Abstract
Modular integrated construction (MiC) offers high construction quality and efficiency. Currently, geometric quality inspections for modular boxes are conducted manually. Therefore, based on BIM and LiDAR, this study proposes an automated inspection approach for outer wall surfaces and rebars of modular boxes. To extract the targeted modular boxes from complex construction sites, a novel method using scanning stations and ray casting algorithm is introduced. The point clouds of different modular boxes are then recognized and segmented into different component categories based on the pairwise registration with as-designed data. Ultimately, a reference plane-based method is proposed to automatically measure the flatness of outer wall surfaces (FOW) and protruding length of rebars (PLR). Experiments on four modular boxes show an accuracy with errors of 2.6 mm for FOW and 2.8 mm for PLR, showing the potential for enhanced quality control and efficiency of modular construction industry.
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