potential of AR that is still unexploited. Results showed that with the new approach it is possible to reduce the time investment for the expert, allowing the operator to autonomously complete the assigned tasks in a time comparable to step-by-step guidance with a negligible need for further support
Anomaly detection and localization with state-of-the-art deep learning models to support quality inspection in car manufacturing
No full textMaintaining high quality in automotive manufacturing is essential, as even small defects can lead to safety issues, costly recalls, and increased operational costs. Manual inspection is often unreliable in fast-paced production, limited by human error and poor scalability. Advanced imaging and deep learning-based Anomaly Detection and Localization (ADL) offer effective alternatives, but their use in industry is challenged by factors like complex geometries, inconsistent lighting, and environmental noise.
This work presents an ADL framework for inspecting sealant application in car underbodies that combines a video acquisition system with four state-of-the-art deep learning models. To overcome the lack of annotated data, a synthetic defect generation module is introduced, creating realistic anomalies that improve model evaluation while reducing annotation effort.
The framework was tested on both synthetic and real-world data, achieving high localization performance (AUROC up to 99.7%, F1-score of 43.4%) with inference times ranging from 0.08 to 3.33 seconds depending on model complexity. These results highlight the trade-offs between speed and accuracy, and confirm the potential of ADL models for real-time quality control in industrial automotive settings
Exploring the suitability of a digital twin- and extended reality-based telepresence platform for a collaborative robotics training scenario over next-generation mobile networks
Full text linkThis paper explores the application of Digital Twins (DTs) and eXtended Reality (XR) in the context of Industry 4.0, and investigates new ways in which these technologies can be used in remote assistance/training scenarios involving Collaborative Robots (CRs). The study builds upon a previous work that examined the suitability of a novel DT/XR-based telepresence platform for CR programming in terms of network capabilities. The present work addresses some of the limitations of the previous study in the context of a new use case, integrating human pose estimation and object tracking to enhance the DT functionalities of the platform, and testing it in a riveting task scenario. The results in terms of bandwidth and latencies obtained in a laboratory setup emulating 6G performance show the potential of DTs and XR in supporting the collaboration of distant human operators and CRs over future mobile networks, paving the way for the development of new services for next- generation industry
Impact of avatar representation in a virtual reality-based multi-user tunnel fire simulator for training purposes
Full text linkVirtual Reality (VR) technology is playing an increasingly important role in the field of training. The emergency domain, in particular, can benefit from various advantages of VR with respect to traditional training approaches. One of the most promising features of VR-based training is the possibility to share the virtual experience with other users. In multi-user training scenarios, the trainees have to be provided with a proper representation of both the other peers and themselves, with the aim of fostering mutual awareness, communication and cooperation. Var- ious techniques for representing avatars in VR have been proposed in the scientific literature and employed in commercial applications. However, the impact of these techniques when deployed to multi-user scenarios for emergency training has not been extensively explored yet. In this work, two techniques for avatar representation in VR, i.e., no avatar (VR Kit only) and Full-Body reconstruction (blending of inverse kinematics and animations), are compared in the context of emergency training. Experiments were carried out in a training scenario simulating a road tunnel fire. The participants were requested to collaborate with a partner (con- trolled by an experimenter) to cope with the emergency, and aspects concerning perceived embodiment, immersion, and social presence were investigated
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