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Condition Monitoring for Image-Based Visual Servoing Using Kalman Filter

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Advances in Visual Computing (ISVC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9475))

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Abstract

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.

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Author information

Authors and Affiliations

  1. Advanced Robotic Centre, Faculty of Engineering, National University of Singapore, Singapore, Singapore

    Mien Van, Denglu Wu, Shuzi Sam Ge & Hongliang Ren

Authors
  1. Mien Van
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  2. Denglu Wu
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  3. Shuzi Sam Ge
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  4. Hongliang Ren
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Corresponding author

Correspondence to Hongliang Ren .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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© 2015 Springer International Publishing Switzerland

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Van, M., Wu, D., Ge, S.S., Ren, H. (2015). Condition Monitoring for Image-Based Visual Servoing Using Kalman Filter. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_79

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  • DOI: https://doi.org/10.1007/978-3-319-27863-6_79

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27862-9

  • Online ISBN: 978-3-319-27863-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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