Model-Free Uncalibrated Visual Servoing Using Recursive Least Squares

被引：3

作者：

Hao, Miao ^{[1
]}

Deuflhard, Peter ^{[2
]}

Sun, Zengqi

Fujii, Masakazu

机构：

[1] Tsinghua Univ, Dept Comp Sci & Technol, Lab Informat Sci & Technol, Beijing, Peoples R China

[2] ZIB, Sci Res Inst, Berlin, Germany

来源：

JOURNAL OF COMPUTERS | 2008年 / 3卷 / 11期

关键词：

Visual Servoing; Jacobian Estimate; Nonlinear Control; Adaptive RLS;

D O I：

10.4304/jcp.3.11.42-50

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, a model free uncalibrated visual servoing algorithm based on recursive least squares is proposed and discussed in depth. No robot kinetics or dynamics, camera calibration or target model to be tracked would be ever needed. Based on the brief retrospection of RLS filter as well as its theoretical analysis, i.e. Wiener-Hopf condition, the core uncalibrated visual servoing algorithm based on recursive least squares is explored in detail. The experimental results of both static and moving targets applied on a Puma-560 6DOFs industrial robot simulation verifies its performances.

引用

页码：42 / 50

页数：9

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