Xin-Han Huang, Xiang-Jin Zeng and Min Wang. SVM-based Identification and Un-calibrated Visual Servoing for Micro-manipulation. International Journal of Automation and Computing, vol. 7, no. 1, pp. 47-54, 2010. DOI: 10.1007/s11633-010-0047-1
Citation: Xin-Han Huang, Xiang-Jin Zeng and Min Wang. SVM-based Identification and Un-calibrated Visual Servoing for Micro-manipulation. International Journal of Automation and Computing, vol. 7, no. 1, pp. 47-54, 2010. DOI: 10.1007/s11633-010-0047-1

SVM-based Identification and Un-calibrated Visual Servoing for Micro-manipulation

  • This paper presents an improved support vector machine (SVM) algorithm, which employs invariant moments-based edge extraction to obtain feature attribute. A heuristic attribute reduction algorithm based on rough set s discernible matrix is proposed to identify and classify micro-targets. To avoid the complicated calibration for intrinsic parameters of camera, an improved Broyden s method is proposed to estimate the image Jacobian matrix which employs Chebyshev polynomial to construct a cost function to approximate the optimization value. Finally, a visual controller is designed for a robotic micromanipulation system. The experiment results of micro-parts assembly show that the proposed methods and algorithms are effective and feasible.
  • loading

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return