Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction

By Frederic N. Bosche. Advanced Engineering Informatics, 2010

500 citations recorded by the source corpus.

The construction industry lacks solutions for accurately, comprehensively and efficiently tracking the three-dimensional (3D) status of buildings under construction. Such information is however critical to the successful management of construction projects: It supports fundamental activities such as progress tracking and construction dimensional quality control. In this paper, a new approach for automated recognition of project 3D Computer-Aided Design (CAD) model objects in large laser scans is presented, with significant improvements compared to the one originally proposed in Bosche et al. (in press) [11]. A more robust point matching method is used and registration quality is improved with the implementation of an Iterative Closest Point (ICP)-based fine registration step. Once the optimal registration of the project's CAD model with a site scan is obtained, a similar ICP-based registration algorithm is proposed to calculate the as-built poses of the CAD model objects. These as-built poses are then used for automatically controlling the compliance of the project with respect to corresponding dimensional tolerances. Experimental results are presented with data obtained from the erection of an industrial building's steel structure. They demonstrate the performance in real field conditions of the model registration and object recognition algorithms, and show the potential of the proposed approach for as-built dimension calculation and control.

Subfields: Aerospace Engineering, Civil and Structural Engineering, Geology

View Paper: https://www.semanticscholar.org/paper/59deb997a07054b34f955a13db2f6ce4d6a9d422

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Citations in the corpus

Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM (2016, methodology): “Bosche [6] proposed a technique for recognizing 3D CAD objects from laser-scanned data for dimensional compliance control of steel elements.”
A framework for dimensional and surface quality assessment of precast concrete elements using BIM and 3D laser scanning (2015, methodology): “As for the dimensional QA, Bosche [10] proposed an automated technique of recognizing 3D CAD objects from laserscanned data for dimensional compliance inspection of construction elements.”
Automated dimensional quality assessment of precast concrete panels using terrestrial laser scanning (2014, methodology): “Bosche [4] proposed an automated technique of recognizing 3D CAD objects from laser-scanned data for dimensional compliance inspection of construction elements.”
Research trends and opportunities of augmented reality applications in architecture, engineering, and construction (2013, methodology): “The methods used to determine the geometric properties from captured images or point clouds are essential in displaying an AR [58,59].”
Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data (2011, methodology): “Our goal is to develop tools to help automate this process using techniques from computer vision and machine learning (Xiong and Huber, 2010; Adan et al., 2011; Adan and Huber, 2011, 2010; Anil et al., 2011a).”
A review and outlook for a 'Building Information Model' (BIM): A multi-standpoint framework for technological development (2011, unknown): “, laser, machine vision, RFID, or photogrammetry [21,39,93,95,104,106].”
State of research in automatic as-built modelling (2015, background): “This section describes works that can achieve these tasks in a fully automatic manner; other works that depend on some form of user input exist, but they are not described here in detail [16,17].”