Assessing AR Visualizations during Non-Complex Assembly: Reporting Preliminary Results from a Crowdsourcing Rework Study
This study assesses the viability of using a simple assembly task as part of a crowdsourcing experiment to evaluate different visualizations in augmented reality (AR). We recruited 36 participants through a crowdsourcing platform to assess how visualization types (i.e., none, contour, and abstract) impact the performance of a gear-box assembly rework task. Our preliminary results suggest that the learning effect associated with manual assembly of a non-complex gearbox object plays a more significant role in improving performance than the type of visualization used. This pilot study also highlights requirements for crowdsourced task difficulty in order to offer potentially viable insights.
Authors
- Alexander Albers (ORCID: https://orcid.org/0000-0002-7573-6093)
- Sławomir Tadeja (ORCID: https://orcid.org/0000-0003-0455-4062)
- Magdalena Igraś-Cybulska (ORCID: https://orcid.org/0000-0001-5621-7901)
- Thomas Bohné (ORCID: https://orcid.org/0000-0001-5986-8638)
Institutions
- University of Cambridge (GB)
- Craft Engineering Associates (United States) (US)
Publication Details
- Published
- 2024-10-21
- DOI
- https://doi.org/10.1109/ismar-adjunct64951.2024.00025
- Primary Topic
- Manufacturing Process and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00