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

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 cla...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2016-12, Vol.12 (6), p.1998-2007
Main Authors: Van, Mien, Wu, Denglu, Ge, Shuzhi Sam, Ren, Hongliang
Format: Article
Language:English
Subjects:
Actuators
Cameras
Configurations
Control of robots
Failure analysis
Fault detection
Fault diagnosis
fault diagnosis (FD)
Feature extraction
image-based visual servoing (IBVS)
kalman filter (KF)
Kalman filters
robot-vision systems
Servomotors
Visual servoing
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Summary: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.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2016.2590338