Development of an automated 3D/4D as-built model generation system for construction progress monitoring and quality control Maalek, Reza; Lichti, Derek; Ruwanpura, Janaka
Automating the progress monitoring and control process is of great interest to industry practitioners to help improve the limitations associated with the current manual data collection and analysis practices. Two remote sensing technologies, namely, Light Detection and Ranging (LiDAR) and digital camera, are widely used to acquire 3D point clouds as a means of measuring the “scope of the work performed” of structural elements. However, to assign the collected 3D point clouds to their corresponding structural element, current object-based recognition models use the as-planned 4D model, which may not be reliable in cases where the locations of the as-built structure differ from those of the planned, and/or the planned 4D model is not available with sufficient detail. Here, a novel method is proposed to eliminate the dependency on the as-planned data by automatically generating the 3D/4D as-built model through a robust Principal Component Analysis-based (PCA) segmentation algorithm. The proposed system is also independent of the technology used to capture the 3D point clouds. To evaluate the reliability of the proposed automated as-built model generation procedure, two sets of LiDAR data from the "Mechanics of Materials" laboratory and the "Graduate Student Hall of Residence" construction site at the University of Calgary were collected. A novel method of automated registration of the as-built model to the planned model coordinate system is also proposed through which the compliance of the planned vs. actual dimensions of corresponding structural elements are examined. The results of the two experiments demonstrate the applicability of the proposed methods for the automatic generation of the 3D/4D as-built model and the dimension compliance control of structural elements.
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