A Switched Extend Kalman-Filter for Visual Servoing Applied in Nonholonomic Robot with the FOV Constraint

被引：0

作者：

Fang, Yuan ^{[1
]}

Zhang Xiaoyong ^{[1
]}

Huang Zhiwu ^{[1
]}

Yu, Wentao ^{[1
]}

Wang, Yabo ^{[1
]}

机构：

[1] Cent S Univ, Sch Informat Sci & Engn, Changsha 410075, Hunan, Peoples R China

来源：

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS | 2015年 / 19卷 / 02期

关键词：

EKF; FOV; visual servoing; control; nonholonomic robot;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a switched Kalmanfilter (KF) is used to predict the status of feature points leaving the field of view (FOV), which is one of the most common constraints in FOV. By using the prediction of status to compensate for the real state of feature points, non-holonomic robots conduct visual servoing tasks efficiently. Results of simulation and experiments verify the effectiveness of the proposed approach.

引用

页码：185 / 190

页数：6

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