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Image-based robotic control with unknown camera parameters and joint velocities

Published online by Cambridge University Press:  29 April 2014

Changchun Hua ,
Yinjuan Liu  and
Yana Yang
Changchun Hua*
Affiliation:
Department of Automation, Institute of Electrical Engineering, Yanshan University, Qinhuangdao City 066004, China
Yinjuan Liu
Affiliation:
Department of Automation, Institute of Electrical Engineering, Yanshan University, Qinhuangdao City 066004, China
Yana Yang
Affiliation:
Department of Automation, Institute of Electrical Engineering, Yanshan University, Qinhuangdao City 066004, China
*
*Corresponding author. E-mail: [email protected]
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Summary

A new image-based controller is proposed for the robotic system with the joint velocity signals unavailable. The Immersion and Invariance (I&I) observer is applied to estimate the unknown velocity information. Compared with the general velocity observer, the I&I observer can estimate the unknown velocity exponentially. We consider the case that the exact camera parameters are not known. The corresponding adaptive controller is designed for the robot system and the stability is rigorously proven by using Lyapunov theorem. Finally, simulations are performed and the results show the effectiveness of the proposed control approach.

Keywords

Image-basedRobot controlI&I velocity observerUnknown camera parameters
Type
Articles
Information
Robotica , Volume 33 , Issue 8 , October 2015 , pp. 1718 - 1730
Copyright
Copyright © Cambridge University Press 2014 

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References

1. Hutchinson, S., Hager, G. and Cork, P., “A tutorial on visual servo control,” IEEE Trans. Robot. Autom. 12 (5), 651–670 (1996).Google Scholar
2. Malis, E., Chaumette, F. and Boudet, S., “Positioning a Coarse-Calibrated Camera with Respect to an Unknown Object by 2D 1/2 Visual Servoing,” Proceedings of the IEEE International Conference on Robotica and Automation, Leuven, Belgium (1998) pp. 1352–1359.Google Scholar
3. Chaumette, F., “Potential Problems of Stability and Convergence in Image-Based and Position-Based Visual Servoing,” Proceedings of the Confluence of Vision and Control, Lecture Notes in Control and Information Sciences Volume 237, vol. 237 (1998) pp. 66–78.Google Scholar
4. Corke, P. I. and Hutchinson, S. A., “A new partitioned approach to image-based visual servo control,” IEEE Trans. Robot. Autom. 179 (4), 507–515 (2001).Google Scholar
5. Kelly, R., Carelli, R., Nasisi, O., Kuchen, B. and Reyes, F.. “Stable visual servoing of camera-in-hand robotic systems,” IEEE Trans. Mechatronics 5 (1), 39–48 (2000).Google Scholar
6. Hashimoto, K., Kimoto, T., Ebine, T. and Kimura, H., “Manipulator Control with Image-Based Visual Servoing,” Proceedings of the IEEE International Conference on Robotics and Automation, Sacramento, CA (1991) pp. 2267–2272.Google Scholar
7. Astolfi, A., Hsu, L., Netto, M. and Ortega, R., “Two solutions to the adaptive visual servoing problem,” IEEE Trans. Robot. Autom. 18 (3), 387–392 (2002).Google Scholar
8. Liang, X., Huang, X., Wang, M. and Zeng, X., “Improved stability results for visual tracking of robotic manipulators based on the depth-independent interaction matrix,” IEEE Trans. Robot. 27 (2), 371–379 (2011).Google Scholar
9. Astolfi, A. and Ortega, R., “Immersion and invariance: A new tool for stabilization and adaptive control of nonlinear systems,” IEEE Trans. Autom. Control 48 (4), 590–606 (2003).Google Scholar
10. Maruthi, R. A., “Vision-based adaptive tracking control of uncertain robot manipulators,” IEEE Trans. Robot. 21 (4), 748–753 (2005).Google Scholar
11. Liu, Y. H., Wang, H., Wang, C. and Lam, K. K., “Uncelebrated visual servoing of robots using a depth-independent interaction matrix,” IEEE Trans. Robot. 22 (4), 804–817 (2006).Google Scholar
12. Liu, Y. and Wang, H., “Uncelebrated visual tracking control without visual velocity,” IEEE Trans. Control Syst. Technol. 18 (6), 1359–1370 (2010).Google Scholar
13. Wang, H. S., Jiang, M. K., Chen, W. D. and Liu, Y. H., “Visual servoing of robots with uncalibrated robot and camera parameters,” Mechatronics 22 (6), 661–668 (2012).Google Scholar
14. Su, Y. and Zheng, C., “Vision-Based PID Regulation of Robotic Manipulators Without Velocity Measurements,” Proceedings of the IEEE International Conference on Robotics and Automatics, Tianjin, China (2010) pp. 1698–1703.Google Scholar
15. Liang, X., Huang, X. and Wang, M., “Approximate Jacobian Control of Robot Manipulators Without Joint Velocity Measurements,” Proceedings of the IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, Kunming, China (2011) pp. 7–12.Google Scholar
16. Lizarralde, F., Leite, A. C., Hsu, L. and Costa, R. R., “Adaptive visual servoing scheme free of image velocity measurement for uncertain robot manipulators,” Automatica 49 (5), 1304–1309 (2013).Google Scholar
17. Dani, A. P., Fischer, N. R., Kan, Z. and Dixon, W. E., “Globally exponentially stable observer for vision-based range estimation,” Mechatronics 22 (4), 381–389 (2012).Google Scholar
18. Hua, C., Liu, Y. and Leng, J., “Visual-Based Robotic Control Without Joint Velocities,” Proceedings of the 12th International Conference on Control, Automation, Robotics & Vision (2012) pp. 1262–1267.Google Scholar
19. Astolfi, A., Ortega, R. and Venkatraman, A.. “A Globally Exponentially Convergent Immersion and Invariance Speed Observer for N Degrees of Freedom Mechanical Systems,” Proceedings of the IEEE Conference on Decision and Control (2009) pp. 6508–6513.Google Scholar