Abstract
In many traditional industries, production instructions are usually provided on paper. Past research has shown the effectiveness of Augmented Reality (AR) for virtual user guidance in various cases. Usually, the main focus lies on 3D overlays and spatially anchored tokens to guide the user. Unfortunately, tracking small and moving objects is not always feasible in highly dynamic or complex environments. Additionally, the setup of anchors, 3D models and guidance procedures is often time-consuming and problem-specific. This study addresses such scenarios and provides empirical results of AR user guidance without employing overlays or object tracking. Therefore, we developed two AR concepts that guide the user using either 2D illustrations or 3D models. For evaluation, we designed a user study in the field of radio-pharmaceuticals, assessing quantitative measurements, usability and cognitive load. The conducted user study indicates that AR can also improve the effectiveness of user guidance in scenarios where direct 3D overlays or object tracking approaches are not feasible. The presented 2D and 3D AR concepts performed similarly, while both lead to fewer errors, faster execution time, and lower cognitive load than the paper instructions. Therefore, to reduce the effort required to create 3D instructions, the use of 2D illustrations could often be the more efficient choice.
Y. Simmen and T. Eggler—Both authors contributed equally to this research.
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Acknowledgements
This work was supported by the project ARIGO funded by the Swiss Innovation Agency Innosuisse (49260.1 IP-LS) and Augmenticon AG. We would like to thank Christian Schmidt, Matthias Friebe and Jamie Gilmartin from Augmenticon AG and Roger Schibli and Annette Krämer from the Institute of Pharmaceutical Sciences at ETH Zurich for the valuable collaboration.
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Simmen, Y., Eggler, T., Legath, A., Agotai, D., Cords, H. (2023). Non-overlayed Guidance in Augmented Reality: User Study in Radio-Pharmacy. In: Zaynidinov, H., Singh, M., Tiwary, U.S., Singh, D. (eds) Intelligent Human Computer Interaction. IHCI 2022. Lecture Notes in Computer Science, vol 13741. Springer, Cham. https://doi.org/10.1007/978-3-031-27199-1_52
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