Literature DB >> 32759085

What, How, and Why are Visual Assets Used in Industrial Augmented Reality? A Systematic Review and Classification in Maintenance, Assembly, and Training (From 1997 to 2019).

Michele Gattullo, Alessandro Evangelista, Antonio E Uva, Michele Fiorentino, Joseph L Gabbard.   

Abstract

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.

Entities:  

Year:  2021        PMID: 32759085     DOI: 10.1109/TVCG.2020.3014614

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  1 in total

1.  Minimal AR: visual asset optimization for the authoring of augmented reality work instructions in manufacturing.

Authors:  Enricoandrea Laviola; Michele Gattullo; Vito Modesto Manghisi; Michele Fiorentino; Antonio Emmanuele Uva
Journal:  Int J Adv Manuf Technol       Date:  2021-11-30       Impact factor: 3.226

  1 in total

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