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RESEARCH PAPERS

Algorithms for On-Line Monitoring of Micro Spheres in an Optical Tweezers-Based Assembly Cell

[+] Author and Article Information
Tao Peng

Mechanical Engineering Department, University of Maryland, College Park, MD 20742

Arvind Balijepalli

Mechanical Engineering Department, University of Maryland, College Park, MD 20742; Manufacturing Engineering Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Stop 1070, Gaithersburg, MD 20899-1070

Satyandra K. Gupta

Mechanical Engineering Department, University of Maryland, College Park, MD 20742; Institute for Systems Research, University of Maryland, College Park, MD 20742

Tom LeBrun

Manufacturing Engineering Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Stop 1070, Gaithersburg, MD 20899-1070

J. Comput. Inf. Sci. Eng 7(4), 330-338 (Aug 09, 2007) (9 pages) doi:10.1115/1.2795306 History: Received September 28, 2006; Revised August 09, 2007

Optical tweezers have emerged as a powerful tool for micro- and nanomanipulation. Using optical tweezers to perform automated assembly requires on-line monitoring of components in the assembly workspace. This paper presents algorithms for estimating three-dimensional positions of microspheres in the assembly workspace. Algorithms presented in this paper use images obtained by optical section microscopy. The images are first segmented to locate areas of interest and then image gradient information from the areas of interest is used to locate the positions of individual micro spheres in the XY plane. Finally, signature curves are computed and utilized to obtain the Z locations of spheres. We have tested these algorithms with glass microspheres of two different sizes under different illumination conditions. Our experiments indicate that the algorithms described in this paper provide sufficient computational speed and accuracy to support the operation of optical tweezers.

Copyright © 2007 by American Society of Mechanical Engineers
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Figures

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Figure 1

Schematic diagram of the imaging module (figure not to the scale)

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Figure 2

Image segmentation

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Figure 3

The rings (or concentric rings) pattern of the images of microspheres

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Figure 4

Construction of the accumulation array from the gradient field

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Figure 5

Gradient field of clustered spheres and the corresponding accumulation array

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Figure 6

Definition of signature curve of the image pattern of a glass sphere

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Figure 7

Example of signature curve computed from an image of a glass sphere

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Figure 8

Signature curves of a glass sphere at different z depths

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Figure 9

Using mask in the computation of signature curve

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Figure 10

Estimated Z coordinates of a 2.47μm sphere by using calibration signature curves obtained under the same illumination condition

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Figure 11

Estimated Z coordinates of a 0.97μm sphere by using calibration signature curves obtained under the same illumination condition

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Figure 12

Estimated Z coordinates of a 0.97μm sphere (under low illumination intensity) by using calibration signature curves obtained under different illumination intensities

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Figure 13

Estimated Z coordinates of a 2.47μm sphere (under medium illumination intensity) by using calibration signature curves obtained under high and medium illumination intensities

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Figure 14

Reconstructed 3D scene of glass spheres

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Figure 15

Resolving clustered spheres

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Figure 16

Resolving spheres overlapping in the Z direction

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