Virtual and augmented reality

The traditional automotive design process follows a structured, linear workflow, progressing through fixed phases from research to validation. While effective in ensuring reliability, this approach often results in high costs, prolonged development times, and limited flexibility for late-stage modifications. This paper introduces a Circular Iterative Design (CID) methodology, integrating Virtual Reality (VR) and Generative Artificial Intelligence (AI) within the Industrial Design Structure (IDeS) to enhance efficiency, adaptability, and innovation. The proposed framework enables real-time design iteration, significantly reducing early-stage conceptualization time by allowing designers to rapidly transition between 3D gestural sketching and 2D refinement. Advanced AI tools further accelerate the process by automating rendering, generating design variations, and optimizing surfaces with minimal manual adjustments. Additionally, by leveraging a progressive 3D dataset (Core Model) that evolves from initial sketches to refined Class A surfaces, CID minimizes redundant efforts and enhances workflow continuity. Compared to traditional workflows, this approach can reduce reliance on physical prototypes, leading to a faster and more cost-effective design cycle, while also promoting sustainability by optimizing resource usage. The findings of this study demonstrate that integrating VR, AI, and structured methodologies into automotive design offers a scalable, collaborative, and highly efficient alternative to conventional processes.

Keywords: Artificial intelligence , Design methodologies , Industrial design structure , Transportation design , Virtual reality

Italian hand gestures constitute a distinctive and widely recognized form of nonverbal communication, deeply embedded in everyday interaction and cultural identity. Despite their prominence, these gestures are rarely formalized or systematically taught, posing challenges for foreign speakers and visitors seeking to interpret their meaning and pragmatic use. Moreover, their ephemeral and embodied nature complicates traditional preservation and transmission approaches, positioning them within the broader domain of intangible cultural heritage. This paper introduces a machine learning–based framework for recognizing iconic Italian hand gestures, designed to support cultural learning and engagement among foreign speakers and visitors. The approach combines RGB–D sensing with depth-enhanced geometric feature extraction, employing interpretable classification models trained on a purpose-built dataset. The recognition system is integrated into a non-immersive virtual reality application simulating an interactive digital totem conceived for public arrival spaces, providing tutorial content, real-time gesture recognition, and immediate feedback within a playful and accessible learning environment. Three supervised machine learning pipelines were evaluated, and Random Forest achieved the best overall performance. Its integration with an Isolation Forest module was further considered for deployment, achieving a macro-averaged accuracy and F1-score of 0.82 under a 5-fold cross-validation protocol. An experimental user study was conducted with 25 subjects to evaluate the proposed interactive system in terms of usability, user engagement, and learning effectiveness, obtaining favorable results and demonstrating its potential as a practical tool for cultural education and intercultural communication.

Keywords: gesture recognition , human–computer interaction , intangible cultural heritage , Italian culture , machine learning , virtual reality

Augmented Reality (AR) is increasingly being adopted in surgical procedures. Identifying accurate and reliable tracking systems can enhance the effectiveness of AR assisted surgery. The study presents a benchmarking platform to evaluate the performance of different optical surgical tools tracking systems for AR applications, addressing the need for standardized comparison of tracking systems' accuracy, repeatability, and reliability. A custom-built, cost-effective benchmarking platform was developed, and different quantitative evaluation metrics were employed to assess performances of Marker-Based (MB) tracking systems. Two types of measurements were performed: static, where metrics such as Target Registration Error (TRE) and tip stability as a measure of jitter were estimated, and dynamic, involving a measure of the deviation between the tracked tooltip trajectory and its GT. Three AR MB-tracking methods were tested: method 1, mono-RGB sensor tracking a planar image target; method 2, RGB-depth sensor tracking passive spherical markers; and method 3, mono-IR sensor tracking IR active markers. Significant performance differences were observed. Method 3 achieved the lowest TRE value of Method 1 exhibited the best tip stability with a jitter value of Method 2 obtained the minimum trajectory distance in dynamic tests. The benchmarking platform demonstrated its effectiveness in evaluating and comparing different AR tracking methods. This study enables the optimization of tracking system selection for use in the operating room, and facilitating the integration of AR as a supportive technology in surgical practice.

Keywords: Augmented reality , Augmented surgery , Marker-based , Pose estimation , RealSense , Tooltip tracking

This study explores how integrating biophilic elements into automated vehicles affects users' experience, affective trust, perceived price value, connectedness to nature, and behavioral intention. Sixty-one participants experienced 4 driving scenarios with three types of biophilic interventions in a mixed reality environment. Results from Partial Least Squares revealed that perceived price value was the strongest predictor of behavioral intention, while final trust and connectedness to nature showed no direct impact. Initial trust influenced behavioral intention indirectly by enhancing user experience, which increased perceived price value. Demographic factors, did not significantly affect outcomes. These findings show the value of integrating biophilic elements in automated vehicles lies not only in making the ride more pleasant, but in strengthening the factors that drive adoption. This research provides pragmatic insights for automotive designers and industries. In a market where technology frequently feels impersonal, integrating natural elements can transform the driving experience, making it not only more pleasant but also more desirable to potential customers.HIGHLIGHTS Biophilic elements in AVs enhance user experience and behavioral intention. Perceived price value is the strongest predictor of behavioral intention. Initial trust boosts behavioral intention indirectly via improved user experience.

Keywords: Automated vehicle adoption , behavioural intention , biophilic design , human–machine interaction , mixed reality experience

Objective. Objective evaluation of operational training remains challenging, particularly when comparing physical training with virtual reality (VR) training. Behavioral and subjective measures capture performance and perceived workload but provide limited insight into the underlying neurocognitive adaptation. This study proposes and validates a synthetic EEG-derived cognitive training index (CTI) that integrates multiple training-sensitive neurometrics into a single composite metric, with two aims: to validate CTI as an objective marker of training progression in a physical training group, and to test whether VR-based training leads to neurocognitive adaptation comparable to physical training when participants subsequently execute the task in the real environment. Approach. Participants completed three repetitions of a realistic confined-space industrial maintenance procedure structured into Entrance, Rolling shutter, and Pipe replacement phases. Behavioral outcomes (execution time, procedural errors) and subjective workload NASA Task Load Index (NASA-TLX) were collected after each trial. Wearable EEG was recorded continuously; six neurometrics were computed from cleaned EEG using band-specific Global Field Power over predefined electrode sets. CTI was obtained via principal component analysis applied at the trial level to the multivariate neurometric time series, followed by segment-wise analysis. Temporal specificity of CTI was assessed through phase-randomized surrogate-data analyses. Main results. Execution time decreased across trials (F = 14.82, p <.001, η2p = 0.35), procedural errors decreased similarly (F = 10.31, p <.001, η2p = 0.27), and NASA-TLX declined (F = 11.94, p <.001, η2p = 0.30). CTI increased significantly with training (F = 18.21, p <.001, η2p = 0.39) and was selectively higher in learning-relevant phases (Entrance and Pipe replacement), while remaining near baseline in the low-demand Rolling shutter phase. Surrogate analyses showed that real CTI exceeded null expectations, supporting temporal specificity. Repeated-measures correlations indicated significant negative associations between CTI and procedural errors (R = − 0.42, p <.01) and between CTI and NASA-TLX (R = − 0.38, p <.01), while CTI was not significantly related to execution time (R = 0.18, p =.12). Significance. CTI provides a psychologically grounded, multivariate EEG marker that tracks training progression and aligns with operationally meaningful outcomes, namely procedural accuracy and perceived workload, rather than task speed alone. This approach supports objective comparison of cognitive adaptation across training modalities and provides a practical basis for neurophysiologically informed training evaluation and future adaptive training systems.

Keywords: EEG , principal component analysis , training

Background: Associative memory is essential for daily functioning; however, VR interventions in this domain are limited. Objectives: The present study examined associative memory in different modalities and investigated the effects of culture on performance and response time in a virtual environment. Methods: Twenty-two healthy younger adults from Italy and Ghana (ages 18-26) completed eight training trial sessions on object-name matching and object-sound matching tasks in a virtual environment. Results: Performance improved progressively across trials in both tasks, with greater accuracy and faster response times in the object-name task than in the object-sound task. Cross-cultural comparisons revealed no significant performance differences between the Ghanaians and Italians. However, the Italians completed both tasks significantly faster than the Ghanaians. Conclusion: The findings of the present study indicate that associative memory is culturally invariant, whereas response-time differences may reflect cultural influences on processing strategies. Overall, this study supports the use of VR as a culturally adaptable platform for associative memory assessment and training.

Keywords: Associative Memory , Cross-cultural Study , Pair-associate learning , Virtual Reality

Remote maintenance is a key function to ensure reliable, safe, and long-term operation of fusion reactors. However, handling heavy components in tight spaces is a challenging task. As part of its goals, the ITER project also has to demonstrate the feasible design, integration, and operation of a remote handling system (RHS) able to perform both preplanned tasks and recovery/rescue operations in case of failure or abnormal conditions. The ITER Remote Handling Control System (RHCS) is based on a man-in-the-loop concept due to the complexity of the tasks. In order to make more informed and aware decisions while supervising or teleoperating RH equipment movements, the operators are provided with both real images coming from on-site cameras and virtual renderings, thanks to the virtual reality (VR) system. Generally, VR renderings are made of rigid CAD models and do not consider the effects of dynamic factors on the RH equipment (RH) structure. This work shows the development activities of the structural simulator (SS) for the calibration of the RH VR models, aimed at accurately representing the real configuration the robots assume due to their own weight and the handled load.

Keywords: ITER , remote handling , robot calibration , structural simulation , virtual joints (VJs) , virtual reality (VR)

This research presents the mechanical design and performance evaluation of a novel 3-Degrees-of-Freedom (DoFs) wrist exoskeleton (W-EXOS) for orthopedic and poststroke patients' upper limbs rehabilitation. The device covers the 93.3% of the human Range of Motion (RoM), simulating the pronosupination, radioulnar deviation, and flexion-extension motion. W-EXOS is actuated through electric motors via an efficient cable transmission, having high torque/weight and torque/volume ratios. Its kinematics is a serial chain of three rotational joints with nonperpendicular axes competing at the wrist rotation center. So, the device joints are coupled but the structure is compact and with good mass distribution. Theoretical modeling allowed the study of the human wrist and the device axes matching, evaluating the RoM and torques at each joint. With the W-EXOS integrated into a rehabilitation station, the performance assessment was done using: 1) a position control test, for the device RoM validation and 2) a virtual reality serious game test, to prove the device assistance strategy during wrist motion tasks performed by healthy subjects in a typical rehabilitation session. Further, the W-EXOS handle has been replaced by a hand exoskeleton and the whole system has been mounted on a 4-DoFs shoulder-elbow exoskeleton, proving the W-EXOS integrability in multiple, highly wearable, compact, and usable, bimanual, upper limb robotic setups.

Keywords: Assistance , human-centered design , mechanical design , Range of Motion (RoM) , rehabilitation robotics , tendon/wire mechanism , virtual prototyping , wearable devices , wrist exoskeleton (W-EXOS)

Virtual Reality is used in design for both supporting design reviews and interacting with products being designed. The interactions Virtual Reality enables are often found engaging and this might affect product evaluation, as experiencing a virtual environment can be the prevalent element of an experience. This paper investigated to what extent product evaluations are affected by the sense of presence enabled by Virtual Reality, the duration of interactions with the whole products and its features, and the product information provided after exposure to the virtual environment. These effects were tested through an experiment involving the virtual tour of a tiny house whose interior was extracted through 360° images, which represents an element of originality of the paper, followed by administering participants informative stimuli. All these phases were supported by eye-tracking, also thanks to the use equipment combining Virtual Reality and eye-tracking, hitherto poorly used in design research, in the first part of the experiment. Based on the experiment results, the effects studied were limited to the gazing of few design elements on some product evaluation dimensions. These findings suggest that Virtual Reality can provide a strong product perception irrespective of sense of presence and other phenomena taking place during product interaction. This is particularly stressed by the failure of informative stimuli to make experiment participants modify the initial evaluations made just after the virtual tour. Overall, the outcomes of this study encourage the use of Virtual Reality for design interaction tasks, especially in relation to environments and building interiors.

Keywords: Eye-tracking , Product evaluation , Sense of presence , Virtual reality , Visual behavior

Safety in the industrial sector is paramount, with national legislations establishing specific regulations to reduce accidents. These regulations emphasize risk removal and proper operator training as preventive measures. However, traditional training can be time-consuming and costly, leading companies to meet only the minimum requirements. In particular, confined spaces pose significant dangers, often resulting in fatal, cascading accidents due to a lack of proper safety procedures. Therefore, effective training is crucial to mitigate these risks. Advanced technologies like Immersive Virtual Reality (IVR) present new opportunities for cost-effective and extensive training campaigns by eliminating the risks associated with real environment training, offering a safe yet realistic experience. Despite the widespread adoption of IVR training applications in industrial research, there is a notable lack of systematic approaches to evaluate their effectiveness. Conducting such evaluations is crucial to ascertain their impact on essential training outcomes, including participant engagement, knowledge transfer, and enhanced safety behavior during work activities. To address this gap, we developed an IVR-based training platform for confined space safety procedures and established a systematic validation procedure using the Kirkpatrick model to assess its effectiveness compared to conventional training methods. Results demonstrate that IVR training provides an excellent user experience, better knowledge transfer than the traditional approach, and improved performance in simulated procedures, reducing execution errors and completion times. This dual focus on creating and validating the IVR system underscores its potential as an effective training tool in hazardous environments such as confined spaces, where proper training can prevent tragic fatalities.

Keywords: Confined space , Safety training , User study , Validation procedure , Virtual reality

Extended Reality (XR) technologies are increasingly popular to support the engagement of different audiences and stakeholders with Discrete Event Simulations (DES) due to their capability to deliver more accessible visual and immersive experiences. XR applications can be developed either using modules integrated into DES software or game engines, providing different sets of opportunities in the environment design. However, there is a lack of development guidelines for such environments, considering visualization, information presentation, interaction, and navigation aspects. The paper presents a systematic review of the use of XR for DES, relating the results to XR design heuristics to identify and discuss major design tradeoffs. Finally, a case study from the mining sector is exemplified to illustrate possible. solutions to balance the trade-offs.

Keywords: Augmented reality , Discrete event simulation , Extended reality , Virtual reality

The evolving landscape of educational technologies has ushered Virtual Reality (VR) in the forefront of higher education. As the COVID-19 pandemic propelled a rapid shift toward e-learning, the demand for high-quality distance education has surged, prompting an exploration of VR as a viable solution. While existing research indicates that VR supports student engagement and learning experiences compared with traditional teaching methods, the lack of shared pedagogical frameworks and systematic analyses of its applications leaves a deeper investigation of VR's potentials and limitations in enhancing learning outcomes still unexplored. This paper presents a systematic literature review aimed at filling this gap by considering studies that evaluate VR-based teaching methods in comparison with traditional ones in higher education contexts in order to assess the strengths and weaknesses of this technology in improving students' learning outcomes and achieve inclusive education. The analysis focuses on a set of dimensions including the adopted research design, participants' characteristics, disciplinary field of application, VR technological features (i.e., immersivity, interactivity, operability, commercial availability, and presence of VR training), adopted teaching methodologies, assessed VR impact on learning outcomes and presence of studies involving students with disabilities or Specific Learning Disorders (SpLDs). Based on inclusion/exclusion criteria, a total of 71 studies of VR in higher education were analysed. Most of analysed studies employed quantitative methods (67%), while no qualitative studies were found. More than half of the studies were conducted with undergraduate students (61%). Most of the studies involved VR in STEM disciplines, with almost half of them concerning Health Sciences (45%). VR solutions were most frequently immersive (63%), predominantly using Oculus Rift and HTC Vive HMDs, interactive (59%), single-user (92%) and non-commercial (57%). Only a small portion of studies included a VR training in the research protocol (8%). Most of the studies compared lecture-based methodologies as control condition with active methodologies in the VR condition. Learning outcomes were positively influenced by immersivity, interactivity and active methodologies, although at different degrees. No study involved students with disabilities or SpLDs in the experimentation. By offering a multidimensional perspective on the application of VR in higher education contexts, the paper provides a valuable resource for educators, researchers, and policymakers navigating the dynamic intersection of VR and higher education.

Keywords: Augmented and virtual reality , Human-computer interface , Media in education , Post-secondary education , Teaching/learning strategies

Nowadays, driving simulation devices represent a continuously evolving and developing area in the world of virtual reality. One of the fundamental elements in the design of driving software is the track model. This work aims to study the use of advanced technologies for the three-dimensional modeling of a racing track in a driving simulator. Specifically, it employs the LiDAR methodology to acquire the three-dimensional coordinates of a 1 km long circuit located on the Fisciano campus of the University of Salerno. The purpose of this work is to explain and present a novel track acquisition and modeling methodology within the realm of simulated driving reality. Following the study, the Virtual Reality Laboratory's driving simulator at the Department of Industrial Engineering conducted tests to validate the proposed circuit model. The test rides analyzed the realism of the driving experience, thereby validating the proposed track model. This phase was complemented by a series of proposals for possible future developments in the field of three-dimensional modeling applied to driving simulation and beyond. In the end, the 3D model obtained demonstrated the high definition of the acquired result and the speed with which multiple data were obtained simultaneously, thanks to the laser scanner used.

Keywords: 3D modeling , driving simulation , LiDAR data , real-world driving , track modeling , virtual environment , virtual reality , virtual reality

In the realm of smart manufacturing, Extended Reality (XR) technologies stand as transformative tools capable of deeply reshaping the industrial landscape. XR has been extensively adopted across various industries, particularly for optimizing complex tasks such as product maintenance and repair. Nevertheless, many industries continue to rely solely on traditional approaches, resulting in low efficiency and productivity. This is often due to the challenges encountered in adopting effective XR solutions to provide comprehensive instructions during maintenance activities. This paper introduces an innovative XR platform tailored to foster collaboration between the technical office and maintainers. Specifically, this platform facilitates maintenance and repair operations on industrial products through close collaboration between a skilled user utilizing a VR application and an inexperienced operator utilizing an AR application. This cooperation is made possible by integrating and concurrently deploying these applications, which communicate via a central server managing the connection in a host/client model.

Keywords: Collaborative platform , Extended Reality , Maintenance

Augmented Reality (AR) stands as a transformative technology reshaping the accessibility of cultural heritage (CH) sites and artworks in digital form. With the integration of virtual avatars, AR applications are poised to revolutionize visitor experiences by immersing them in interactive narratives. However, conventional AR systems often limit avatars to specific points of interest (POIs), lacking guidance throughout the exploration tour. This paper introduces an innovative AR-based system tailored for immersive CH encounters, leveraging virtual avatars as navigational aids through indoor and outdoor exhibits and artworks. The core of this system comprises two main components: an authoring tool for content creation and an AR application for user visualization and interaction. The authoring tool empowers creators to define POIs and seamlessly associate digital content, while the AR application enables visitors to engage with this content, guided by virtual avatars throughout the augmented tour.

Keywords: ARI questionnaire , Augmented reality , Cultural heritage , Virtual humans

The paper presents an overview of current training endeavours for technology-related/professional skill acquisition in immersive environments together with educational/training needs that emerge from the literature. The aim is to establish a general framework for the design and development of educational initiatives for lifelong learners, both HEI students and professional. The paper details how immersive technologies enable a wide variety of skills (e.g. psychomotor, spatial, procedural, decisional skills) to be acquired and trained while reducing the costly and risky conditions of on the field training. On the other hand, the framework will also display how the immersive technologies might trigger high engagement and motivation in active/student-centred learning contexts, making them suitable to provide meaningful learning experiences for the largest possible variety of learning styles, which are vital to ensure life-long learning and embrace the principles of pedagogy and andragogy.

Keywords: Education Framework , Immersive Environment , Professional Skill Training

Digital transformation of industrial training processes is still an ongoing process. The transformation requires a specific training model to be applied to an already structured context, to experienced workers, sometimes with their needs and specific skills, and the solution is designed considering a series of boundary conditions. To design a new training model that the industry will accept, it is important to consider the design space offered by technology, but at the same time, to consider human complexity. This paper proposes a methodology to analyze current training strategies in the industrial sector to design new tools according to a digital transformation logic that considers the underlying principle of the human centricity of Industry 5.0.

Keywords: Digital transformation , Industrial training , Industry 5.0

In the automotive industry, assembly line equipment represents one of the major costs to be considered during product-process development due to the complexity of assembly operations and their need of purchasing cutting-edge solutions capable of carrying them out. DMU (Digital Mock-Up) software may support components design and assembly lines development allowing simulations of the operations. Currently, real-time virtual prototyping and simulation involve exclusively components that could be modeled as rigid or 1D-deformable. For other components, especially non-metallic ones, mock-ups are realized exclusively through physical models. To increase DMU software benefits, it is necessary an increase of fidelity concerning the modeling of a larger set of materials (e.g. hyperelastic models) and 2D geometric large deformations, present in thin-wall and shell components. This capability becomes crucial in DMU of real-practice cases, allowing to simulate assembly paths through gaps that are inaccessible without deforming the component to be inserted. Elastic deformation during assemblies represents a high computational effort for 2D components that is not affordable yet in real time conditions. Defeaturing is a possible strategy to simplify components, lightening computational effort. Hence, a compromise between response speed and accuracy in the respect to real behavior is necessary. This paper reports feasibility analyses and developed procedures based on this set of simulations, helpful for the current development of a 2D-elastic module of a VR/AR software, IC.IDO (ESI). To do this a plastic wheel arch has been used as development case study. FE simulations and results are reported, using Hyperworks and IC.

Keywords: Assembly , Automotive , Defeaturing , Digital Mock-Up , Finite Element Analysis , Real-Time Simulations , Virtual Reality

The primary procedures performed in maxillofacial surgery are osteotomy and repositioning. Surgeons usually exploit 3D printed guides and splints which entail considerable production time and high costs. To address these issues, innovative technologies such as mixed reality (MR) are emerging, but accuracy must still be assessed. Head-mounted displays (HMDs) are categorised into two main types: optical and video see-through. Recognisable comparisons between HoloLoens 2 (optical see-through) and Varjo XR3 (video see-through) are still not available in the scientific literature. This paper compares the accuracy of simulating maxillofacial surgery through these two different headsets. For the evaluation, a 3D model of a skull was 3D printed using Color Material Jetting 3D printing technology. Six people tested the MR application by i) tracing lines and holes with a pen following the holograms displayed on the phantom's anatomy for osteotomies, ii) moving the maxillary fragmented bone according to the projected hologram for repositioning. Times were recorded during the trial. The tested geometries were then 3D scanned to reconstruct the traced cutting lines and holes, and quantitative results were extracted in CloudCompare by comparing the drawn and nominal lines. For the repositioning, deviations have been computed to calculate the mean deviation from the planned displacement.

Keywords: Healthcare Design , Maxillofacial Surgery , Mixed Reality , Optical See-Through , Video See-Through

In the evolving landscape of driving training, the integration of technology has played a pivotal role in shaping educational methodologies and enhancing learning outcomes. Virtual training methods, which often rely on the use of monitors, have been the standard for decades. However, with the advent of augmented reality (AR), a new dimension of interactive and immersive training is emerging, promising to revolutionize the way driving skills are taught and acquired. This paper aims to explore and compare the effectiveness of virtual monitor-based training with the innovative use of augmented reality in driving simulations. The focus is on understanding how each method affects learning efficiency, user engagement, and the practical applicability of the skills acquired through these training modalities. Virtual monitor-based training systems are valued for their accessibility and cost-effectiveness, making them a prevalent choice in many training programs. On the other hand, augmented reality introduces a layer of interactive elements that overlay the real world or simulated environments, providing real-time feedback and enhancing situational awareness. This paper seeks to delineate the strengths and limitations of the AR-integrated driving training simulations. The goal is to provide insights into how virtual-based training can be optimized to enhance the safety, efficiency, and effectiveness of driving education, ultimately contributing to better-prepare drivers in their driving performances.

Keywords: Augmented Reality , Driving Simulator , User Experience