Using AR and YOLOv8-Based Object Detection to Support Real-World Visual Search in Industrial Workshop: Lessons Learned from a Pilot Study

Łysakowski, Mikołaj; Żywanowski, Kamil; Banaszczyk, Adam; Nowicki, Michał R.; Skrzypczyński, Piotr; Tadeja, Sławomir Konrad

doi:10.1109/ismar-adjunct60411.2023.00039

2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) 2023

DOI: 10.1109/ismar-adjunct60411.2023.00039

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Using AR and YOLOv8-Based Object Detection to Support Real-World Visual Search in Industrial Workshop: Lessons Learned from a Pilot Study

Mikołaj Łysakowski,

Kamil Żywanowski,

Adam Banaszczyk

et al.

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2024

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Decision support for augmented reality-based assistance systems deployment in industrial settings

Bock,

Bohné,

Tadeja

2024

Multimed Tools Appl

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The successful deployment of augmented reality (AR) in the industry for on-the-job guidance depends heavily on factors such as the availability of required expertise, existing digital content and other deployment-related criteria such as a task’s error-proneness or complexity. Particularly in idiosyncratic manufacturing situations involving customised products and diverse complex and non-complex products and its variants, the applicability and attractiveness of AR as a worker assistance system is often unclear and difficult to gauge for decision-makers. To address this gap, we developed a decision support tool to help prepare customised deployment strategies for AR-based assistance systems utilising manual assembly as the main example. Consequently, we report results from an interview study with sixteen domain experts. Furthermore, when analysing captured expert knowledge, we found significant differences in criteria weighting based on task complexity and other factors, such as the effort required to obtain data.

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Decision support for augmented reality-based assistance systems deployment in industrial settings

Bock,

Bohné,

Tadeja

2024

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

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Using AR and YOLOv8-Based Object Detection to Support Real-World Visual Search in Industrial Workshop: Lessons Learned from a Pilot Study

Cited by 1 publication

References 21 publications

Decision support for augmented reality-based assistance systems deployment in industrial settings

Decision support for augmented reality-based assistance systems deployment in industrial settings

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