Uncalibrated Trinocular-Microscope Visual Servo Control Strategy

  • Xuewei Wang
  • Qun Gao
  • Fucheng You
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10636)


Considering that both calibtating accurate the camera parameters and establishing a precise robot kinematics model are hardly, the uncalibrated trinocular-microscope visual servoing control strategy used for achieving precise positioning of the cylindrical target is proposed in this paper. Firstly, using Canny-algorithm, polar coordinate scanning and Ransac Least-Square fitting to extract the features of the target image and Moving-edge algorithm is used to realize real-time tracking of the target. Secendly, dynamic Quasi-Newton algorithm is adopted to estimate the image Jacobian matrix of the trinocular-microscope visual system. Thirdly, use the variance minimization strategy of the target pose error function to control the end movement of positioning robot, and use the strategy of iterative least-squares to improve the stability of the whole system. Furthermore, obtain the initial value of image Jacobian matrix according to the target moving which is in form of discrete linear independence movement near the desired pose. Finally, the dynamic residuals are adjusted in order to achieve precise positioning of the target under the condition that the basic platform of the positioning robot is in disturbance. Experimental results demonstrate the effectiveness of the proposed strategy.


Quasi-Newton algorithm Image jacobian Dynamic residuals Visual servoing control 



This work was supported by a grant from the Joint Funding Project of Beijing Municipal Commission of Education and Beijing Natural Science Fund Committee (201710015010).


  1. 1.
    Chaumette, F., Hutchinson, S.: Visual servo control i: basic approaches. J. IEEE Robot. Autom. Mag. 13(4), 82–90 (2016)CrossRefGoogle Scholar
  2. 2.
    Chaumette, F., Hutchinson, S.: Visual servo control ii: advanced approaches. J. IEEE Robot. Autom. Mag. 14(1), 109–118 (2017)CrossRefGoogle Scholar
  3. 3.
    Wang, L., Mills, J.K.: Automatic microassembly using visual servo control. J IEEE Trans. Electron. Packag. Manuf. 31(4), 316–325 (2008)CrossRefGoogle Scholar
  4. 4.
    Zhang, Y.N., Chen, X.: Visual measurement of micro-target pose in ICF experiment. J. Opto-Electron. Eng. 39(5), 18–24 (2012)Google Scholar
  5. 5.
    Tamadazte, B., Thomas, A.: Automatic micromanipulation using multiscale visual servoing. In: Proceedings of IEEE Conference of Advanced Intelligent Mechatronics, pp. 88–93 (2009)Google Scholar
  6. 6.
    Wang, H., Jiang, M., et al.: Visual servoing of robots with uncalibrated robot and camera parameters. J. Mechatron. 22(6), 661–668 (2012)CrossRefGoogle Scholar
  7. 7.
    Kosmopoulos, D.I.: Robust Jacobian matrix estimation for image-based visual servoing. J. Robot. Comput. Integr. Manuf. 27(1), 82–87 (2011)CrossRefGoogle Scholar
  8. 8.
    Liu, M.: Research of uncalibrated visaual servoing robot. D. Master dissertion of Yanshan University, pp. 30–39 (2011)Google Scholar
  9. 9.
    Kim, G.W., Lee, B.H.: Uncalibrated visual vervoing technique using large residual. In: International Conference on Robotics and Automation, pp. 3315–3320 (2003)Google Scholar
  10. 10.
    Piepmeier, J.A., McMurray, G.V.: Uncalibrated dynamic visual servoing. J. IEEE Trans. Robot. Autom. 20, 143–147 (2004)CrossRefGoogle Scholar
  11. 11.
    Zhao, J., Li, M., Li, G.: Study on uncalibrated visual servoing technique. J. Control Decis. 21(9), 1015–1020 (2006)MATHGoogle Scholar
  12. 12.
    Li, M.: Research on robot uncalibrated visual servoing key technique. D. Ph.D. dissertion of Harbin Institute of Technology, p. 59-9 (2008)Google Scholar
  13. 13.
    Malis, E.: Visual servoing invarant to changes in camera-intrinsic parameters. J. IEEE Trans. Robot. Autom. 20(1), 72–81 (2004)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Information EngineeringBeijing Institute of Graphic CommunicationBeijingChina
  2. 2.Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of SciencesChangchunChina

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