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Search Publications by: Marek Franaszek (Fed)

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Displaying 26 - 50 of 53

Optimization of Registration Performance Metrics

February 25, 2016
Author(s)
Marek Franaszek, Geraldine Cheok
Perception systems are a very important component of automation and robotics. These systems localize objects in its local coordinate frame and the data has to be available for use in another coordinate frame. This requires that the data be transformed from

Real-Time Monitoring: Augmenting Building Information Modeling with 3D Imaging Data to Control Drilling for Embeds into Reinforced Concrete Bridge Decks

September 16, 2013
Author(s)
Manu Akula, Robert R. Lipman, Marek Franaszek, Geraldine Cheok, Kamel Saidi, Vineet Kamat
A major contributing factor attributed to accidents in construction is the lack of hazard recognition due to limited visibility that characterizes construction projects. Real-time monitoring systems that utilize context aware computing techniques

Variances of Cylinder Parameters Fitted to Range Data

September 26, 2012
Author(s)
Marek Franaszek
Industrial pipelines are frequently scanned with 3D imaging systems (e.g., LADAR) and cylinders are fitted to the collected data. Then, the fitted as-built model is compared with the as-designed model. Meaningful comparison between the two models requires

Image-based 3D Mapping of Rebar Location for Automated Assessment of Safe Drilling Areas Prior to Placing Embedments in Concrete Bridge Decks

May 23, 2012
Author(s)
Mani Golparvar-Fard, Behshad Ghadimi, Kamel Saidi, Geraldine Cheok, Marek Franaszek, Robert R. Lipman
This paper presents a new image-based approach for 3D mapping the locations of the rebar and embedded components in a railway bridge deck prior to placement of concrete. Our approach enables practitioners to quickly and automatically identify where the

Development and Use of the NIST Intelligent and Automated Construction Job Site Testbed

December 16, 2011
Author(s)
Kamel Saidi, Geraldine Cheok, Marek Franaszek, Christopher U. Brown, Jeremy Swerdlow, Robert R. Lipman, Itai Katz, Mani Golparvar-Fard, Paul Goodrum, Manu Akula, Gabriel Dadi, Behshad Ghadimi
The Intelligent and Automated Construction Job Site (IACJS) Testbed is a large laboratory facility that was established at the National Institute of Standards and Technology (NIST) in 2011. The creation of the testbed was motivated by the need for such

Characterization of the Range Performance of a 3D Imaging System (NIST TN 1695)

May 9, 2011
Author(s)
Geraldine S. Cheok, Kamel S. Saidi, Marek Franaszek, James J. Filliben, Nicholas Scott
A 3D imaging instrument is a non-contact measurement instrument used to rapidly obtain 3D information about a scene or object. The use of and the applications for these instruments have grown tremendously in the last decade. The expanded use of 3D imaging

3D Imaging Systems for Manufacturing, Construction, and Mobility (NIST TN 1682)

December 15, 2010
Author(s)
Geraldine S. Cheok, Maris Juberts, Marek Franaszek
The National Defense Center of Excellence for Industrial Metrology and 3D Imaging (COE-IM3DI) is conducting research to enable the next generation of manufacturing-centric human/instrument/machine interaction. The generalized goal of the COE-IM3DI research

Variances of Plane Parameters Fitted to Range Data

May 5, 2010
Author(s)
Marek Franaszek
Formulas for variances of plane parameters fitted with Nonlinear Least Squares to points cloud acquired by 3D imaging systems (e.g., LADAR) are derived. Two different error functions used in minimization are discussed: the orthogonal and the directional

Proceedings of the GSA 3D Imaging Workshop, February 28, 2011 (NIST TN 1699)

December 9, 2009
Author(s)
Geraldine S. Cheok, Marek Franaszek, Kamel S. Saidi
The General Services Administration (GSA) has been involved in 3D imaging since the early 2000s. Since 3D imaging was a relatively new technology at that time, GSA needed to develop and provide initial guidance to their project managers (PMs) on 3D imaging

Fitting Spheres to Range Data from 3D Imaging Systems

October 1, 2009
Author(s)
Marek Franaszek, Geraldine S. Cheok, Kamel S. Saidi, Christoph J. Witzgall
Two error functions used for nonlinear Least Squares (LS) fitting of spheres to range data from 3D imaging systems are discussed: orthogonal error function and directional error function. Both of the functions allow unrestricted gradient-based minimization

Gauging the Repeatability of 3D Imaging Systems by Sphere Fitting

September 30, 2009
Author(s)
Marek Franaszek, Geraldine S. Cheok, Kamel S. Saidi
Multiple scans of the same object acquired with 3D imaging system (e.g., laser scanner) in the same experimental conditions could provide valuable information about the instrument s performance (e.g., stability, existence of bias, measurement error)

Sensitivities and Variances for Fitted Parameters of Spheres

July 1, 2009
Author(s)
Christoph J. Witzgall, Marek Franaszek
Experimental data have been gathered by applying 3D imaging systems, such as LIDAR/LADAR instruments, to spherical objects. This report provides a compilation of the statistical and analytical procedures to be used for an evaluation, to be reported

Target Penetration of Laser-Based 3D Imaging Systems

January 19, 2009
Author(s)
Geraldine S. Cheok, Kamel S. Saidi, Marek Franaszek
The ASTM E57.02 Test Methods Subcommittee is developing a test method to evaluate the ranging performance of a 3D imaging system. The test method will involve either measuring the distance between two targets or between an instrument and a target. The