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JACIII Vol.19 No.2 pp. 185-190
doi: 10.20965/jaciii.2015.p0185
(2015)

Paper:

A Switched Extend Kalman-Filter for Visual Servoing Applied in Nonholonomic Robot with the FOV Constraint

Yuan Fang, Zhang Xiaoyong, Huang Zhiwu, Wentao Yu, and Yabo Wang

School of Information Science and Engineering, Central South University
Changsha, Hunan 410075, China

Received:
July 1, 2014
Accepted:
November 13, 2014
Published:
March 20, 2015
Keywords:
EKF, FOV, visual servoing, control, nonholonomic robot
Abstract

In this paper, a switched Kalmanfilter (KF) is used to predict the status of feature points leaving the field of view (FOV), which is one of the most common constraints in FOV. By using the prediction of status to compensate for the real state of feature points, nonholonomic robots conduct visual servoing tasks efficiently. Results of simulation and experiments verify the effectiveness of the proposed approach.

References
  1. [1] A. C. Sanderson and L. E. Weiss, “Image--based visual servo control using relational graph error signals,” Proc. IEEE Int. Conf. On Robotics and Automation, pp. 1074-1077, 1980.
  2. [2] S. Hutchinson, G. Hager, and P. I. Corke, “A tutorial on visual servo control,” IEEE Trans. Robot. Autom., Vol.12, No.5, pp. 651-670, Oct. 1996.
  3. [3] F. Chaumette and S. Hutchinson, “Visual servo control Part I: Basic approaches,” IEEE Robot. Autom. Mag., Vol.13, No.4, pp. 82-90, Dec. 2006.
  4. [4] F. Chaumette and S. Hutchinson, “Visual servo control Part II: Advanced approaches,” IEEE Robot. Autom. Mag., Vol.14, No.1, pp. 109-118, Mar. 2007.
  5. [5] Y. Mezouar and F. Chaumette, “Path planning for robust image-based control,” IEEE Trans. Robot. Autom., Vol.18, No.4, pp. 534-549, Aug. 2002.
  6. [6] G. Chesi and Y. S. Hung, “Global path-planning for constrained andoptimal visual servoing,” IEEE Trans. Robot., Vol.23, No.5, pp. 1050-1060, Oct. 2007.
  7. [7] X. Zhang, Y. Fang, and X. Liu, “Motion-Estimation - Based Visual Servoing of Nonholonomic Mobile Robots” IEEE Trans. 2011 on Robotics, Vol.27, No.6, pp. 1167-1175, Dec. 2011.
  8. [8] G. L’opez-Nicolás and S. Bhattacharya, “Switched homography-based visual control of differential drive vehicle swith field-of-viewconstraints,”Proc. IEEE Int. Conf. Robot. Autom., pp. 4238-4244, 2007.
  9. [9] Y. Fang, X. Liu, and X. Zhang, “Adaptive Active Visual Servoing of Nonholonomic Mobile Robots” IEEE Trans. on Industrial Electronics, Vol.59, No.1, pp. 486-479, Jun. 2012.
  10. [17] R. M. Haralick, H. Joo, C. Lee, X. Zhang, V. Vaidya, and M. Kim, “Pose estimation from corresponding point data,” IEEE Trans. Syst., Man, Cybern., Vol.19, No.6, pp. 1426-1446, Nov./Dec. 1989.
  11. [14] W. J. Wilson, C. W. Hulls, and G. S. Bell, “Relative end-effector controlusing Cartesian position based visual servoing,” IEEE Trans. on Robot. Autom., Vol.12, No.5, pp. 684-696, Oct. 1996.
  12. [18] F. Janabi-Sharifi, “Visual servoing: Theory and applications,” in Opto-Mechatronic Systems Handbook, H. Cho, Ed. Boca Raton, FL: CRC, pp. 15-1--15-24, 2002.
  13. [19] W. J. Wilson, C. W. Hulls, and F. Janabi-Sharifi, “Robust image processing and position-based visual servoing,” Robust Vision for Vision-Based Control of Motion, M. Vincze and G. D. Hager (Eds.), New York, IEEE Press, pp. 163-201, 2000.
  14. [10] R. Hartley and A. Zisserman, “Multiple View Geometry in Computer Vision,” Cambridge, U.K., Cambridge Univ. Press, 2000.
  15. [11] Y. Ma, S. Soatto, J. Kuosecká, and S. S. Sastry, “An Invitation to 3-D Vi-sion: From Images to Geometric Models,” New York, Springer, 2003.
  16. [12] K. Deguchi, “Optimal motion control for image-based servoing by de-coupling translation and rotation,” Proc. Int. Conf. Intelligent Robotsand Systems, pp. 705-711, Oct. 1998.
  17. [13] R. Hartley and A. Zisserman, “Multiple View Geometry in Computer Vision,” Cambridge, U.K., Cambridge Univ. Press, 2000.
  18. [15] J. Wang and W. J. Wilson,“3D relative position and orientation estimation using Kalman filtering for robot control,” IEEE Int. Conf. Robot. Autom., Nice, France, pp. 2638-2645, 1992.
  19. [16] G. L. Mariottini, G. Oriolo, and D. Prattichizzo, “Image-Based Visual Servoing for Nonholonomic Mobile Robots Using Epipolar Geometry,” IEEE Trans. on Robotics, Vol.23, No.1, pp. 87-100, 2007.
  20. [20] Y. Fang, W. E. Dixon, D. M. Dawson, and P. Chawda, “Homographybased visual servo regulation of mobile robots,” IEEE Trans. Syst., Man, Cybern. B, Cybern., Vol.35, No.5, pp. 1041-1050, Oct. 2005.

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