Orthogonalization Principle for Dynamic Visual Servoing of Constrained Robot Manipulators

  • Vicente Parra-Vega
  • Emmanuel Dean-Leon

Abstract

A monocular visual servoing scheme for constrained robots is considered in this chapter. Inspired by the Orthogonalization Principle (OP) introduced by Suguru Arimoto in the context of robot force control, a Visual Orthogonalization Principle (VOP) is proposed and a novel control scheme for adaptive image-based visual servoing is presented. The scheme guarantees a global exponential convergence for the image-based position-velocity and contact forces even when the robot parameters are considered unknown. The stability of the new control scheme is tested under experiments. The experimental results comply to the theoretical considerations.

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References

  1. 1.
    Whitney D (1997) Force feedback control of manipulator fine motions. ASME Journal of Dynamic Systems, Measurement and Control 99:91–97Google Scholar
  2. 2.
    Whitney D (1985) Historical perspective and state of the art in robot force control. In: Proc. IEEE Int. Conf. on Robotics and Automation 262–268Google Scholar
  3. 3.
    De Schutter J, Bruyninckx H, Zhu WH, Spong M (1997) Force control: A bird's eye view. In: Proc. IEEE CSS/RAS Int. Workshop on Control Problems in Robotics and Automation: Future DirectionsGoogle Scholar
  4. 4.
    Arimoto S (1996) Control Theory of Non-linear Mechanical Systems: A Passivity-based and Circuit-theoretic Approach. Oxford Engineering Science Series, Oxford University PressGoogle Scholar
  5. 5.
    McClamroch H, Wang D (1988) Feedback stabilizationand tracking of constrained robots. IEEE Transactions on Automatic Control 33(5):419–426MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Arimoto S, Liu YH, Parra-Vega V (1992) Design of model-based adaptive controllers for robot manipulators under geometric constraints. In: Proc. The Japan-USA Symposium on Flexible Automation, USA 615–621Google Scholar
  7. 7.
    Liu YH, Arimoto S, Parra-Vega V, Kitagaki K (1997) Decentralized adaptive control of multiple manipulators in co-operation. International Journal of Control 67(5):649–673MATHCrossRefMathSciNetGoogle Scholar
  8. 8.
    Parra-Vega V, Rodriguez-Angeles A, Arimoto S, Hirzinger G (2001) High precision constrained grasping with cooperative adaptive handcontrol. Journal of Intelligent and Robotic Systems 32(3):235–254MATHCrossRefGoogle Scholar
  9. 9.
    Hutchinson S, Hager G, Corke P (1996) A tutorial on visual servo control. IEEE Transactions on Robotics and Automation 12(5):651–670CrossRefGoogle Scholar
  10. 10.
    Weiss L, Sanderson A, Neuman C (1987) Dynamic sensor based control of robots with visual feedback. IEEE Journal of Robotics and Automation 3(5):404–417CrossRefGoogle Scholar
  11. 11.
    Papanikolopoulus N, Khosla P, Kanade T (1993) Visual tracking of a moving target by a camera mounted on a robot: A combination of control and vision. IEEE Journal of Robotics and Automation 9:14–35CrossRefGoogle Scholar
  12. 12.
    Castano A, Hutchinson S (1994) Visual compliance: Task directed visual servo control. IEEE Transactions on Robotics and Automation 10(3):334–342CrossRefGoogle Scholar
  13. 13.
    Bishop B, Spong M (1997) Adaptive calibration and control of 2D monocular visual servo system. In: Proc. IFAC Symposium on Robot Control, Nantes, France 525–530.Google Scholar
  14. 14.
    Miyazaki F, Masutani Y (1990), Robustness on sensory feedback control based on imperfect jacobian, In: Robotics Research: The Fifth Int Symp, Miura H, Arimoto S (eds.), MIT, Cambridge, MA, 201–208.Google Scholar
  15. 15.
    Kelly R, Marquez A (1995) Fixed-eye direct visual feedback control of planar robots. Journal of System Engineering 4(5):239–248Google Scholar
  16. 16.
    Kelly R (1996) Robust asymptotically stable visual servoing of planar robots. IEEE Transactions on Robotics and Automation 12(5):759–766CrossRefGoogle Scholar
  17. 17.
    Zergeroglu E, Dawson D, de Queiroz M, Setlur P (2003) Robust visual-servo control of robot manipulators in the presence of uncertainty. Journal of Robotic Systems 20(2):93–106MATHCrossRefGoogle Scholar
  18. 18.
    Dean-León E, Parra-Vega V, Espinosa-Romero A, Fierro J (2004) Dynamical image-based PID uncalibrated visual servoing with .xed camera for tracking of planar robots with a heuristical predictor. In: Proc. 2nd IEEE Int. Conf. on Industrial Informatics 339–345Google Scholar
  19. 19.
    Shen Y, Sun D, Liu YH, Li KJ (2003) Asymptotic trajectory tracking of manipulators using uncalibrated visual feedback. IEEE/ASME Transactions on Mechatronics 8(1):87–9CrossRefGoogle Scholar
  20. 20.
    Xiao D (2000) Sensor-hybrid position/force control of a robot manipulator in an uncalibrated enviroment. IEEE Transactions on Control System Technology 8(4):635–645MATHCrossRefGoogle Scholar
  21. 21.
    Nelson B, Khosla P (1996) Force and vision resolvability for assimilating disparate sensory feedback. IEEE Transactions on Robotics and Automation 12(5):714–731CrossRefGoogle Scholar
  22. 22.
    Baeten J, De Schutter J (2001) Combined vision/force control at corners in planar robotic contour following. In: Proc. IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics 810–815Google Scholar
  23. 23.
    Hosoda K, Igarashi K, Asada M (1998) Adaptive hybrid control for visual and force servoing in an unknown environment. IEEE Robotics and Automation Magazine 5:39–43CrossRefGoogle Scholar
  24. 24.
    Parra-Vega V, Arimoto S, Liu YH, Naniwa T (1994) Model-based adaptive hybrid control of robot manipulators under holonomic constraints. In: Proc. IFAC Symposium on Robot Control 475–480Google Scholar
  25. 25.
    Blajer W, Schiehleny W, Schirm W (1994) A projection criterion to the coordinate partitioning method for multi body dynamics. Archive of Applied Mechanics 84:86–98Google Scholar
  26. 26.
    García L, Dean-León E, Parra-Vega V, Espinosa-Romero A, Fierro J (2005) Experimental results of image-based adaptive visual servoing of 2D robots under jacobian and dynamic friction uncertainties. In: Proc. Int. Symposium on Computational Intelligence in Robotics and AutomationGoogle Scholar
  27. 27.
    Parra-Vega V, Arimoto S, Liu YH, Hirzinger G, Akella P (2003) Dynamic sliding PID control for tracking of robot manipulators: theory and experiments. IEEE Transactions on Robotics and Automation 19:967–976CrossRefGoogle Scholar

Copyright information

© Springer 2006

Authors and Affiliations

  • Vicente Parra-Vega
    • 1
  • Emmanuel Dean-Leon
    • 1
  1. 1.Mechatronics Division - Research Center for Advanced Studies (CINVESTAV)Mexico CityMexico

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