Ladars for construction assessment and update

Cheok, Geraldine S.; Stone, William C.; Lipman, Robert R.; Witzgall, Christoph

doi:10.1016/s0926-5805(00)00058-3

Cited by 65 publications

(26 citation statements)

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“…There are several methods which can be used to register these scan stations by applying one of the two methods, or a combination of them, for example, target based or point cloud based (Mills and Barber, 2004;Rajendra et al, 2014). Using the Global Positioning System (GPS), the co-ordinates based on the laser scanner location can be determined, which can then, according to Cheok et al (2000), -allow for the scans from each position to be brought into a common frame of reference in a global or project co-ordinate system‖. The first method; target based or target-to-target registration, is a registration between multiple point cloud scans and registered into a single point cloud through the use of control targets in the point clouds.…”

Section: Point Cloud Registrationmentioning

confidence: 99%

Digital Heritage Documentation Via TLS And Photogrammetry Case Study

Baik¹

2017

THE IJES

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Section: Point Cloud Registrationmentioning

confidence: 99%

Digital Heritage Documentation Via TLS And Photogrammetry Case Study

Baik¹

2017

THE IJES

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“…Cheok et al demonstrated how LADAR (Laser Distance and Ranging) can be used for construction progress monitoring by focusing on and developing an approach for excavation work [18]. Their approach included generating and analyzing terrain models based on the data collected from LADARs to assess the progress of an excavation activity.…”

Section: Background Researchmentioning

confidence: 99%

A formalism for utilization of sensor systems and integrated project models for active construction quality control

Akinci

Boukamp

Gordon

et al. 2006

Automation in Construction

273

148

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Defects experienced during construction are costly and preventable. However, inspection programs employed today cannot adequately detect and manage defects that occur on construction sites, as they are based on measurements at specific locations and times, and are not integrated into complete electronic models. Emerging sensing technologies and project modeling capabilities motivate the development of a formalism that can be used for active quality control on construction sites. In this paper, we outline a process of acquiring and updating detailed design information, identifying inspection goals, inspection planning, as-built data acquisition and analysis, and defect detection and management. We discuss the validation of this formalism based on four case studies.

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“…In parallel, research has progressed on the use of two and three-dimensional image data for construction progress tracking (Cheok et al 2000, Abeid et al 2003, Shih and Huang 2006, Teizer et al 2007, El-Omari and Moselhi 2008, Ibrahim et al 2009, Ahmed et al 2011c. Another approach to automated progress tracking is based on automatic recognition of construction elements using a priori information such as3D Building Information Models (BIM) and 2D images (Wu et al 2010), or BIM and 3D images (Bosche and Haas 2008).…”

Section: Introductionmentioning

confidence: 99%

Autonomous Modeling of Pipes within Point Clouds

Ahmed¹,

Haas²,

Haas³

2013

Proceedings of the 30th International Symposium on Automation and Robotics in Construction and Mining (ISARC 2013): Building Th

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Three-dimensional models are in increasing demand for design, maintenance, operations and construction project management. Point-clouds are the main output of automatic data collection using laser-scanners and photogrammetric technologies. Pipe-works may comprise 50% of the value of important construction projects such as industrial and research facilities. We have developed a practical and cost-effective approach, based on the Hough-transform and judicious use of domain constraints, to find, recognize and reconstruct/model 3D pipes within point-clouds fully automatically. The developed approach allows pipe growing within a 3D point-cloud. It samples the point-cloud to sequential orthogonal slices, detects pipe's cross-sections within sampled slices and grows the pipe along the cross sections centerlines. It is validated using laser-scanner data from construction of the Engineering-VI building on the University of Waterloo (UW) campus. The system works on a typical laptop. Recognition and localization results are within a few millimeters. The presented approach opens the gate to broad applications of pipe-network modeling.

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Ladars for construction assessment and update

Cited by 65 publications

References 1 publication

Digital Heritage Documentation Via TLS And Photogrammetry Case Study

Digital Heritage Documentation Via TLS And Photogrammetry Case Study

A formalism for utilization of sensor systems and integrated project models for active construction quality control

Autonomous Modeling of Pipes within Point Clouds

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