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Technical Briefs

Develop a Robot-Aided Area Sensing System for 3D Shape Inspection

[+] Author and Article Information
Quan Shi1

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48823qshi@ppg.com

Ning Xi

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48823xin@egr.msu.edu

Chi Zhang

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48823zhangc11@msu.edu

1

Corresponding author.

J. Manuf. Sci. Eng 132(1), 014502 (Jan 07, 2010) (4 pages) doi:10.1115/1.4000756 History: Received June 03, 2007; Revised November 04, 2009; Published January 07, 2010; Online January 07, 2010

Dimensional inspection using a contact-based coordinate measurement machine (CMM) is time consuming because the part can only be measured point-by-point. A 3D sensor may replace the traditional CMM technology because it can measure a surface patch-by-patch. Therefore, the automotive industry has been seeking a practical solution for rapid surface inspection using a 3D sensor. However, the challenge is the capability to meet all the requirements including sensor accuracy, resolution, system efficiency, and system cost. In this paper, we develop a robot-aided 3D sensing system, which can automatically allocate sensor viewing points, measure the freeform part surface, and generate an error map for quality control. The measurement accuracy meets the industrial standards. This paper briefly describes the system architecture, design principle, calibration methods, and the present results.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 1

Area sensor calibration using pixel-to-pixel strategy

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Figure 2

Visibility constraints of an area sensor

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Figure 3

Integration of planning constraints using a bounding box method

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Figure 4

3D scan on different viewpoints

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Figure 5

Evaluating sensor precision using a depth-verified gauge (four slots are fabricated, from left to right, the depths are: 32±1 μm, 24±1 μm, 14±2 μm, and 6±2 μm)

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Figure 6

Point clouds measured on each viewpoint

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Figure 7

Register the final point cloud to the CAD model

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Figure 8

The developed error map of pillar, m32510

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Figure 9

An automotive door panel

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Figure 10

The point cloud of the measured door panel

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