Fault Diagnosis in Image-Based Visual Servoing With Eye-in-Hand Configurations Using Kalman Filter

被引：37

作者：

Van, Mien ^{[1
,2
,3
]}

Wu, Denglu ^{[4
]}

Ge, Shuzhi Sam ^{[5
,6
]}

Ren, Hongliang ^{[1
,2
]}

机构：

[1] Natl Univ Singapore, Dept Biomed Engn, Singapore 117575, Singapore

[2] Natl Univ Singapore, Adv Robot Ctr, Singapore 117575, Singapore

[3] Univ Warwick, Int Mfg Ctr, WMG, Coventry CV4 7AL, W Midlands, England

[4] Natl Univ Singapore, Temasek Labs, Singapore 117580, Singapore

[5] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117580, Singapore

[6] Natl Univ Singapore, Social Robot Lab, Singapore 117580, Singapore

来源：

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2016年 / 12卷 / 06期

关键词：

Control of robots; fault diagnosis (FD); image-based visual servoing (IBVS); kalman filter (KF); robot-vision systems; PART I; FEATURES;

D O I：

10.1109/TII.2016.2590338

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the fault diagnosis (FD) problem in image-based visual servoing with eye-in-hand configurations is investigated. The potential failures are detected and isolated based on approximating parameters related. First, the failure scenarios of the visual servoing systems are reviewed and classified into the actuator and sensor faults. Second, a residual generator is proposed to detect the failure occurrences, based on the Kalman filter. Third, a decision table is proposed to isolate the fault type. Finally, simulation and experimental results are given to validate the efficacy and the efficiency of the proposed FD strategies.

引用

页码：1998 / 2007

页数：10

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