Condition monitoring for Image-based visual servoing using Kalman Filter

Mien Van, Denglu Wu, Sam Shuzhi Ge, Hongliang Ren

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


In image-based visual servoing (IBVS), the control law is based on the error between the current and desired features on the image plane. The visual servoing system is working well only when all the designed features are correctly extracted. To monitor the quality of feature extraction, in this paper, a condition monitoring scheme is developed. First, the failure scenarios of the visual servoing system caused by incorrect feature extraction are reviewed. Second, we propose a residual generator, which can be used to detect if a failure occurs, based on the Kalman filter. Finally, simulation results are given to verify the effectiveness of the proposed method.
Original languageEnglish
Title of host publication11th International Symposium on Visual Computing (ISVC’15), 2015
PublisherSpringer Lecture Notes in Computer Science (LNCS)
Publication statusPublished - 2015


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