Dissertation/Thesis Abstract

A View-Specific Matching Algorithm to Align and Visualize Hidden Assets for Precise Post-drilling Construction
by Yilmaz, Yigit, M.S., Southern Illinois University at Edwardsville, 2019, 36; 27664954
Abstract (Summary)

Invisibility of the hidden assets is a big constraint for safe and efficient construction. One promising solution is to utilize the existing digitalized building information models (BIMs) to visualize the enveloped field information in various construction activities, such as, to map the layouts of rebar and electrical cables embedded in walls for collision-free post-drilling. Recent studies have exploited the potential in use of the augmented reality to blend invisible virtual models and physical objects to the field crew’s views automatically, using either location-based or vision-based positioning algorithm. However existing efforts cannot satisfy the requirements in stability and accuracy for alignment and visualization of hidden assets during post-drilling construction. This study creates a view-specific matching algorithm to quickly and accurately align the views captured from Building Information models (BIMs) and the field, and then visualize the aligned hidden components in augmented reality. This approach is tested in both indoor and outdoor environment to validate individual views in a static mode. The experimental results show great potentials in applying the newly created matching algorithm to the real construction sites to improve the transparency and accuracy for precise post-drilling construction related to hidden assets.

Indexing (document details)
Advisor: Yuan, Chenxi, Lee, H. Felix
Commitee: Ko, Hoo Sang
School: Southern Illinois University at Edwardsville
Department: Industrial Engineering
School Location: United States -- Illinois
Source: MAI 81/7(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Industrial engineering, Engineering
Keywords: Post-drilling construction, View-specific matching
Publication Number: 27664954
ISBN: 9781392858325
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