Evaluation of AR Pattern Guidance Methods for a Surface Cleaning Task

Abstract

Cleanroom cleaning is a surface coverage task where the pattern should be followed correctly, and the entire surface should be covered. We investigate the efficacy of augmented reality (AR) by implementing various pattern guidance designs to enhance a cleanroom cleaning task. We developed an AR guidance system for cleaning procedures and evaluated four distinct pattern guidance methods: (1) breadcrumbs, (2) examples, (3) middle lines, and (4) outlines. We vary the instructions on the entire surface or as a single step. To measure performance, accuracy, and user satisfaction associated with each guidance method, we conducted a large-scale (n=864) between-subjects study. Our findings indicate that single step instructions proved to be more intuitive and efficient than full instructions, especially for the breadcrumbs. We also discussed the implications of our results for the development of AR applications for surface coverage and pattern optimization.