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An Enhanced IBVS Controller of a 6DOF Manipulator Using Hybrid PD-SMC Method

Abstract

The accuracy and stability are two fundamental concerns of the visual servoing control system. This paper presents an enhanced image based visual servoing (IBVS) method for increasing the accuracy of a 6DOF manipulator. The controller is designed to combine proportional derivative (PD) control with sliding mode control (SMC) on a 6DOF manipulator. The properly tuned PD controller can ensure the fast tracking performance and SMC can deal with the external disturbance and uncertainties due to the depth. The enhanced IBVS controller benefits from simple structure and easy implementation of PD control and good robustness to uncertainties of SMC. The stability of the proposed method is proven by using Lyapunov method. Simulation and experimental results are used to demonstrate the effectiveness of the proposed controller.

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References

  1. A. Ghanbari, W. Wang, C. E. Hann, J. G. Chase, and X. Chen, “Cell image recognition and visual servo control for automated cell injection,” Proc. of 4th International Conference on Autonomous Robots and Agents, pp. 92–96, Feb. 2009. [click]

    Google Scholar 

  2. Y. Zhao, W.-F. Xie, and S. Liu, “Image-based visual servoing using improved image moments in 6-dof robot systems,” International Journal of Control, Automation, and Systems, vol. 11, no. 3, pp. 586–596, Feb. 2013.

    Article  Google Scholar 

  3. T. Banlue, P. Sooraksa, and S. Noppanakeepong, “A practical position-based visual servo design and implementation for automated fault insertion test,” International Journal of Control, Automation, and Systems, vol. 12, no. 5, pp. 1090–1101, May 2014. [click]

    Article  Google Scholar 

  4. K. Hashimoto, “A review on vision-based control of robot manipulators,” Advanced Robotics, vol. 17, no. 10, pp. 969–991, 2003. [click]

    Article  Google Scholar 

  5. H. Liu, Y. Yu, F. Sun, and J. Gu, “Visual tactile fusion for object recognition,” IEEE Transactions on Automation Science and Engineering, vol. 14, no. 2, pp. 996–1008, Apr. 2017. [click]

    Article  Google Scholar 

  6. H. Liu, D. Guo, and F. Sun, “Object recognition using tactile measurements: Kernel sparse coding methods,” IEEE Transactions on Instrumentation and Measurement, vol. 65, no. 3, pp. 656–665, Mar. 2016. [click]

    Article  Google Scholar 

  7. P. Corke, Robotics, Vision and Control, Springer, 2011. [click]

    Book  MATH  Google Scholar 

  8. F. Chaumette and S. Hutchinson, “Visual servo control. i. basic approaches,” IEEE Robotics Automation Magazine, vol. 13, no. 4, pp. 82–90, Dec. 2006.

    Article  Google Scholar 

  9. S. Hutchinson, G. D. Hager, and P. I. Corke, “A tutorial on visual servo control,” IEEE Transactions on Robotics and Automation, vol. 12, no. 5, pp. 651–670, Oct. 1996. [click]

    Article  Google Scholar 

  10. F. Chaumette and S. Hutchinson, “Visual servo control. ii. advanced approaches,” IEEE Robotics Automation Magazine, vol. 14, no. 1, pp. 109–118, Mar. 2007. [click]

    Article  Google Scholar 

  11. J. k. Kim, D. w. Kim, S. j. Choi, and S. c. Won, “Imagebased visual servoing using sliding mode control,” Proc. of SICE-ICASE International Joint Conference, pp. 4996–5001, Oct. 2006.

    Google Scholar 

  12. J. Wang and H. Cho, “Micropeg and hole alignment using image moments based visual servoing method,” IEEE Transactions on Industrial Electronics, vol. 55, no. 3, pp. 1286–1294, Mar. 2008. [click]

    Article  Google Scholar 

  13. M. Keshmiri, W. F. Xie, and A. Mohebbi, “Augmented image-based visual servoing of a manipulator using acceleration command,” IEEE Transactions on Industrial Electronics, vol. 61, no. 10, pp. 5444–5452, Oct. 2014. [click]

    Article  Google Scholar 

  14. G. Allibert, E. Courtial, and F. Chaumette, “Predictive control for constrained image-based visual servoing,” IEEE Transactions on Robotics, vol. 26, no. 5, pp. 933–939, Oct. 2010. [click]

    Article  Google Scholar 

  15. Y. Fang, X. Liu, and X. Zhang, “Adaptive active visual servoing of nonholonomic mobile robots,” IEEE Transactions on Industrial Electronics, vol. 59, no. 1, pp. 486–493, Jan. 2012.

    Article  Google Scholar 

  16. W. Wroblewski, “Implementation of a model predictive control algorithm for a 6dof manipulator - simulation results,” Proceedings of the Fourth International Workshop on Robot Motion and Control, pp. 209–212, Jun. 2004. [click]

    Google Scholar 

  17. N. S. C. Cai and A. Knoll, “Orthogonal image features for visual servoing of a 6-dof manipulator with uncalibrated stereo cameras,” IEEE Transactions on Robotics, vol. 32, no. 2, pp. 452–461, Oct. 2016. [click]

    Article  Google Scholar 

  18. E. C. G. Allibert and F. Chaumette, “Predictive control for constrained image-based visual servoing,” IEEE Transactions on Robotics, vol. 26, no. 5, pp. 933–939, Oct. 2010. [click]

    Article  Google Scholar 

  19. J. J. E. Slotine and W. Li, Applied Nonlinear Control, Prentice Hall, 1991.

    Google Scholar 

  20. M. Asad, A. I. Bhatti, S. Iqbal, and Y. Asfia, “A smooth integral sliding mode controller and disturbance estimator design,” International Journal of Control, Automation, and Systems, vol. 13, no. 6, pp. 1326–1336, Jan. 2015.

    Article  Google Scholar 

  21. Q. H. Ngo, N. P. Nguyen, C. N. Nguyen, T. H. Tran, and K.-S. Hong, “Fuzzy sliding mode control of container cranes,” International Journal of Control, Automation, and Systems, vol. 13, no. 2, pp. 419–425, Aug. 2015. [click]

    Article  Google Scholar 

  22. T. Yüksel, “Ibvs with fuzzy sliding mode for robot manipulators,” Proc. of International Workshop on Recent Advances in Sliding Modes (RASM), pp. 1–6, Apr. 2015. [click]

    Google Scholar 

  23. M. Parsapour, S. RayatDoost, and H. D. Taghirad, “Position based sliding mode control for visual servoing system,” Proc. of First RSI/ISM International Conference on Robotics and Mechatronics (ICRoM), pp. 337–342, Feb. 2013.

    Google Scholar 

  24. F. Li and H. Xie, “Sliding mode variable structure control for visual servoing system,” International Journal of Automation and Computing, vol. 7, no. 3, pp. 317–323, Aug. 2010. [click]

    Article  Google Scholar 

  25. J. M. Acob, V. Pano, and P. R. Ouyang, “Hybrid pd sliding mode control of a two degree-of-freedom parallel robotic manipulator,” Proc. of 10th IEEE International Conference on Control and Automation (ICCA), pp. 1760–1765, Jun. 2013. [click]

    Google Scholar 

  26. J.-L. Chang, “Sliding mode control design for mismatched uncertain systems using output feedback,” International Journal of Control, Automation, and Systems, vol. 14, no. 2, pp. 579–586, Apr. 2016. [click]

    Article  Google Scholar 

  27. T. Fujio, H. Shibasaki, R. Tanaka, T. Murakami, and Y. Ishida, “Sliding mode control based on a modified linear control input,” International Journal of Control, Automation, and Systems, vol. 14, no. 1, pp. 115–127, Mar. 2016.

    Article  Google Scholar 

  28. D. Lee, T. Ryan, and H. J. Kim, “Autonomous landing of a vtol uav on a moving platform using image-based visual servoing,” Proc. of IEEE International Conference on Robotics and Automation (ICRA), pp. 971–976, May. 2012. [click]

    Google Scholar 

  29. J. Craig, Introduction to Robotics: Mechanics and Control, 2nd ed., Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1989.

    MATH  Google Scholar 

  30. P. I. Corke and B. Armstrong-Hlouvry, “A meta-study of puma 560 dynamics: A critical appraisal of literature data,” Robotica, vol. 13, no. 03, pp. 253–258, 1995. [click]

    Article  Google Scholar 

  31. Quanser 6-Axis Articulated Robot, Quanser/Denso Specialty Plants, Markham, ON,Canada, 2011.

  32. M.W. Spong and S. Hutchinson, Robot Modeling and Control, Wiley, Hoboken, NJ, USA, 2006.

    Google Scholar 

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Correspondence to Wenfang Xie.

Additional information

Recommended by Associate Editor Huaping Liu under the direction of Editor Duk-Sun Shim. This work was supported by the China Scholarship Council(CSC).

Shutong Li received her B.S. and M.S. degrees in mechanics and mechatronic engineering from the Harbin University of Science and Technology, Harbin, China, in 2010 and 2014. She is currently working toward a Ph.D. degree at Harbin Engineering University, Harbin, China. From 2015 to 2016, she was a visiting research student in Intelligent Control System Laboratory in the Department of Mechanical and Industrial Engineering at Concordia University, Montreal, QC, Canada. Her research interests include visual servoing design of mechatronic systems, intelligent robot control systems.

Ahmad Ghasemi received his B.S. and M.S. degrees in mechanical engineering from Isfahan University of Technology (IUT), Isfahan, Iran, in 2005 and 2008, respectively. He was a member of the Dynamic and Robotic Research Group, IUT, and was involved in some projects of the group. He is currently doing research on vision-based control of robots as Ph.D. student at Concordia University, Montreal, QC, Canada. His research interests include robotics and control, machine vision, machine learning and nonlinear systems.

Wenfang Xie received her Ph.D. from The Hong Kong Polytechnic University in 1999 and her Master’s degree from Beihang University in 1991. She is a professor with the Department of Mechanical and Industrial Engineering at Concordia University, Montreal, Canada. She joined Concordia University as an assistant professor in 2003 and was promoted to associate professor, professor, in 2008 and 2014 respectively. Her research interests include nonlinear control and identification in mechatronics, visual servoing, model predictive control, neural network, and advanced process control and system identification.

Yanbin Gao received his B.S. degree and M.S. degree from Harbin Engineering University (HEU), in 1985 and 1987 respectively. Now he is a professor and Ph.D. tutor in College of Automation, HEU. He is a leader in Institute of Inertial Navigation andM&CTechnology in HEU. His research interests include micro-signal processing and noise suppression, navigation in formation conversion, PINS and SINS techniques, and the applications of novel inertial devices and high-precision navigation systems.

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Li, S., Ghasemi, A., Xie, W. et al. An Enhanced IBVS Controller of a 6DOF Manipulator Using Hybrid PD-SMC Method. Int. J. Control Autom. Syst. 16, 844–855 (2018). https://doi.org/10.1007/s12555-016-0720-4

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  • DOI: https://doi.org/10.1007/s12555-016-0720-4

Keywords

  • Image based visual servoing (IBVS)
  • PD control
  • sliding mode control
  • 6DOF manipulator