Characterization of Laser Scanners and Algorithms for Detecting Flatness Defects on Concrete Surfaces Pingbo Tang, A.M.ASCE 1 ; Daniel Huber 2 ; and Burcu Akinci 3 Abstract: In many construction and infrastructure management projects, it is important to ensure the flatness of concrete surfaces. Inspectors assess the quality of flat surface construction by checking whether a surface deviates from perfectly flat by more than a specified tolerance. Current flatness assessment methods, such as using a straightedge or shape profiler, are limited in the speed or density of their measurements. Laser scanners are general-purpose instruments for densely and accurately measuring three-dimensional shapes. In this paper, we show how laser scanners can be effectively used to assess surface flatness. Specifically, we formalize, implement, and validate three algorithms for processing laser-scanned data to detect surface flatness deviations. Since different scanners and algorithms can perform differently, we define an evaluation framework for objectively evaluating the performance of different algorithms and scanners. Using this framework, we analyze and compare the performance of the three algorithms using data from three laser scanners. The results show that it is possible to detect surface flatness defects as small as 3 cm across and 1 mm thick from a distance of 20 m. DOI: 10.1061/ASCECP.1943-5487.0000073 CE Database subject headings: Inspection; Data processing; Defects; Accuracy; Three-dimensional analysis; Quality control; Con- struction management; Concrete. Author keywords: Inspection; Data processing; Defects; Accuracy; Three-dimensional analysis; Quality control; Construction management. Introduction Surface flatness assessment is an important component of quality control in many construction and infrastructure management projects. For example, evaluation of the flatness of a surface is needed for slabs during building construction American Concrete Institute ACI 2006, for roadways during highway construction, for running surfaces during construction of light-rail systems Tang et al. 2009, and for long-term deformation monitoring of bridges Park et al. 2007. Failures in quality control can be ex- pensive. In general, construction-site defects result in rework costs of up to 6–12% of construction costs Josephson and Ham- marlund 1999; Patterson and Ledbetter 1989. In the architecture/engineering/construction AEC industry, surface flatness assessment is generally based on identifying “flat- ness defects,” which are surface regions having deviations larger than a tolerance from an as-designed plane depicting the ideal shape of the assessed surface. Identification of flatness defects is commonly accomplished by either using a straightedge or a pro- filometer. With the straightedge approach, inspectors use a long straightedge e.g., 3 m to assess a surface using certain measure- ment patterns, such as stars, composed of transverse lines La- timer et al. 2002. Flatness defects are identified by the size of the gap between the surface and straightedge. Alternatively, when using a profilometer, inspectors operate a device that moves above the inspected surface in predefined patterns, such as longi- tudinal and transverse lines. The device takes elevation measure- ments on the surface and compares them to the as-designed elevations to detect flatness defects Latimer et al. 2002. A typi- cal example is the rolling profiler recommended by the American Concrete Institute ACI for measuring slab flatness. This device rolls across a surface, measuring elevations of surface points in 1-ft intervals. It then uses these measurements to calculate a glo- bal flatness measure, called the F-number American Concrete Institute ACI 2006; Stuart 2007. Each of the existing flatness assessment methods has limita- tions in terms of sparseness of measurements, need for surface contact, or measurement speed, issues that are discussed further in the next section. Laser scanning offers an alternative approach that does not suffer from these limitations. A laser scanner is a sensor that measures the three-dimensional 3D structure of an environment by using a laser to measure distances to nearby vis- ible surfaces. Commercially available laser scanners can measure thousands to hundreds of thousands of 3D points per second with uncertainties of a few millimeters at distances of tens of meters or more. Unfortunately, the use of laser scanners for flatness assess- ment is not well understood, and methods for detecting surface flatness defects from laser-scanned data have not been studied. In this paper, we address these issues by showing how laser scanners can be effectively used to assess surface flatness, and we investi- 1 Postdoctoral Researcher, Dept. of Civil and Environment Engineer- ing and Geodetic Science, Ohio State Univ., 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43210-1275 corresponding author. E-mail: tangpingbo@gmail.com 2 Systems Scientist, Robotics Institute RI, Newell-Simon Hall, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: dhuber@cs. cmu.edu 3 Professor, Dept. of Civil and Environmental Engineering, Carnegie Mellon Univ., Pittsburgh, PA 15213. E-mail: bakinci@cmu.edu Note. This manuscript was submitted on September 9, 2009; approved on May 6, 2010; published online on May 14, 2010. Discussion period open until June 1, 2011; separate discussions must be submitted for indi- vidual papers. This paper is part of the Journal of Computing in Civil Engineering, Vol. 25, No. 1, January 1, 2011. ©ASCE, ISSN 0887-3801/ 2011/1-31–42/$25.00. 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