Using Tablets in the Vision-based Control of a Ball and Beam Test-bed
Jared A. Frank, José Antonio De Gracia Gómez, Vikram Kapila
2015
Abstract
Although the onboard cameras of smart devices have been used in the monitoring and teleoperation of physical systems such as robots, their use in the vision-based feedback control of such systems remains to be fully explored. In this paper, we discuss an approach to control a ball and beam test-bed using visual feedback from a smart device with its camera pointed at the test-bed. The computation of a homography between the frames of a live video and a reference image allows the smart device to accurately estimate the state of the test-bed while facing the test-bed from any perspective. Augmented reality is incorporated in the development of an interactive user interface on the smart device that allows users to command the position of the ball on the beam by tapping their fingers at the desired location on the touchscreen. Experiments using a tablet are performed to characterize the noise of vision-based measurements and to illustrate the performance of the closed-loop control system.
References
- Baggio, D. (2012). Mastering OpenCV with Practical Computer Vision Projects. Packt Publishing Ltd.
- Berenguel, M., et al. (2004). An artificial vision-based control system for automatic heliostat positioning offset correction in a central receiver solar power plant. Solar Energy, 76(5):563-575.
- Bolívar, C. and Beauchamp, G. (2014). Modelling the ball-and-beam system from newtonian mechanics and from lagrange methods. In Proc. Latin American and Carribbean Conference on Engineering and Technology, page 176.
- Burschka, D. and Hager, G. (2001). Vision-based control of mobile robots. In IEEE Int. Conf. Robotics and Automation, volume 2, pages 1707-1713.
- Dadios, E.P., et al. (2000). Vision guided ball-beam balancing system using fuzzy logic. In IEEE Conf. Industrial Electronics Society, volume 3, pages 1973-1978.
- Das, A.K., et al. (2002). A vision-based formation control framework. IEEE Trans. Robotics and Automation, 18(5):813-825.
- Desai, A., et al. (2013). Stabilization and control of quad-rotor helicopter using a smartphone device. IS&T/SPIE Electronic Imaging, 8662(8):1-9.
- El-Gaaly, T., et al. (2013). Visual obstacle avoidance for autonomous watercraft using smartphones. In Autonomous Robots and Multirobot Systems Workshop.
- Greenwood, D. (1988). Principles of Dynamics. PrenticeHall Englewood Cliffs, NJ.
- Grieder, R., et al. (2014). Multi-robot control and interaction with a hand-held tablet. In Proc. IEEE Int. Conf. Robotics and Automation, volume 131.
- Hartley, R. and Zisserman, A. (2003). Multiple View Geometry in Computer Vision. Cambridge University Press.
- Hasanzade, I., Anvar, S., and Motlagh, N. (2008). Design and implementation of visual servoing control for ball and beam system. In Int. Symp. Mechatronics and Its Applications, pages 1-5.
- Hirschorn, R. (2002). Incremental sliding mode control of the ball and beam. IEEE Trans. Automatic Control, 47(10):1696-1700.
- Hu, J., et al. (2012). Fish species classification by color, texture and multi-class support vector machine using computer vision. Computers and Electronics in Agriculture, 88:133-140.
- Huang, H., et al. (2007). Visual-based impedance force control of three-dimensional cell injection system. In IEEE Int. Conf. Robotics and Automation, pages 4196-4201.
- Hutchinson, S., Hager, G., and Corke, P. (1996). A tutorial on visual servo control. IEEE Trans. Robotics and Automation, 12(5):651-670.
- Kastrinaki, V., Zervakis, M., and Kalaitzakis, K. (2003). A survey of video processing techniques for traffic applications. Image and Vision Computing, 21(4):359-381.
- Laukonen, E. and Yurkovich, S. (1993). A ball and beam testbed for fuzzy identification and control design. In American Control Conference, pages 665-669. IEEE.
- Lewis, F. (1986). Optimal Estimation: With an Introduction to Stochastic Control Theory. Wiley New York et al.
- Li, G., et al. (2012). Testing mobile phone camera based fingerprint recognition under real-life scenarios. Norsk informasjonssikkerhetskonferanse, 2012.
- Masselli, A., Hanten, R., and Zell, A. (2013). Robust realtime detection of multiple balls on a mobile robot. In European Conf. Mobile Robots, pages 355-360.
- Nguyen, L., et al. (2009). Vision-based system for the control and measurement of wastewater flow rate in sewer systems. Water Science and Technology, 60(ECOLARTICLE-2009-029):2281-2289.
- Pang, Z.-H., Zheng, G., and Luo, C.-X. (2011). Augmented state estimation and LQR control for a ball and beam system. In Int. Conf. Industrial Electronics and Applications, pages 1328-1332.
- Petrovic, I., Brezak, M., and Cupec, R. (2002). Machine vision based control of the ball and beam. In Int. Workshop Advanced Motion Control, pages 573-577.
- Sanderson, A. and Weiss, L. (1980). Image-based visual servo control using relational graph error signals. Proc. IEEE, 1074.
- Shirai, Y. and Inoue, H. (1973). Guiding a robot by visual feedback in assembling tasks. Pattern Recognition, 5(2):99-108.
- Soille, P. (2003). Morphological Image Analysis: Principles and Applications. Springer-Verlag New York, Inc.
- Tapu, R., et al. (2013). A smartphone-based obstacle detection and classification system for assisting visually impaired people. In Int. Conf. Computer Vision Workshops, pages 444-451.
- Vincze, M. and Hager, G. (1999). Robust Vision for VisionBased Control of Motion. Wiley-IEEE Press.
- Wang, L.-X. (1998). Stable and optimal fuzzy control of linear systems. IEEE Trans. Fuzzy Systems, 6(1):137- 143.
- Wei, W. and Xue, P. (2010). A research on control methods of ball and beam system based on adaptive neural network. In Int. Conf. Computational and Information Sciences, pages 1072-1075.
- You, C.-W., et al. (2013). Carsafe app: Alerting drowsy and distracted drivers using dual cameras on smartphones. In Proc. Int. Conf. Mobile Systems, Applications, and Services, pages 13-26.
- Zhou, K., et al. (1996). Robust and Optimal Control. Prentice Hall New Jersey.
Paper Citation
in Harvard Style
A. Frank J., Antonio De Gracia Gómez J. and Kapila V. (2015). Using Tablets in the Vision-based Control of a Ball and Beam Test-bed . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-123-6, pages 92-102. DOI: 10.5220/0005544600920102
in Bibtex Style
@conference{icinco15,
author={Jared A. Frank and José Antonio De Gracia Gómez and Vikram Kapila},
title={Using Tablets in the Vision-based Control of a Ball and Beam Test-bed},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2015},
pages={92-102},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005544600920102},
isbn={978-989-758-123-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Using Tablets in the Vision-based Control of a Ball and Beam Test-bed
SN - 978-989-758-123-6
AU - A. Frank J.
AU - Antonio De Gracia Gómez J.
AU - Kapila V.
PY - 2015
SP - 92
EP - 102
DO - 10.5220/0005544600920102