Surface Feature Identification Using a Vision-Based Manifold for Robotic Demanufacturing

[+] Author and Article Information
Michael M. Bailey-Van Kuren

Department of Manufacturing and Mechanical Engineering, Miami University, Oxford, OH 45056baileym@muohio.edu

J. Manuf. Sci. Eng 128(2), 523-530 (Mar 14, 2005) (8 pages) doi:10.1115/1.2114911 History: Received July 16, 2003; Revised March 14, 2005

Robotic demanufacturing requires efficient operation on complex product surfaces from a diverse product stream. A new vision-based approach for surface identification is proposed. Vision-based information defines a surface manifold utilizing structured lighting. The surface manifold model is integrated with a surface estimation model to relate information back to the robot work space. A technique for developing surface patches related to surface objects detected in machine vision images is shown. Case study results from a scrap keyboard are presented and discussed. It is shown that the method iteratively generates a complete surface patch for any viewable surface object.

Copyright © 2006 by American Society of Mechanical Engineers
Topics: Robotics , Manifolds
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Figure 4

Surface modeling using vision systems

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Figure 5

Diagram of topological space

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Figure 6

Series of images captured on a structured lighted surface

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Figure 7

Diagram of manifold based on four images

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Figure 8

Product feature overlay on image

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Figure 9

Product feature overlay on surface manifold

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Figure 10

Camera model parameters

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Figure 11

Example image from machine vision system

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Figure 12

Binarized image of structured lighting on a keyboard

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Figure 13

Binarized image identifying fastener feature on a keyboard

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Figure 14

Binarized image identifying seam feature on a keyboard

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Figure 15

Plot of complete manifold showing initial feature node sets

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Figure 1

Example product for demanufacturing

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Figure 2

Flowchart of manifold-based method

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Figure 3

Results of stereo vision surface feedback (a) limited feedback region and (b) missed surface region




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