Pipe radius estimation using Kinect range cameras

Abstract In the heavy construction industry, pipe spool assembly is geometrically complex and suboptimal fabrication processes inevitably lead to fabrication errors and costly rework. In an attempt to mitigate fabrication risks and improve product quality, computer aided tools are being developed to provide an additional layer of control. In this paper, the data acquisition capabilities of two low-cost range cameras are investigated for the eventual purpose of pipe fitting process monitoring in a smart fabrication facility environment. Range images of various pipes are systematically taken at varying distances from the sensor. By using the proposed radius estimation algorithm, the utility of the data for accurate geometrical pipe feature detection is evaluated by a radius feature metric. Results show that the algorithm reliably extracts radius information from point clouds representing piping. In conjunction with the algorithm, the low-cost range camera hardware was able to characterize pipes, of radius ranging from 2.41 cm to 8.78 cm at a distance from the sensor ranging from 0.5 m to 3.75 m, with an average error of 18% for Kinect 1 and 10% for Kinect 2.

[1]  Bon-Gang Hwang,et al.  Measuring the Impact of Rework on Construction Cost Performance , 2009 .

[2]  Fernanda Leite,et al.  Evaluation of accuracy of as-built 3D modeling from photos taken by handheld digital cameras , 2012 .

[3]  Arjan Kuijper,et al.  Estimation of Curvatures in Point Sets based on Geometric Algebra , 2010, VISAPP.

[4]  Carl T. Haas,et al.  Pipe spool recognition in cluttered point clouds using a curvature-based shape descriptor , 2016 .

[5]  Carl T. Haas,et al.  Automated 3D compliance checking in pipe spool fabrication , 2014, Adv. Eng. Informatics.

[6]  Ioannis K. Brilakis,et al.  A videogrammetric as-built data collection method for digital fabrication of sheet metal roof panels , 2013, Adv. Eng. Informatics.

[7]  Mani Golparvar-Fard,et al.  Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques , 2011 .

[8]  Shi-Min Hu,et al.  Robust principal curvatures on multiple scales , 2006, SGP '06.

[9]  Carl T. Haas,et al.  Kinematics chain based dimensional variation analysis of construction assemblies using building information models and 3D point clouds , 2017 .

[10]  Sander Oude Elberink,et al.  Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications , 2012, Sensors.

[11]  Yong K. Cho,et al.  As-built error modeling for effective 3D laser scanning on construction sites , 2013 .

[12]  Peter E.D. Love,et al.  Quantifying the causes and costs of rework in construction , 2000 .

[13]  Jochen Teizer,et al.  Real-time construction worker posture analysis for ergonomics training , 2012, Adv. Eng. Informatics.

[14]  Manfredo P. do Carmo,et al.  Differential geometry of curves and surfaces , 1976 .

[15]  Carl T. Haas,et al.  Skeleton-based discrepancy feedback for automated realignment of industrial assemblies , 2016 .

[16]  Carl T. Haas,et al.  Optimum Assembly Planning for Modular Construction Components , 2017 .

[17]  Ling Shao,et al.  Enhanced Computer Vision With Microsoft Kinect Sensor: A Review , 2013, IEEE Transactions on Cybernetics.

[18]  Mani Golparvar-Fard,et al.  Segmentation of building point cloud models including detailed architectural/structural features and MEP systems , 2015 .

[19]  Manolis I. A. Lourakis,et al.  Automated as-built 3D reconstruction of civil infrastructure using computer vision: Achievements, opportunities, and challenges , 2015, Adv. Eng. Informatics.

[20]  Chih-Chen Chang,et al.  Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM , 2016 .

[21]  Mani Golparvar-Fard,et al.  Vision-based workface assessment using depth images for activity analysis of interior construction operations , 2014 .

[22]  Frédéric Bosché,et al.  As-built data acquisition and its use for production monitoring and automated layout in civil infrastructure: a survey , 2015 .

[23]  Changmin Kim,et al.  3D reconstruction of as-built industrial instrumentation models from laser-scan data and a 3D CAD database based on prior knowledge , 2015 .

[24]  Tarek Hegazy,et al.  Incorporating rework into construction schedule analysis , 2011 .

[25]  Peter E.D. Love,et al.  Influence of Project Type and Procurement Method on Rework Costs in Building Construction Projects , 2002 .