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Rebar Spacing Fixing Technology using Laser Scanning and HoloLens

  • Lee, Yeongjoo (Department of Architectural Engineering, Chungbuk National University ) ;
  • Kim, Jeongseop (Department of Architectural Engineering, Chungbuk National University ) ;
  • Lee, Jin Gang (School of Industrial Design Engineering & Architectural Engineering, Korea University of Technology and Education) ;
  • Kim, Minkoo (Department of Architectural Engineering, Chungbuk National University)
  • Received : 2023.02.28
  • Accepted : 2024.02.27
  • Published : 2024.03.31

Abstract

Currently rebar spacing inspection is carried out by human inspectors who heavily rely on their individual experience, lacking a guarantee of objectivity and accuracy in the inspection process. In addition, if incorrectly placed rebars are identified, the inspector need to correct them. Recently, laser scanning and AR technologies have been widely used because of their merits of measurement accuracy and visualization. This study proposes a technology for rebar spacing inspection and fixing by combining laser scanning and AR technology. First, scan data acquisition of rebar layers is performed and the raw scan data is processed. Second, AR-based visualization and fixing are performed by comparing the design model with the model generated from the scan data. To verify the developed technique, performance comparison test is conducted by comparing with existing drawing-based method in terms of inspection time, error detection rate, cognitive load, and situational awareness ability. It is found from the result of the experiment that the AR-based rebar inspection and fixing technology is faster than the drawing-based method, but there was no significant difference between the two groups in error identification rate, cognitive load, and situational awareness ability. Based on the experimental results, the proposed AR-based rebar spacing inspection and fixing technology is expected to be highly useful throughout the construction industry.

Keywords

Acknowledgement

This research was supported by Chungbuk National University Korea National University Development Project (2022).

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