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

F. Bosché
Journal of Advanced Engineering Informatics
Vol. 24, No. 1, pp. 107-118, 2010

Abstract

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 [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 algorithmis 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.


Link to publisher's page
@Article{eth_biwi_00711,
  author = {F. Bosché},
  title = {Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction},
  journal = {Journal of Advanced Engineering Informatics},
  year = {2010},
  month = {},
  pages = {107-118},
  volume = {24},
  number = {1},
  keywords = {}
}