• Simplifying authoring helps non-experts to create AR technical documentation • We introduced Minimal AR for optimized AR info, but prior tools do not support it • We propose STAAR-TECH, an AR authoring tool aligned with the Minimal AR approach • We validate STAAR-TECH’s effectiveness through a comparative user study • Results show that STAAR-TECH is a highly suitable tool for AR manual creation This study aims to validate STAAR-TECH, an Augmented Reality (AR) authoring tool for technical documentation designed for end users without expertise in AR development. Previous research on AR authoring tools has primarily focused on simplifying interfaces and interactions to enhance usability. However, these tools are inadequate for applying the Minimal AR authoring approach, according to which the information provided through AR visual assets should be the minimum needed to accomplish the task. The focus of this study is to propose an authoring tool that comprehensively adheres to this approach, ensuring the selection and customization of visual assets and their properties, which are essential for optimally conveying all information types according to the literature. To validate its effectiveness, we conducted a comparative user study with Microsoft Dynamics 365 Guides as baseline, involving 32 participants using HoloLens. We measured the authoring performance, the perceived workload, and the user experience while using both tools. Our findings confirmed that STAAR-TECH is a highly suitable tool for AR manual creation. Participants appreciated its extensive visual asset customization and flexibility, reinforcing its potential as an effective solution for AR authoring.

Our research explored the use of Whiskers, Wedge, and Compass augmented reality (AR) visualization techniques (VTs) in an outdoor field-based user study conducted with Search and Rescue (SAR) subject matter experts (SMEs). The goal of this study was to understand what hazard-based out-of-view information SAR responders need and how SAR SMEs prefer information to be presented. We investigated why certain design elements and preattentive properties of these visualization techniques are most preferred for use during a SAR mission. A key aim was to gain insight on what AR design elements can help guide SAR responders away from dangerous out-of-view hazards, while still allowing them to efficiently search for victims. We derived a set of AR VT design guidelines, specifically applicable to dynamic, potentially dangerous environments, through semi-structured interviews with SMEs and thematic analysis of data. We additionally identified how SAR SMEs envision these AR VTs fitting in with the current SAR ecosystem.

Due to the growing adoption of Immersive Virtual Reality (IVR) in various contexts, understanding how virtual workspaces impact humans and how they should be designed is crucial. Exploring optimal design strategies that can enhance well-being within IVR environments becomes important. In real contexts, biophilic design offers a way to improve well-being by introducing natural elements. IVR can go beyond real-world constraints for integrating biophilic elements, but this aspect is scarcely addressed in literature. A valuable assistance to support the design of IVR workspaces could be offered by generative Artificial Intelligence (AI), which is becoming increasingly integrated into everyday life. The aim of this work is twofold: (i) assessing if the biophilic design of IVR workspaces can improve human well-being and (ii) investigating if AI can inspire the biophilic design properly. Thus, we conducted a user study comparing psycho-physiological and subjective metrics in three conditions. A workspace without biophilia was used as a baseline. The same was enriched with two biophilic designs: one suggested by expert designers and another inspired by AI-generated graphics, simulating a not-expert developer. The findings showed that both biophilic designs significantly improved well-being; however, AI suggestions led to a reduced sense of presence in the IVR environment.

This study aims to explore the use of Augmented Reality (AR) visual assets to convey procedural instructions, specifically for conveying information about component orientation. We focused on assembly scenarios where no affordance is provided for orientation while maintaining a consistently high affordance for how components are mounted. This information is recurrent in tasks where users are familiar with components that fit together without needing specialized tools but lack knowledge of the specific orientations required for the assembly. A typical example is placing rubber gaskets that fit smoothly into grooves but where no markings indicate the correct sealing side. We evaluated six different AR presentation modes for conveying component orientation: image, video, static side-by-side product model, animated side-by-side product model, static in-situ product model, and animated in-situ product model. The literature provides no clear agreement on which is the most effective. To fill this gap, we conducted a user study with 36 participants, measuring completion time, accuracy, and cognitive load across the six AR presentation modes. We also analyzed how users interacted with each of them and collected user subjective feedback. Our findings revealed that the animated side-by-side product model ensures better completion time, demanding less cognitive load and being favored by users.

The creation and management of content are among the main open issues for the spread of Augmented Reality. In Augmented Reality interfaces for procedural tasks, a key authoring strategy is chunking instructions and using optimized visual cues, i.e., tailored to the specific information to convey. Nevertheless, research works rarely present rationales behind their choice. This work aims to provide design guidelines for the localization of in-view and not occluded components, which is recurrent information in technical documentation. Previous studies revealed that the most suited visual cues to convey this information are auxiliary models, i.e., abstract shapes that highlight the space region where the component is located. Among them, 3D arrows are widely used, but they may produce ambiguity of information. Furthermore, from the literature, it is unclear how to design auxiliary model shapes and if they are affected by the component shapes. To fill this gap, we conducted two user studies. In the first study, we collected the preference of 45 users regarding the shape, color, and animation of auxiliary models for the localization of various component shapes. According to the results of this study, we defined guidelines for designing optimized auxiliary models based on the component shapes. In the second user study, we validated these guidelines by evaluating the performance (localization time and recognition accuracy) and user experience of 24 users. The results of this study allowed us to confirm that designing auxiliary models following our guidelines leads to a higher recognition accuracy and user experience than using 3D arrows.

Immersive Virtual Reality (IVR) training offers the capability to industrial workers to acquire skills and address complex tasks by immersing them in a safe and controlled virtual environment (VE). However, in the literature, IVR training is mainly based on principles of standardization and efficiency without considering the operators’ well-being. A novel design approach consists of the introduction in the VE of Positive Computing to improve workers’ well-being by applying the Biophilia hypothesis. In this work, we explored the possibility of introducing biophilic elements in a VE training scenario that would support psychological well-being and human potential. However, the introduction of virtual elements not related to the training task may distract operators, impairing their performance. We selected as a training scenario the assembly of a real truck engine. It is accomplished in a workstation, and operators do not interact with the surrounding VE. Therefore, we placed the training area into four different types of VEs: 3D Minimal (MIN), 3D Minimal Biophilic enriched (MIN+BIO), 3D Realistic (REAL), and 3D Realistic Biophilic enriched (REAL+BIO). We compared the MIN and REAL scenarios with the respective biophilic enriched scenarios. The performance of 40 participants was evaluated in terms of completion time, object fixation time, training task accuracy, knowledge accuracy, cognitive load, and user experience. The results revealed that introducing biophilic elements in a VR training environment attracts users’ attention in the idle phase of the training. In contrast, they keep concentrating on the task without worsening their performance during the task accomplishment.