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Robot Pose and Velocity Estimation Using a Binocular Vision

  • Conference paper
Book cover Next Wave in Robotics (FIRA 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 212))

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Abstract

A robot state estimation algorithm based on the vision feedback is proposed in the paper. The algorithm consists of an image feature detector and an extended Kalman filter (EKF) based estimator. The detected image features are scale-invariant and provide a robust representation of moving objects and static landmarks in the environment. The recursive EKF-based estimator is utilized to determine the pose and velocity of moving robots. Experiments are carried out on a hand-held binocular camera to verify the performances of the proposed state estimation algorithm. The results show that the integration of the image feature detector and the state estimator is efficient in highly dynamic environments.

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References

  1. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: SURF: speeded up robust features. Computer Vision and Image Understanding 110, 346–359 (2008)

    Article  Google Scholar 

  2. Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: MonoSLAM Real Time Single Camera SLAM. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 1052–1067 (2007)

    Article  Google Scholar 

  3. Wang, Y.T., Lin, M.C., Ju, R.C.: Visual SLAM and Moving Object Detection for a Small-size Humanoid Robot. International Journal of Advanced Robotic Systems 7, 133–138 (2010)

    Google Scholar 

  4. Hutchinson, S., Hager, G.D., Corke, P.I.: A tutorial on visual servo control. IEEE Transactions on Robotics and Automation 12, 651–670 (1996)

    Article  Google Scholar 

  5. Sciavicco, L., Siciliano, B.: Modelling and Control of Robot Manipulators. McGraw-Hill, New York (1996)

    MATH  Google Scholar 

  6. Lindeberg, T.: Feature detection with automatic scale selection. International Journal of Computer Vision 30, 79–116 (1998)

    Article  Google Scholar 

  7. Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60, 91–110 (2004)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Mechanical and Electro-Mechanical Eng., Tamkang Univ., New Taipei City, Taiwan

    Yin-Tien Wang, Shi-Hao Wang & Ying-Chieh Feng

  2. Mechanical Eng., Technology and Science Institute of Northern Taiwan, Taipei, Taiwan

    Jin-Yi Lin

Authors
  1. Yin-Tien Wang
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  2. Shi-Hao Wang
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  3. Ying-Chieh Feng
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  4. Jin-Yi Lin
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, National Cheng Kung University, No. 1, University Road, 701, Tainan City, Taiwan

    Tzuu-Hseng S. Li

  2. National Kaohsiung First University of Science and Technology, 2 Juoyue Road, 40227, Taichung, Taiwan

    Kuo-Yang Tu

  3. Department of Electrical Engineering, Nationan Chung Hsing University, No. 250, Kuo-Kuang Road, 40227, Taichung, Taiwan

    Ching-Chih Tsai

  4. Department of Applied Electronics Technology, National Taiwan Normal University, 162 He-Ping East Road, Section 1, 10610, Taipei, Taiwan

    Chen-Chien Hsu

  5. National Kaohsiung First University of Science and Technology, 2 Juoyue Road, Nantsu District, 811, Kaohsiung City, Taiwan

    Chien-Cheng Tseng

  6. National University of Singapore, Singapore

    Prahlad Vadakkepat

  7. Department of Computer Science,, University of Manitoba, R3T 2N2, Winnipeg, Manitoba, Canada

    Jacky Baltes

  8. Department of Computer Science, University of Manitoba, R3T 2N2, Winnipeg, Manitoba, Canada

    John Anderson

  9. Tamkang University, Taipei, Taiwan

    Ching-Chang Wong

  10. Technische Universität Dortmund, Dortmund, Germany

    Norbert Jesse

  11. Department of Electrical Engineering, National Taiwan University of Science and Technology, 43, Sec. 4, Keelung Rd., 106, Taipei, Taiwan

    Chung-Hsien Kuo

  12. Institute of System Information and Control, National Kaohsiung First University of Science and Technology, 2 Juoyue Road, Nantsu District, 811, Kaohsiung City, Taiwan

    Haw-Ching Yang

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© 2011 Springer-Verlag Berlin Heidelberg

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Wang, YT., Wang, SH., Feng, YC., Lin, JY. (2011). Robot Pose and Velocity Estimation Using a Binocular Vision. In: Li, TH.S., et al. Next Wave in Robotics. FIRA 2011. Communications in Computer and Information Science, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23147-6_17

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  • DOI: https://doi.org/10.1007/978-3-642-23147-6_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23146-9

  • Online ISBN: 978-3-642-23147-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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