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Carnegie Mellon Robotics Institute

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Abstract

Defects that occur during the construction process account for a large percentage of overall defects in the built environment. Defects waste time and money, and affect the overall performance of the built environment. These problems can be minimized with proactive application of advanced scanners, sensing, and data modelling techniques. Researchers in the departments of Architecture, Robotics, and Civil and Environmental Engineering at Carnegie Mellon University are investigating ways to integrate suites of emerging evaluation technologies to help find, record, manage, and limit the impact of construction defects. As part of this effort, the researchers have conducted a case study on a construction site near Pittsburgh, Pennsylvania. The case study serves to identify challenges in applying specific reality capture technologies and in coordinating suites of these tools on construction sites. The researchers conducted the following activities: creation of a 3D design model, generation of strategies and mechanisms to create 3D as- built models; establishment of specific measurement goals; creation of laser scanner and sensor planning software; targeted use of laser scanners and wireless embedded sensing for capturing as-built data; and analysis of captured data for possible defects. This paper discusses the process of deploying sensing and scanning tools on the case study construction site, and the process of implementing components of an integrated early defect detection system.

Keywords

laser scanning, embedded sensing, 3D modeling, defect detection

Notes

Sponsor: National Science Foundation, CMS #0121549.

Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Field Robotics Center

Associated Lab(s) / Group(s): Software Systems Group and 3D Computer Vision Group

Associated Project(s): Advanced Sensor Based Defect Management at Construction Sites

Text Reference

C. Gordon, F. Boukamp, Daniel Huber, Edward Latimer, K. Park, and B. Akinci, "Combining Reality Capture Technologies for Construction Defect Detection: A Case Study," EIA9: E-Activities and Intelligent Support in Design and the Built Environment, 9th EuropIA International Conference, October, 2003, pp. 99-108.

BibTeX Reference

@inproceedings{Huber_2003_4670,
   author = "C. Gordon and F. Boukamp and Daniel Huber and Edward Latimer and K. Park and B. Akinci",
   title = "Combining Reality Capture Technologies for Construction Defect Detection: A Case Study",
   booktitle = "EIA9: E-Activities and Intelligent Support in Design and the Built Environment, 9th EuropIA International Conference",
   pages = "99-108",
   month = "October",
   year = "2003",
}

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