Exploring the performance of an augmented reality application for construction layout tasks

摘要

While Building Information Modeling (BIM) adoption has increased in the industry, most office-to-site design communication still happens using 2D paper plans. Augmented Reality (AR) has been shown to be able to deliver design information to end users, but the degree to which it impacts different applications is still being investigated. This paper explores the use of AR for viewing full-scale model content to support point layout tasks. The paper answers questions related to the performance, accuracy, and effort required from practitioners to use AR as compared to traditional paper documentation. Thirty-two current electrical construction practitioners participated in the experiment completing eight layout tasks each. Half of these tasks were completed with AR and the other half were completed using paper. The results suggest AR enables faster layout of points, while requiring less physical and mental demand compared to paper. However, accuracy is significantly less accurate and may be below some installation standards. Through discussions with the partner organization, it was determined that elevation accuracy may not always be a major concern for electrical device layout, since electrical systems are frequently laid out before walls are framed. This means that points are only placed on the ground, negating the need for elevation accuracy during layout. Therefore, the results suggest potential to using a hybrid point layout method, leveraging the faster layout horizontally with AR and the accuracy of elevation measurement using traditional measuring tapes, when necessary. This paper contributes to the AR body of knowledge by empirically demonstrating the performance benefits and drawbacks of current AR technology for point layout tasks as compared to current paper documentation. This will enable practitioners to evaluate whether to use AR for a point layout task, depending on the required accuracy tolerances, and it will enable researchers to study appropriate applications through a better understanding of the capabilities of current generation AR devices.