• 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.

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.

Industrial Augmented Reality (iAR) has demonstrated its advantages to communicate technical information in the fields of maintenance, assembly, and training. However, literature is scattered among different visual assets (i.e., AR visual user interface elements associated with a real scene). In this work, we present a systematic literature review of visual assets used in these industrial fields. We searched five databases, initially finding 1757 papers. Then, we selected 122 iAR papers from 1997 to 2019 and extracted 348 visual assets. We propose a classification for visual assets according to (i) what is displayed, (ii) how it conveys information (frame of reference, color coding, animation), and, (iii) why it is used. Our review shows that product models, text and auxiliary models are, in order, the most common, with each most often used to support operating, checking and locating tasks respectively. Other visual assets are scarcely used. Product and auxiliary models are commonly rendered world-fixed, color coding is not used as often as expected, while animations are limited to product and auxiliary model. This survey provides a snapshot of over 20 years of literature in iAR, useful to understand established practices to orientate in iAR interface design and to present future research directions.

Technical information presentation is evolving from static contents presented on paper or via digital publishing to real-time context-aware contents displayed via virtual and augmented reality devices. We present a Context-Aware Technical Information Management system (CATIM), that dynamically manages (1) what information as well as (2) how information is presented in an augmented reality interface. CATIM acquires context data about activity, operator, and environment, and then based on these data, proposes a dynamic augmented reality output tailored to the current context. The system was successfully implemented and preliminarily evaluated in a case study regarding the maintenance of a hydraulic valve.

Due to the recent advances in technologies for gesture recognition, midair gestures can be considered the interface of the future in a large number of applications. However, designing effective interfaces with midair gestures is not an easy task because the design is application dependent and it must fulfill many requirements at the same time. Despite the availability of general guidelines in the literature, clear and well-established procedures for the optimal design of midair gesture-based interfaces are, to date, not available and remain an open issue. The main contribution of this paper is a user-centered modular framework, which integrates existing and novel methods. It supports the designer considering multiple aspects including ergonomics, memorability, and specific user requirements tailored to the application scenario. The framework involves three design steps and a final validation step, also supported by dedicated software. We tested with success the proposed framework in an industrial case study, where technicians must easily access technical information by browsing digital manuals during maintenance operations.

Text readability with augmented reality head-worn displays is critical and at present time, there are no standard guidelines to follow. The readability depends mainly on background lighting, display technology (i.e., OST: optical see-through or VST: video see-through), and text style (e.g., plain text, outline or billboard). In this work, we addressed the readability limits for industrial activities. We experimented the effects of two background illuminances levels (1,000 lx for very fine basic industrial tasks and 4,000 lx for fine machining), two commercially available head-worn display technologies, variable outline widths and contrast polarity of text. We analyzed the performance of 12 subjects by collecting about 3,400 measurements using a specific test application and followed by qualitative interviews. With high illuminances, VST performed better than OST, regardless of contrast polarity and outline width. We found that negative contrast polarity is preferable with VST, and that just a minimum outline (1 px) around black text is optimal. On the contrary, positive contrast polarity should be used with OST and outline is not effective. Therefore, we evaluated the usage limits of the OST by sampling its contrast sensitivity function.

Efficient text visualization in head-worn augmented reality (AR) displays is critical because it is sensitive to display technology, text style and color, ambient illumination and so on. The main problem for the developer is to know the optimal text style for the specific display and for applications where color coding must be strictly followed because it is regulated by laws or internal practices. In this work, we experimented the effects on readability of two head-worn devices (optical and video see-through), two backgrounds (light and dark), five colors (white, black, red, green, and blue), and two text styles (plain text and billboarded text). Font type and size were kept constant. We measured the performance of 15 subjects by collecting about 5,000 measurements using a specific test application and followed by qualitative interviews. Readability turned out to be quicker on the optical see-through device. For the video see-through device, background affects readability only in case of text without billboard. Finally, our tests suggest that a good combination for indoor augmented reality applications, regardless of device and background, could be white text and blue billboard, while a mandatory color should be displayed as billboard with a white text message.