We present an empirical study that evaluates the effectiveness of technical maintenance assisted with interactive augmented reality instructions. Our approach consists in an augmented visualization on a large screen and a combination of multiple fixed and mobile cameras. We used commercially available solutions. In our test, 14 participants completed a set of 4 maintenance tasks based on manual inspections of a motorbike engine. Tool selection, removal of bolts, and part disassembly, are supported by visual labels, 3D virtual models and 3D animations. All participants executed similar operations in two modalities: paper manuals and augmented instructions. Statistical analyses proved that augmented instructions reduced significantly participants’ overall execution time and error rate.

lo scambio dati nei vari formati CAD è ancora un problema per l'industria. Questo articolo presenta una panoramica su cinque dei formati più diffusi.

The interaction metaphor, based on mouse, monitor and keyboard, presents evident limits in the engineering design review activities, when real and virtual models must be explored and compared, and also in "outside-the-office" environments, where the desk is not available. The presented research aims to explore a new generation of gesture-based interfaces, called "natural interfaces", which promise an intuitive control using free hands and without the desk support. We present a novel natural design review workspace which acquires user motion using a combination of video and depth cameras and visualizes the CAD models using monitor-based augmented reality. We implemented a bimanual egocentric pointer paradigm by a virtual active surface in front of the user. We used a XML configurable approach to explore bimanual gesture commands to browse, select, dis/assembly and explode 3D complex models imported in standard STEP format. Our experiments demonstrated that the virtual active surface is able to effectively trigger a set of CAD specific commands and to improve technical navigation in non-desktop environments: e.g. shop floor maintenance, on site quality control, etc. We evaluated the feasibility and robustness of the interface and reported a high degree of acceptance from the users who preferred the presented interface to a unconstrained 3D manipulation.

The application of Augmented Reality in industrial environments requires an effective visualization of text on see-through head mounted display. The main contribution of this work is an empirical study of text styles as viewed through a monocular optical see-through display on three real workshop backgrounds examining four colors and four different text styles. We ran 2520 test trials with 14 participants using a mixed design and evaluated completion time and error rates. We found that both presentation mode and background influence the readability of text but there is no interaction effect between these two variables. Another interesting aspect is that the presentation mode influences differently completion time and error rate. The present study allows us to draw some guidelines for an effective use of AR text visualization in industrial environments. We suggest maximum contrast when reading time is important, and the use of colors to reduce errors. We also recommend colored billboard with transparent text where colors have a specific meaning.

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.

A correct recognition of nonverbal expressions is currently one of the most important challenges of research in the field of human computer interaction. The ability to recognize human actions could change the way to interact with machines, maybe the way to live. In this paper, the innovative recognition system developed in the Italian research project PON SS-RR, finalized to support the classification process of the two behavioral situations (resonance and dissonance) of a candidate applying for a job position, is focused and described.