Advances in artificial intelligence and embodied interaction in augmented reality (AR) are creating new opportunities for intelligent instructional systems that dynamically adapt to individual learners. However, sustaining real-time responsiveness while preserving natural, socially meaningful interaction remains a persistent challenge. This work introduces ARIA (Augmented Reality Instructional Agent), a real-time software architecture for embodied AI instruction in augmented reality. ARIA leverages large language models (LLMs) with adaptive prompt engineering to tailor dialogue style, instructional strategy, and persona expression to each user. Its modular pipeline is optimized for robust, low-latency performance, with benchmarks reported for responsiveness and system stability. To complement the technical evaluation, user experience was assessed through standardized questionnaires, offering insights into perceived personalization, trust, and interaction quality. Quantitative and qualitative results demonstrate that ARIA achieves sub-second responsiveness, high pragmatic and hedonic usability, and a strong sense of co-presence and instructional trust. This work contributes a unified framework and reference architecture for developing adaptive embodied agents that combine technical efficiency with human-centered design, highlighting how real-time responsiveness can serve as the foundation for relational engagement in embodied AI instruction.

While embodied conversational agents driven by Large Language Models (LLMs) are emerging as valuable tools for instruction in Augmented Reality (AR), a key challenge lies in crafting their personalities to optimize both instructional efficacy and user engagement. To address this, we present findings from a within-subjects experiment that compared task performance and user experience with a LEGO assembly task. Participants received guidance from a real human instructor and three virtual counterparts, whose Big Five personality profiles were designed to be: (1) a direct replica of the real human, (2) an "ideal" profile ba sed on pedagogical research, or (3) customized by the participant. Our results reveal a critical trade-off: instruction from the real expert resulted in superior task efficiency and clarity; however, among the virtual conditions, instructors with idealized or user-customized personalities fostered significantly higher levels of user engagement and social presence compared to the virtual replica. Crucially, allowing users to customize their instructor's persona led to the strongest preference for future interaction. These findings underscore that personality is a fundamental component in the design of AI-driven instructors, providing empirical evidence for navigating the balance between task-oriented guidance and personalized, socially resonant user experiences.

Teleportation has become a popular locomotion method for virtual reality due to lesser demands on physical space and decreased levels of motion sickness compared to other methods. However, prior work has shown that these advantages come at the cost of impaired spatial perception and awareness, the extent to which is still largely unknown. In this work, we present a within-subjects study (N = 29) that explores the effects of teleportation on spatial perception by investigating how much humans can be unknowingly displaced relative to their intended destination during teleportation. After teleporting to the specified location, participants indicated the direction and magnitude (small, medium, large) of the perceived shift or rotation. Displacement from the target happened either as a translation in the forward- or strafe-axis, or a rotation about the up-axis at the intended target. Each displacement condition included eleven offsets that were repeated six times. Our results indicate points of subjective equality, which show a significant perceptual shift along the forward-direction, as well as detection thresholds, which indicate a comparatively wide range in which humans are unable to detect induced shifts. Furthermore, our results show that even if humans are able to detect these shifts, larger ones can be introduced before their magnitudes are rated as medium or large, which provides ample opportunities for interface designers who want to leverage these results in virtual reality.

The swift advancement of drone technology presents new challenges in data analysis and integration as deployments increase. This paper addresses the complexities of managing multiple drone video feeds and controlling autonomous drone swarms to enhance situational awareness through the use of real-time updated digital twins for drone swarm command and control. We aim to enhance the effectiveness of drone swarm operations by introducing a novel method, Camera-based Adaptive Line Formation and Dynamic Leader-following Optimization (CALF-DLFO). We investigate the impact of this novel control method on area coverage and drone distribution, considering factors such as formation direction, speed, separation distance, and adjustments. Simulation experiments demonstrate a significant improvement in area coverage compared to prior methods which focused on isolated segments. Our camera-based adaptive line formation, combined with efficient drone control mechanisms, not only enhances coverage but also provides a promising approach to scalable and automated drone swarm management.

It is our great pleasure to welcome you to the 31st IEEE Conference on Virtual Reality and 3D User Interfaces, the premier international conference focused on the latest research in these domains. We are delighted to host IEEE VR 2024 as the first fully in-person VR since the 2020 COVID-19 pandemic and look forward to seeing, learn, share, and hang out with our vibrant community after these challenging years.

It is not uncommon for science fiction movies to portray futuristic user interfaces that can only be realized decades later with state-of-the-art technology. In this work, we present a prototypical augmented reality (AR) installation that was inspired by the movie The Time Machine (2002). It consists of a transparent screen that acts as a window through which users can see the stereoscopic projection of a three-dimensional virtual human (VH). However, there are some key differences between the vision of this technology and the way VHs on these displays are actually perceived. In particular, the additive light model of these displays causes darker VHs to appear more transparent, while light in the physical environment further increases transparency, which may affect the way VHs are perceived, to what degree they are trusted, and the distances one maintains from them in a spatial setting. In this paper, we present a user study in which we investigate how transparency in the scope of transparent AR screens affects the perception of a VH’s appearance, social presence with the VH, and the social space around users as defined by proxemics theory. Our results indicate that appearances are comparatively robust to transparency, while social presence improves in darker physical environments, and proxemic distances to the VH largely depend on one’s distance from the screen but are not noticeably affected by transparency. Overall, our results suggest that such transparent AR screens can be an effective technology for facilitating social interactions between users and VHs in a shared physical space.

Our paper presents LIFT, a system that enables educators to create immersive virtual field trip experiences for their students. LIFT overcomes the challenges of enabling non-technical educators to create their own content and allows educators to act as guides during the immersive experience. The system combines live-streamed 360° video, 3D models, and live instruction to create collaborative virtual field trips. To evaluate LIFT, we developed a field trip with biology educators from the University of Central Florida(UCF) and showcased it at a science festival. Our results suggest that LIFT can help educators create immersive educational content while out in the field. However, our pilot observational study at the museum highlighted the need for further research to explore the instructional design of mixed immersive content created with LIFT. Overall, our work provides an application development framework for educators to create immersive, hands-on field trip experiences.

Research on alternative ways to provide anatomy learning and training has increased over the past few years, especially since the COVID-19 pandemic. Virtual reality (VR) and augmented reality (AR) represent two promising alternatives in this regard. For this reason, in this work, we analyze the suitability of applying VR and AR for anatomy training, comparing an optical-based AR setup and a semi-immersive setup based on a VR table, using the same anatomy training software and the same interaction system. The AR-based setup uses a Magic Leap One, whereas the VR table is configured through the use of stereoscopic TV displays and a motion-capture system. This experiment builds on a previous one (Vergel et al., 2020) on which we have improved the AR-based setup and increased the complexity of one of the two tasks. The goal of this new experiment is to confirm whether the changes made in the setups modify the previous conclusions. Our hypothesis is that the improved AR-based setup will be more suitable, for anatomy training, than the VR-based setup. For this reason, we conducted an experimental research with 45 participants, comparing the use of an anatomy training software. Objective and subjective data were collected. The results show that the AR-based setup is the preferred choice. The differences in measurable performance were small but also favorable to the AR setup. In addition, participants provided better subjective ratings for the AR-based setup, confirming our initial hypothesis. Nevertheless, both setups offer a similar overall performance and provide excellent results in the subjective measures, with both systems approaching the highest possible values.

Abstract Human-computer interaction based on hand gesture tracking is not uncommon in Augmented Reality. In fact, the most recent optical Augmented Reality devices include this type of natural interaction. However, due to hardware and system limitations, these devices, more often than not, settle for semi-natural interaction techniques, which may not always be appropriate for some of the tasks needed in Augmented Reality applications. For this reason, we compare two different optical Augmented Reality setups equipped with hand tracking. The first one is based on a Microsoft HoloLens (released in 2016) and the other one is based on a Magic Leap One (released more than two years later). Both devices offer similar solutions for the visualization and registration problems but differ in the hand tracking approach, since the former uses a metaphoric hand-gesture tracking and the latter relies on an isomorphic approach. We raise seven research questions regarding these two setups, which we answer after performing two task-based experiments using virtual elements, of different sizes, that are moved using natural hand interaction. The questions deal with the accuracy and performance achieved with these setups and also with user preference, recommendation and perceived usefulness. For this purpose, we collect both subjective and objective data about the completion of these tasks. Our initial hypothesis was that there would be differences, in favor of the isomorphic and newer setup, in the use of hand interaction. However, the results surprisingly show that there are very small objective differences between these setups, and the isomorphic approach is not significantly better in terms of accuracy and mistakes, although it allows a faster completion of one of the tasks. In addition, no remarkable statistically significant differences can be found between the two setups in the subjective datasets gathered through a specific questionnaire. We also analyze the opinions of the participants in terms of usefulness, preference and recommendation. The results show that, although the Magic Leap-based system gets more support, the differences are not statistically significant.

Motion-based simulators are used for a variety of applications, such as research, education, entertainment and training. In fact, motion cues are required to achieve the highest regulatory certifications in training vehicle simulators. Nonetheless, the reproduction of self-motion cues presents technological and economic limitations that are not present in the generation of audiovisual cues. For this reason, the generated motion does not generally match the expected one. Therefore, it is necessary to define means to assess the suitability/fidelity of the generated motion cues. After more than 50 years of motion-based vehicle simulation, no mechanism has been universally accepted as the standard solution for the evaluation of motion cues. This paper reviews the mechanisms for obtaining measures of motion fidelity, focusing on those based on objective methods. Since the design of the Objective Motion Cueing Test in 2006, researchers have shown a renewed interest in identifying objective methods to evaluate motion cueing, as the number of works following this approach in recent years reveals. Objective motion fidelity systems allow also performing automatic tuning of MCA by means of optimization techniques, which addresses one of the other main problems of these algorithms. Nevertheless, a universally accepted objective method to assess perceptual motion fidelity in vehicle simulators has not been proposed yet. For this reason, this review work frames and classifies the existing methods. In addition, the authors propose a series of features that an ideal evaluation method for assessing perceptual motion fidelity should include and provide future research guidelines for this complex topic.

Anatomy training with real cadavers poses many practical problems for which new training and educational solutions have been developed making use of technologies based on real-time 3-D graphics. Although virtual reality (VR) and augmented reality (AR) have been previously used in the medical field, it is not easy to select the right 3-D technology or setup for each particular problem. For this reason, this article presents a comprehensive comparative study with 82 participants between two different 3-D interactive setups: an optical-based AR setup, implemented with a Microsoft HoloLens device, and a semi-immersive setup based on a VR Table. Both setups are tested using an anatomy training software application. Our primary hypothesis is that there would be statistically significant differences between the use of the AR application and the use of the VR Table. Our secondary hypothesis is that user preference and recommendation for the VR setup would be higher than for the HoloLens-based system. After completing two different tasks with both setups, the participants filled two questionnaires about the use of the anatomy training application. Three objective measures are also recorded (time, number of movements, and a score). The results of the experiments show that more than two-thirds of the users prefer, recommend, and find more useful the VR setup. The results also show that there are statistically significant differences in the use of both systems in favor of the VR Table.

The three papers in this special section are expanded versions of the three best papers from the IEEE VR 2008 proceedings.

Online software maintenance (OSM) is performed while an application is running. It requires transforming the runtime state of the application to go along with updates of its software. The goal is to perform maintenance of mission-critical systems while they continue to run. This research presents dynamically evolvable C++ classes as a way to enable OSM. The associated implementation mechanism is called the OSM framework. We provide a high-level view of the OSM framework and then describe different types of object-oriented design transformations that are supported. The accompanying state transformations are described to evolve the live objects along with the software. We have implemented a prototype of the OSM framework; it works with the g++ and the Microsoft C++ compilers. Performance results are presented to assess the memory and processing overheads of the OSM framework. The proposed approach advances the state of the art in two ways: (a) it extends the notion of dynamic evolvability by including fission and fusion and other object-oriented design transformations, and (b) it provides a novel OSM framework that takes advantage of C++ templates

MOTIVATION: Metabolic networks combine metabolism and regulation. These complex networks are difficult to understand and visualize due to the amount and diverse types of information that need to be represented. For example, pathway information gives indications of interactions. Experimental data, such as transcriptomics, proteomics and metabolomics data, give snapshots of the system state. Stereoscopic virtual environments provide a true three-dimensional representation of metabolic networks, which can be intuitively manipulated, and may help to manage the data complexity. RESULTS: MetNet3D, a 3D virtual reality system, allows a user to explore gene expression and metabolic pathway data simultaneously. Normalized gene expression data are processed in R and visualized as a 3D plot. Users can find a particular gene of interest or a cluster of genes that behave similarly and see how these genes function in metabolic networks from MetNetDB, a database of Arabidopsis metabolic networks, using animated network graphs. Interactive virtual reality, with its enhanced ability to display more information, makes such integration more effective by abstracting key relationships. AVAILABILITY: MetNet3D and some sample datasets are available at http://www.vrac.iastate.edu/research/sites/metnet/Download/Download.htm. SUPPLEMENTARY INFORMATION: Color snapshots and movies are available at http://www.vrac.iastate.edu/research/sites/metnet/Bioinformatics/SupplementaryInformation.htm.

Today, scientists and engineers are exploring advanced applications and uses of immersive systems that can be cost-effectively applied in their fields. However, one of the impediments to the widespread use of these technologies is the extensive technical expertise required of application developers. A software environment that provides abstractions from specific details of hardware configurations and low-level software tools is needed to provide a common base for the prototyping, development, testing and debugging of applications. This paper describes VR Juggler, a virtual platform for the creation and execution of immersive applications, that provides a virtual reality system-independent operating environment. We focus on the approach taken to specify, design and implement VR Juggler and the benefits derived from our approach.

With the widespread popularity of the Internet and advances in distributed computing and in virtual reality, more flexibility is needed in the development and use of collaborative virtual environments. In this paper, we present Octopus, a cross-platform, object-oriented API for constructing shared virtual worlds. The list of goals for Octopus, a description of its design and a detailed discussion of its implementation are provided. The design description gives explanations of the three components of Octopus: the core that handles networking and data sharing, the interface for implementing user representations in the virtual space (avatars), and the actual implementations of the avatars.

Virtual reality (VR) installations are often unique; every one is a complex blend of hardware devices, displays and computing resources. The configuration of VR software is therefore a difficult and time-consuming process. VR Juggler, our toolkit for VR application development, addresses these problems with a number of innovations. VR Juggler provides a unique system for organizing the configuration information for a system and minimizing the proliferation of configuration files that many systems suffer. It provides a graphical tool, called VjControl, for editing configurations, which can protect users from many common mistakes. VR Juggler also has advanced capabilities for monitoring and altering the configuration of a running immersive application.

We have created an immersive application for statistical graphics and have investigated what benefits it offers over more traditional data analysis tools. We present a description of both the traditional data analysis tools and our virtual environment, and results of an experiment designed to determine if an immersive environment based on the XGobi desktop system provides advantages over XGobi for analysis of high-dimensional statistical data. The experiment included two aspects of each environment: three structure detection (visualization) tasks and one ease of interaction task. The subjects were given these tasks in both the C2 virtual environment and a workstation running XGobi. The experiment results showed an improvement in participants' ability to perform structure detection tasks in the C2 to their performance in the desktop environment. However, participants were more comfortable with the interaction tools in the desktop system.

This paper concentrates on the applicability of virtual reality (VR) technology to science and engineering research. To that end, a look into the effort required to develop effective applications emphasizing software design issues is presented. The applicability and use of these issues is covered for their implementation on the CAVE virtual reality system.