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对称工件定位算法:收敛性及其改进

陈善勇 李圣怡 戴一帆

陈善勇, 李圣怡, 戴一帆. 对称工件定位算法:收敛性及其改进. 自动化学报, 2006, 32(3): 428-432.
引用本文: 陈善勇, 李圣怡, 戴一帆. 对称工件定位算法:收敛性及其改进. 自动化学报, 2006, 32(3): 428-432.
CHEN Shan-Yong, LI Sheng-Yi, DAI Yi-Fan. Symmetric Workpiece Localization Algorithms: Convergence and Improvements. ACTA AUTOMATICA SINICA, 2006, 32(3): 428-432.
Citation: CHEN Shan-Yong, LI Sheng-Yi, DAI Yi-Fan. Symmetric Workpiece Localization Algorithms: Convergence and Improvements. ACTA AUTOMATICA SINICA, 2006, 32(3): 428-432.

对称工件定位算法:收敛性及其改进

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    通讯作者:

    陈善勇

Symmetric Workpiece Localization Algorithms: Convergence and Improvements

More Information
    Corresponding author: CHEN Shan-Yong
  • 摘要: Symmetric workpiece localization algorithms combine alternating optimization and linearization. The iterative variables are partitioned into two groups. Then simple optimization approaches can be employed for each subset of variables, where optimization of configuration variables is simplified as a linear least-squares problem (LSP). Convergence of current symmetric localization algorithms is discussed firstly. It is shown that simply taking the solution of the LSP as start of the next iteration may result in divergence or incorrect convergence. Therefore in our enhanced algorithms, line search is performed along the solution of the LSP in order to find a better point reducing the value of objective function. We choose this point as start of the next iteration. Better convergence is verified by numerical simulation. Besides, imposing boundary constraints on the LSP proves to be another efficient way.
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出版历程
  • 收稿日期:  2004-11-19
  • 修回日期:  2005-09-26
  • 刊出日期:  2006-05-20

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