Paper Titles
Merging Phase Shifting Interferometry with Confocal Chromatic Microscopy
p.287
Positional Detection in Grating Mosaic Based on Image Processing of Far-Field Diffraction Intensity Patterns in Two Wavelengths
p.291
A Comparison of Image Registration Methods Used for Printed Circuit Board Inspection
p.295
Analyzing the Grating Profile Parameters Based on Scanning-Electron Microscope Images
p.299
Machine Vision Based Tracking Control of a Ball-Beam System
p.301
A Point Matching Method for Stereovision Measurement
p.305
Photogrammetric Measurement of Deformation of Large Deployable Mesh Microwave Antenna
p.309
Photogrammetric Method with Distance Constraint for Profile of Inflatable Space Antenna
p.313
A Research on the Colorimetric Characterization of Digital Camera
p.317

Machine Vision Based Tracking Control of a Ball-Beam System

Article Preview

Abstract:

The dynamic behavior of a ball-beam system is highly nonlinear and its characteristic is difficult to define. In this paper we present a new ball-beam balancing control system using machine vision to feedback the beam angle and ball position on the beam. Adaptive threshold based continuously mean shift vision tracking algorithm is applied to record the ball position and the beam angle with highly captured frame-rate. The proposed vision tracking algorithm is tolerant to lighting influence, highly computing efficiency and more robust than traditional template pattern matching or edge detection algorithm under non-ideal environment. The vision tracking performance is experimentally tested on a ball-beam benchmark system, where a PD controller is applied to control the motion of the ball to maintain balance. Experimental result shows that the beam angle measurement, ball tracking and balancing control of the vision feedback system are robust, accurate and highly efficient.

You might also be interested in these eBooks
Measurement Technology and Intelligent Instruments VIII View Preview

Info:

Periodical:

Key Engineering Materials (Volumes 381-382)

Pages:

301-304

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.381-382.301

Citation:

Cite this paper

Online since:

June 2008

Authors:

Chao Ching Ho, C.L. Shih

Keywords:

A Ball-Beam System, Adaptive Threshold Tracking, Machine Vision, Optical Metrology and Image Processing, Visual Servo Control

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2008 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

References

[1] S. Hutchinson, GD Hager and P. Corke: IEEE Trans. on Robotics and Automation, Vol. 12 (1996), pp.651-670.

Google Scholar

[2] Luigi di Stefano, Stefano Mattoccia, Martino Mola: ICIAP 2003, The International Conference on Image Analysis and Processing (2003), pp.322-327.

Google Scholar

[3] Hauser, S. Sastry, and P. Kokotovi'c: IEEE Transactions on Automatic Control, Vol. 37 (1992), pp.392-398.

Google Scholar

[4] P. Kokotovic: IEEE Control System, Vol. 12 (1992), pp.7-17.

Google Scholar

[5] Y. Cheng: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 17 (1995), pp.790-799.

Google Scholar

[6] GR Bradski et al.: Proc. IEEE Workshop Applications of Computer Vision, (1998), pp.214-219.

Google Scholar

[7] Petrovic, I. Brezak, M. Cupec, R.: Advanced Motion Control, (2002), pp.573-577.

Google Scholar