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

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 positions and orientations of microscale and nanoscale components in the 3-Dimensional 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 generate probable locations and orientations of components in the XY-plane. Finally, signature curves are computed and utilized to obtain component locations and orientations in 3-D space. We have tested these algorithms with silica micro-spheres as well as metallic nanowires. We believe that the algorithms described in this paper will provide the foundation for realizing automated assembly operations in optical tweezers-based assembly cells.

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

Journal of Computing and Information Science in Engineering ◽

10.1115/1.2795306 ◽

2007 ◽

Vol 7 (4) ◽

pp. 330-338 ◽

Cited By ~ 44

Author(s):

Tao Peng ◽

Arvind Balijepalli ◽

Satyandra K. Gupta ◽

Tom LeBrun

Keyword(s):

Optical Tweezers ◽

Three Dimensional ◽

Optical Section ◽

Automated Assembly ◽

Glass Microspheres ◽

Assembly Cell ◽

Computational Speed ◽

On Line ◽

Areas Of Interest ◽

Speed And Accuracy

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.

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Algorithms for Extraction of Nanowires Attributes From Optical Section Microscopy Images

Volume 2: 27th Computers and Information in Engineering Conference, Parts A and B ◽

10.1115/detc2007-35456 ◽

2007 ◽

Cited By ~ 1

Author(s):

Tao Peng ◽

Arvind Balijepalli ◽

Satyandra K. Gupta ◽

Thomas W. LeBrun

Keyword(s):

Optical Tweezers ◽

Building Blocks ◽

Optical Section ◽

Extraction Techniques ◽

Automated Assembly ◽

Assembly Cell ◽

Cell Components ◽

Gradient Based ◽

Areas Of Interest ◽

Microscopy Images

Optical tweezers have emerged as a unique tool for micro and nanomanipulation. In an optical tweezers-based assembly cell, components are usually suspended in a fluidic medium and undergo constant random Brownian motion. Automated assembly using optical tweezers requires online monitoring of components in the assembly workspace. Nanowires are very important building blocks for constructing nanoscale devices. This paper presents algorithms for estimating length, location, and orientation of nanowires in the workspace using images obtained by optical section microscopy. The images are first segmented to locate general areas of interest which are then analyzed to determine discrete nanowire parameters. We use image gradient based techniques as well as feature extraction techniques to identify parameters of nanowire image patterns. These parameters are then used to estimate length, location, and orientation of nanowires.

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Algorithms for Extraction of Nanowire Lengths and Positions From Optical Section Microscopy Image Sequence

Journal of Computing and Information Science in Engineering ◽

10.1115/1.3249573 ◽

2009 ◽

Vol 9 (4) ◽

Cited By ~ 1

Author(s):

Tao Peng ◽

Arvind Balijepalli ◽

Satyandra K. Gupta ◽

Thomas W. LeBrun

Keyword(s):

Image Processing ◽

Optical Tweezers ◽

Image Sequence ◽

Optical Section ◽

Image Frame ◽

Image Processing Techniques ◽

Microscopy Image ◽

Processing Techniques ◽

Areas Of Interest ◽

Microscopy Images

This paper presents algorithms for estimating length, location, and orientation of nanowires in a fluidic workspace using images obtained by optical section microscopy. Images containing multiple nanowires are first segmented to locate general areas of interest, which are then analyzed to determine discrete nanowire parameters. We use a set of image processing techniques to extract features of nanowire image patterns, e.g., boundary of nanowire, linear edges, and the intensity profile of nanowire’s diffraction fringes. The parameters of the features are then used to estimate length, 3D position, and 3D orientation of nanowires. A scene representing the workspace is reconstructed using the estimated attributes of nanowires, and it is constantly updated upon the capture of every image frame. We believe that the work described in this paper will be useful for assembly of nanowires using optical tweezers.

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Design and calibration of an IVEM for general 3-dimensional imaging of non-diffracting materials

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100129838 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1040-1041

Author(s):

Neil Rowlands ◽

Jeff Price ◽

Michael Kersker ◽

Seichi Suzuki ◽

Steve Young ◽

...

Keyword(s):

3D Imaging ◽

Tomographic Reconstruction ◽

Three Dimensional ◽

3 Dimensional ◽

3D Microstructure ◽

Image Translation ◽

Digital Correlation ◽

On Line ◽

Mechanical Stage ◽

Projection Angle

Three-dimensional (3D) microstructure visualization on the electron microscope requires that the sample be tilted to different positions to collect a series of projections. This tilting should be performed rapidly for on-line stereo viewing and precisely for off-line tomographic reconstruction. Usually a projection series is collected using mechanical stage tilt alone. The stereo pairs must be viewed off-line and the 60 to 120 tomographic projections must be aligned with fiduciary markers or digital correlation methods. The delay in viewing stereo pairs and the alignment problems in tomographic reconstruction could be eliminated or improved by tilting the beam if such tilt could be accomplished without image translation.A microscope capable of beam tilt with simultaneous image shift to eliminate tilt-induced translation has been investigated for 3D imaging of thick (1 μm) biologic specimens. By tilting the beam above and through the specimen and bringing it back below the specimen, a brightfield image with a projection angle corresponding to the beam tilt angle can be recorded (Fig. 1a).

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Generalized recognition of single-ended contact formations for use in automated assembly operations

10.2172/325764 ◽

1999 ◽

Author(s):

R. Ravuri ◽

L.J. Everett

Keyword(s):

Automated Assembly ◽

Assembly Operations

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Simulation of Automated Robotic Assembly

Volume 1: 21st Design Automation Conference ◽

10.1115/detc1995-0090 ◽

1995 ◽

Author(s):

Alec R. Miller ◽

Raymond J. Cipra

Keyword(s):

Manufacturing System ◽

Three Dimensional ◽

Robotic Assembly ◽

Automated Assembly ◽

System A ◽

Assembly Cell ◽

Wide Range ◽

Graphical Visualization ◽

Manufacturing Software ◽

Research And Education

Abstract This paper examines the development of a networked simulation system. The Automated Robotic Manipulation (ARM) simulator is a central part of the network. This simulation tool currently assists with research and education into automated assembly. Robots, fixtures, conveyors, and parts create an automated assembly cell which is used to test advanced manufacturing software. ARM animates models of these physical components and enhances them with additional forms of three-dimensional graphical visualization. The feasibility of automated assembly can rapidly be assessed from the visual content presented by the simulator. Input formats for ARM are flexible enough to support a wide range of assembly cells and activities. Files and network transmissions customize the simulator to a particular assembly cell and its activities. The emerging assembly data protocol promotes the development of a truly integrated manufacturing system. A graphical interface complete with multiple views assists assembly cell layout and activity review, and networked operations significantly expand its role to areas such as interactive robot control and assembly preview.

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