%0 Journal Article
%T SVM-based Identification and Un-calibrated Visual Servoing for Micro-manipulation<br>
%A Xin-Han Huang
%A Xiang-Jin Zeng
%A Min Wang
%A <br>
%J 国际自动化与计算杂志
%D 2010
%I 
%X 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.
%K Micro-assembly
%K support vector machine
%K part identification
%K Broyden method
%K visual servoing<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7139AD613512F4F05F6D525B914296AA&aid=11AD023117B8F02D33FED1DFED286335&yid=140ECF96957D60B2&vid=DF92D298D3FF1E6E&iid=CA4FD0336C81A37A&sid=F4B561950EE1D31A&eid=318E4CC20AED4940&journal_id=1476-8186&journal_name=国际自动化与计算杂志&referenced_num=0&reference_num=21