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Selection of Observation Position and Orientation in Visual Servoing with Eye-in-vehicle Configuration for Manipulator

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Abstract

In this paper, we propose a method to select the observation position in visual servoing with an eye-in-vehicle configuration for the manipulator. In traditional visual servoing, the images taken by the camera may have various problems, including being out of view, large perspective aberrance, improper projection area of object in images and so on. In this paper, we propose a method to determine the observation position to solve these problems. A mobile robot system with pan-tilt camera is designed, which calculates the observation position based on an observation and then moves there. Both simulation and experimental results are provided to validate the effectiveness of the proposed method.

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References

  1. X. L. Li, L. C. Wu, T. Y. Lan. A 3D-printed robot hand with three linkage-driven underactuated fingers. International Journal of Automation and Computing, vol. 15, no. 5, pp. 593–602, 2018. DOI: https://doi.org/10.1007/s11633-018-1125-z.

    Article  Google Scholar 

  2. A. Saxena, H. Pandya, G. Kumar, A. Gaud, K. M. Krishna. Exploring convolutional networks for end-to-end visual servoing. In Proceedings of IEEE International Conference on Robotics and Automation, Singapore, pp. 3817–3823, 2007.

    Google Scholar 

  3. S. Kundu, D. R. Parhi. Reactive navigation of underwater mobile robot using ANFIS approach in a manifold manner. International Journal of Automation and Computing, vol. 14, no. 3, pp. 307–320, 2017. DOI: https://doi.org/10.1007/s11633-016-0983-5.

    Article  Google Scholar 

  4. D. Xu, M. Tan, X. G. Zhao, Z. G. Tu. Seam tracking and visual control for robotic arc welding based on structured light stereovision. International Journal of Automation and Computing, vol. 1, no. 1, pp. 63–75, 2004. DOI: https://doi.org/10.1007/s11633-004-0063-0.

    Article  Google Scholar 

  5. H. B. Wang, M. Liu. Design of robotic visual servo control based on neural network and genetic algorithm. International Journal of Automation and Computing, vol. 9, no. 1, pp. 24–29, 2012. DOI: https://doi.org/10.1007/s11633-012-0612-x.

    Article  MathSciNet  Google Scholar 

  6. F. Li, H. L. Xie. Sliding mode variable structure control for visual servoing system. International Journal of Automation and Computing, vol. 7, no. 3, pp. 317–323, 2010. DOI: https://doi.org/10.1007/s11633-010-0509-5.

    Article  Google Scholar 

  7. F. Nagata, K. Watanabe. Adaptive learning with large variability of teaching signals for neural networks and its application to motion control of an industrial robot. International Journal of Automation and Computing, vol. 8, no. 1, pp. 54–61, 2011. DOI: https://doi.org/10.1007/s11633-010-0554-0.

    Article  Google Scholar 

  8. F. Nagata, K. Watanabe, M. K. Habib. Machining robot with vibrational motion and 3D printer-like data interface. International Journal of Automation and Computing, vol. 15, no. 1, pp. 1–12, 2018. DOI: https://doi.org/10.1007/s11633-017-1101-z.

    Article  Google Scholar 

  9. H. S. Wang, Y. H. Liu, D. X. Zhou. Adaptive visual servoing using point and line features with an uncalibrated eye-in-hand camera. IEEE Transactions on Robotics, vol. 24, no. 4, pp. 843–857, 2008. DOI: https://doi.org/10.1109/TRO.2008.2001356.

    Article  Google Scholar 

  10. P. J. S. Gonçalves, L. F. Mendonça, J. M. C. Sousa, and J. R. C. Pinto. Uncalibrated eye-to-hand visual servoing using inverse fuzzy models. IEEE Transactions on Fuzzy Systems, vol. 16, no. 2, pp. 341–353, 2008. DOI: https://doi.org/10.1109/TFUZZ.2007.896226.

    Article  Google Scholar 

  11. B. Thuilot, P. Martinet, L. Cordesses, J. Gallice. Position based visual servoing: Keeping the object in the field of vision. In Proceedings of IEEE International Conference on Robotics and Automation, Washington, USA, vol. 2, pp. 1624–1629, 2002.

    Google Scholar 

  12. G. Chesi, K. Hashimoto, D. Prattichizzo, A. Vicino. Keeping features in the field of view in eye-in-hand visual servoing: A switching approach. IEEE Transactions on Robotics, vol. 20, no. 5, pp. 908–914, 2004. DOI: https://doi.org/10.1109/TRO.2004.829456.

    Article  Google Scholar 

  13. Y. Mezouar, F. Chaumette. Path planning for robust image-based control. IEEE Transactions on Robotics and Automation, vol. 18, no. 4, pp. 534–549, 2002. DOI: https://doi.org/10.1109/TRA.2002.802218.

    Article  Google Scholar 

  14. G. Chesi, Y. S. Hung. Global path-planning for constrained and optimal visual servoing. IEEE Transactions on Robotics, vol. 23, no. 5, pp. 1050–1060, 2007. DOI: https://doi.org/10.1109/TRO.2007.903817.

    Article  Google Scholar 

  15. Z. Zhu, W. Zou, Q. B. Wang, F. Zhang. A velocity compensation visual servo method for oculomotor control of bionic eyes. International Journal of Robotics & Automation, vol. 33, no. 1, pp. 33–44, 2018. DOI: https://doi.org/10.2316/Journal.206.2018.1.206-4938.

    Article  Google Scholar 

  16. Q. B. Wang, W. Zou, D. Xu, Z. Zhu. Motion control in saccade and smooth pursuit for bionic eye based on three-dimensional coordinates. Journal of Bionic Engineering, vol. 14, no. 2, pp. 336–347, 2017. DOI: https://doi.org/10.1016/S1672-6529(16)60402-X.

    Article  Google Scholar 

  17. N. V. Tinh, P. T. Cat, P. M. Tuan, T. T. Q. Bui. Visual control of integrated mobile robot-pan tilt-camera system for tracking a moving target. In Proceedings of IEEE International Conference on Robotics and Biomimetics, Bali, Indonesia, pp. 1566–1571, 2014.

    Google Scholar 

  18. V. C. Le, T. C. Pham. Optimal tracking a moving target for integrated mobile robot-pan tilt-stereo camera. In Proceedings of IEEE International Conference on Advanced Intelligent Mechatronics, Banff, Canada, pp. 530–535, 2016.

    Google Scholar 

  19. Y. C. Fang, X. Liu, X. B. Zhang. Adaptive active visual servoing of nonholonomic mobile robots. IEEE Transactions on Industrial Electronics, vol. 59, no. 1, pp. 486–497, 2012. DOI: https://doi.org/10.1109/TIE.2011.2143380.

    Article  Google Scholar 

  20. R. Sharma, S. Hutchinson. Optimizing hand/eye configuration for visual-servo systems. In Proceedings of IEEE International Conference on Robotics and Automation, IEEE, Nagoya, Japan, pp. 172–177, 1995.

    Google Scholar 

  21. K. Tarabanis, R. Y. Tsai, P. K. Allen. Automated sensor planning for robotic vision tasks. In Proceedings of IEEE International Conference on Robotics and Automation, Sacramento, USA, vol. 1, pp. 76–82, 1991.

    Google Scholar 

  22. J. Y. Zheng, Q. Chen, S. Tsuji. Active camera guided manipulation. In Proceedings of IEEE International Conference on Robotics and Automation, Sacramento, USA, vol. 1, pp. 632–638, 1991.

    Google Scholar 

  23. D. Xu, M. Tan, Z. M. Jiang, H. S. Hu. Use of colour and shape constraints in vision-based valve operation by robot. International Journal of Advanced Robotic Systems, vol. 3, no. 3, pp. 267–274, 2006. DOI: https://doi.org/10.5772/5728.

    Article  Google Scholar 

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Acknowledgements

This work was supported by Natural Science Foundation of China (No. 61773374) and Key Research and Development Program of China (No. 2017YFB1300104).

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Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Science, Beijing, 100080, China

    Hong-Xuan Ma, Wei Zou, Zheng Zhu, Chi Zhang & Zhao-Bing Kang

Authors
  1. Hong-Xuan Ma
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  2. Wei Zou
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  3. Zheng Zhu
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  4. Chi Zhang
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  5. Zhao-Bing Kang
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Corresponding author

Correspondence to Wei Zou.

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Recommended by Associate Editor Nazim Mir-Nasiri

Hong-Xuan Ma received the B. Sc. degree in intelligent science and technology from Central South University, China in 2016. He is currently a Ph. D. degree candidate in control science and engineering at Institute of Automation, Chinese Academy of Sciences, China. He is also with University of Chinese Academy of Sciences, China.

His research interests include visual servoing, robot localization, computer vision and navigation.

Wei Zou received the B. Eng. degree in control science and engineering from Baotou University of Iron and Steel Technology, China in 1997, the M. Eng. degree in control science and engineering from Shandong University of Technology, China in 2000, and the Ph. D. degree in control science and engineering from Institute of Automation, Chinese Academy of Sciences (IACAS), China in 2003. Currently, he is a professor at the Research Center of Precision Sensing and Control, IACAS.

His research interests include intelligent robotics, visual servoing, robot localization and navigation.

Zheng Zhu received the B. Sc. degree in automation from Zhenzhou University, China in 2014. He is currently a Ph. D. degree candidate in control science and engineering at Institute of Automation, Chinese Academy of Sciences, China. He is also with University of Chinese Academy of Sciences, China.

His research interests include computer vision, deep learning and robotics.

Chi Zhang received the B. Sc. degree in automation from Shenyang University of Chemical Technology, China in 2015, and the M. Sc. degree in control engineering from Harbin University of Science and Technology, China and Institute of Automation, Chinese Academy of Sciences, China in 2018. He is currently a Ph. D. degree candidate in control science and engineering at Institute of Automation, Chinese Academy of Sciences, China.

His research interests include intelligent control and reinforcement learning.

Zhao-Bing Kang received the B. Eng. degree in mechanical engineering and automation from Dezhou University, China in 2008, the M. Eng. degree in mechanical and electronic engineering from Harbin Institute of Technology, China in 2011. Currently, he is a Ph. D. degree candidate in control science and engineering at Institute of Automation, Chinese Academy of Science, China.

His research interests include visual servoing and robot location and navigation.

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Ma, HX., Zou, W., Zhu, Z. et al. Selection of Observation Position and Orientation in Visual Servoing with Eye-in-vehicle Configuration for Manipulator. Int. J. Autom. Comput. 16, 761–774 (2019). https://doi.org/10.1007/s11633-019-1181-z

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