LMI-BASED TRAJECTORY PLANNING FOR CLOSED-LOOP CONTROL OF ROBOTIC SYSTEMS WITH VISUAL FEEDBACK

Graziano Chesi

Abstract

Closed-loop robot control based on visual feedback is an important research area, with useful applications in various fields. Planning the trajectory to be followed by the robot allows one to take into account multiple constraints during the motion, such as limited field of view of the camera and limited workspace of the robot. This paper proposes a strategy for path-planning from an estimate of the point correspondences between the initial view and the desired one, and an estimate of the camera intrinsic parameters. This strategy consists of generating a parametrization of the trajectories connecting the initial location to the desired one via polynomials. The trajectory constraints are then imposed by using suitable relaxations and LMIs (linear matrix inequalities). Some examples illustrate the proposed approach.

References

  1. Allotta, B. and Fioravanti, D. (2005). 3D motion planning for image-based visual servoing tasks. In Proc. IEEE Int. Conf. on Robotics and Automation, Barcelona, Spain.
  2. Chaumette, F. and Hutchinson, S. (2006). Visual servo control, part I: Basic approaches. IEEE Robotics and Automation Magazine, 13(4):82-90.
  3. Chaumette, F. and Hutchinson, S. (2007). Visual servo control, part II: Advanced approaches. IEEE Robotics and Automation Magazine, 14(1):109-118.
  4. Chesi, G. (2009a). Camera displacement via constrained minimization of the algebraic error. IEEE Trans. on Pattern Analysis and Machine Intelligence, 31(2):370-375.
  5. Chesi, G. (2009b). Visual servoing path-planning via homogeneous forms and LMI optimizations. IEEE Trans. on Robotics, 25(2):281-291.
  6. Chesi, G., Garulli, A., Tesi, A., and Vicino, A. (2003). Solving quadratic distance problems: an LMI-based approach. IEEE Trans. on Automatic Control, 48(2):200-212.
  7. Chesi, G., Garulli, A., Tesi, A., and Vicino, A. (2009). Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems. Springer (in press).
  8. Chesi, G. and Hashimoto, K. (2004). A simple technique for improving camera displacement estimation in eye-inhand visual servoing. IEEE Trans. on Pattern Analysis and Machine Intelligence, 26(9):1239-1242.
  9. Chesi, G., Hashimoto, K., Prattichizzo, D., and Vicino, A. (2004). Keeping features in the field of view in eyein-hand visual servoing: a switching approach. IEEE Trans. on Robotics, 20(5):908-913.
  10. Chesi, G. and Hung, Y. S. (2007). Global path-planning for constrained and optimal visual servoing. IEEE Trans. on Robotics, 23(5):1050-1060.
  11. Chesi, G., Tesi, A., Vicino, A., and Genesio, R. (1999). On convexification of some minimum distance problems. In 5th European Control Conf., Karlsruhe, Germany.
  12. Chesi, G. and Vicino, A. (2004). Visual servoing for large camera displacements. IEEE Trans. on Robotics, 20(4):724-735.
  13. Corke, P. I. and Hutchinson, S. (2001). A new partitioned approach to image-based visual servo control. IEEE Trans. on Robotics and Automation, 17(4):507-515.
  14. Cowan, N. J. and Chang, D. E. (2005). Geometric visual servoing. IEEE Trans. on Robotics, 21(6):1128-1138.
  15. Deng, L., Janabi-Sharifi, F., and Wilson, W. J. (2005). Hybrid motion control and planning strategy for visual servoing. IEEE Trans. on Industrial Electronics, 52(4):1024-1040.
  16. Gans, N. and Hutchinson, S. (2007). Stable visual servoing through hybrid switched-system control. IEEE Trans. on Robotics, 23(3):530-540.
  17. Hashimoto, K. (1993). Visual Servoing: Real-Time Control of Robot Manipulators Based on Visual Sensory Feedback. World Scientific, Singapore.
  18. Hashimoto, K., Kimoto, T., Ebine, T., and Kimura, H. (1991). Manipulator control with image-based visual servo. In Proc. IEEE Int. Conf. on Robotics and Automation, pages 2267-2272.
  19. Iwatsuki, M. and Okiyama, N. (2005). A new formulation of visual servoing based on cylindrical coordinate system. IEEE Trans. on Robotics, 21(2):266-273.
  20. Kazemi, M., Gupta, K., and Mehran, M. (2009). Global path planning for robust visual servoing in complex environments. In Proc. IEEE Int. Conf. on Robotics and Automation, Kobe, Japan.
  21. Lopez-Nicolas, G., Bhattacharya, S., Guerrero, J. J., Sagues, C., and Hutchinson, S. (2007). Switched homography-based visual control of differential drive vehicles with field-of-view constraints. In Proc. IEEE Int. Conf. on Robotics and Automation, pages 4238- 4244, Rome, Italy.
  22. Malis, E. (2004). Visual servoing invariant to changes in camera-intrinsic parameters. IEEE Trans. on Robotics and Automation, 20(1):72-81.
  23. Malis, E. and Chaumette, F. (2000). 2 1/2 D visual servoing with respect to unknown objects through a new estimation scheme of camera displacement. Int. Journal of Computer Vision, 37(1):79-97.
  24. Malis, E., Chesi, G., and Cipolla, R. (2003). 2 1/2 D visual servoing with respect to planar contours having complex and unknown shapes. Int. Journal of Robotics Research, 22(10):841-853.
  25. Mezouar, Y. and Chaumette, F. (2002). Path planning for robust image-based control. IEEE Trans. on Robotics and Automation, 18(4):534-549.
  26. Miura, K., Hashimoto, K., Inooka, H., Gangloff, J. A., and de Mathelin, M. F. (2006). Model-less visual servoing using modified simplex optimization. Journal Artificial Life and Robotics, 10(2):131-135.
  27. Park, J. and Chung, M. (2003). Path planning with uncalibrated stereo rig for image-based visual servoing under large pose discrepancy. IEEE Trans. on Robotics and Automation, 19(2):250-258.
  28. Tahri, O. and Chaumette, F. (2005). Point-based and regionbased image moments for visual servoing of planar objects. IEEE Trans. on Robotics, 21(6):1116-1127.
  29. Tarbouriech, S., Soueres, P., and Gao, B. (2005). A multicriteria image-based controller based on a mixed polytopic and norm-bounded representation of uncertainties. In 44th IEEE Conf. on Decision and Control and European Control Conf., pages 5385-5390, Seville, Spain.
  30. Thuilot, B., Martinet, P., Cordesses, L., and Gallice, J. (2002). Position based visual servoing: keeping the object in the field of vision. In Proc. IEEE Int. Conf. on Robotics and Automation, pages 1624-1629, Washington, D.C.
  31. Yao, Z. and Gupta, K. (2007). Path planning with general end-effector constraints. Robotics and Autonomous Systems, 55(4):316-327.
Download


Paper Citation


in Harvard Style

Chesi G. (2009). LMI-BASED TRAJECTORY PLANNING FOR CLOSED-LOOP CONTROL OF ROBOTIC SYSTEMS WITH VISUAL FEEDBACK . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-674-000-9, pages 13-20. DOI: 10.5220/0002172200130020


in Bibtex Style

@conference{icinco09,
author={Graziano Chesi},
title={LMI-BASED TRAJECTORY PLANNING FOR CLOSED-LOOP CONTROL OF ROBOTIC SYSTEMS WITH VISUAL FEEDBACK},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2009},
pages={13-20},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002172200130020},
isbn={978-989-674-000-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - LMI-BASED TRAJECTORY PLANNING FOR CLOSED-LOOP CONTROL OF ROBOTIC SYSTEMS WITH VISUAL FEEDBACK
SN - 978-989-674-000-9
AU - Chesi G.
PY - 2009
SP - 13
EP - 20
DO - 10.5220/0002172200130020