Skip to main content
Log in

Cartesian space control of a quadrotor system based on low cost localization under a vision system

  • Regular Papers
  • Control Theory and Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

This article presents the Cartesian position control of a quadrotor system in the indoor environment. Prior to applying the position control to a quadrotor system, the quadrotor is localized to measure the status of the quadrotor system under the vision system. Due to the expensive cost of motion-capturing sensors, a single camera is used to detect the heading angle and the position by using the color of markers on the top of the quadrotor system. Since a single camera cannot detect the distance from the object, compensation methods for the position and height are presented. Localization for the height can be done by using local information on the basis of the regular rectangular shape of the tiles on the floor. Control performances of the hovering, heading angle and trajectory are evaluated by empirical studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. K. Yang, Y. Kang, and S. Sukkarieh, “Adaptive nonolinear model predictive path-following control for a fixed-wing unmanned aerial vehicle,” International Journal of Control. Automation and Systems, vol. 11, no. 1, pp. 65–74, 2013. [click]

    Article  Google Scholar 

  2. B. Zhu and W. Huo, “Trajectory linearization control for a miniature unmanned helicopter,” International Journal of Control. Automation and Systems (IJCAS), vol. 11, no. 2, pp. 286–295, 2013. [click]

    Article  Google Scholar 

  3. A. Tayebi and S. McGilvray, “Attitude stabilization of a VTOL quadrotor aircraft,” IEEE Trans. on Control Systems Technology, vol. 14, no. 3, pp. 562–571, 2006. [click]

    Article  Google Scholar 

  4. A. Das, K. Subbarao, and F. Lewis, “Dynamic inversion with zero-dynamics stabilization for quadrotor control,” IET Control Theory and Applications, vol. 3, no. 3, pp. 303–314, 2009. [click]

    Article  MathSciNet  Google Scholar 

  5. Z. Zuo, “Trajectory tracking control design with commandfiltered compensation for a quadrotor,” IET Control Theory and Applications, vol. 4, no. 11, pp. 2343–2355, 2010. [click]

    Article  MathSciNet  Google Scholar 

  6. F. Hoffmann, N. Goddemeier, and T. Bertram, “Attitude estimation and control of a quadrocopter,” Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1072–1077, 2010. [click]

    Google Scholar 

  7. R. Zhang, Q. Quan, and K. Y. Cai, “Attitude control of a quadrotor aircraft subject to a class of time-varying distur-bances,” IET Control Theory and Applications, vol. 4, no. 9, pp. 1140–1146, 2010. [click]

    MathSciNet  Google Scholar 

  8. D. Lee, H. J. Kim, and S. Sastry, “Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter,” International Journal of Control, Automation and Systems, vol. 7, no. 3, pp. 419–428, 2009. [click]

    Article  Google Scholar 

  9. D. B. Lee, C. Nataraj, T. C. Burg, and D. M. Dawson, “Adaptive tracking control of an underactuated aerial vehicle,” Proc. of American Control Conference, pp. 2326–2331, 2011. [click]

    Google Scholar 

  10. K. Alexis, G. Nikolakopouplos, and A. Tzes, “Design and experimental verification of a constrained finite time optimal control scheme for the attitude control of a quadrotor helicopter subject to wind gusts,” Proc. of IEEE Conf. on Robotics and Automations, pp. 1636–1642, 2010. [click]

    Google Scholar 

  11. T. Dierks and S. Jagannathan, “Output feedback control of a quadrotor UAV using neural networks,” IEEE Trans on Neural Networks, vol. 21, no. 1, pp. 50–66, 2010. [click]

    Article  Google Scholar 

  12. M. Efe, “Neural network assisted computationally simple PID control of a quadrotor UAV,” IEEE Trans. on Industrial Informatics, vol. 7, no. 2, pp. 354–361, 2011. [click]

    Article  Google Scholar 

  13. S. Park, D. H. Won, M. S. Kang, T. J. Kim, H. G. Lee, and S. J. Kwon, “RIC(Robust internal-loop compensator) based flight control of quadrotor type UAV,” Proc. of IEEE International Conference on Intelligent Robots and Systems(IROS), pp. 3542–3547, 2005. [click]

    Google Scholar 

  14. H. Huang, G. M. Hoffmann, S. L. Waslander, and C. J. Tomlin, “Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering,” Proc. of IEEE Conf. on Robotics and Automations, pp. 3277–3282, 2009. [click]

    Google Scholar 

  15. S. Grzonka, G. Grisetti, and W. Burgard, “A fully autonomous indoor quadrotor,” IEEE Trans. on Robotics, vol. 28, no. 1, pp. 90–100, 2012. [click]

    Article  Google Scholar 

  16. K. J. Yoon and N. S. Goo, “Development of a small autonomous flying robot with four rotor system,” Proc. of International Conference on Advanced Robotics, pp. 150–154, 2011. [click]

    Google Scholar 

  17. M. Hehn and R. D’Andrea, “A flying inverted pendulum,” Proc. of IEEE Conference on Robotics and Automation(ICRA), pp. 763–770, 2011. [click]

    Google Scholar 

  18. S. H. Jeong, S. Jung, and M. Tomizuka, “Attitude control of a quadrotor system using an acceleration-based disturbance observer: an empirical approach”, Proc. of IEEE AIM, pp. 916–921, 2012. [click]

    Google Scholar 

  19. UPENN, http://www.upenn.edu/spotlights/penn-quadrotors-ted

  20. ETH, Zurich, http://www.youtube.com/watch

  21. S. Jung, “An impedance force control approach to a quadrotor system based on an acceleration-based disturbance observer,” Journal of Intelligent & Robotic Systems, vol. 73, no. 1, pp. 175–185, 2014. [click]

    Article  Google Scholar 

  22. S. H. Jeong and S. Jung, “A vision-based localization of a quadrotor system,” Proc. of URAI, pp. 636–638, 2012. [click]

    Google Scholar 

  23. S. H. Jeong and S. Jung, “Experimental studies of interaction control between a quadrotor system and a human operator,” Proc. of IEEE ROMAN, pp. 372–373, 2013. [click]

    Google Scholar 

  24. H. J. Lee and S. Jung, “Balancing and navigation control of a mobile inverted pendulum robot using sensor fusion of low cost sensors,” Mechatronics, vol. 22, no. 1, pp. 95–105, 2012. [click]

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Seul Jung.

Additional information

Recommended by Associate Editor Wen-Hua Chen under the direction of Editor Hyouk Ryeol Choi. This work was supported in part by the 2012 National Research Foundation of Korea and 2014 the basic research funds through the contract of National Research Foundation of Korea (NRF-2014R1A2A1A11049503).

Seung Ho Jeong received the B.S. degree in 2010 and M.S. degree in 2012 from Department of Mechatronics Engineering, Chungnam National University. He is currently working at LIG Nex1, Korea. His research interests include unmanned aerial vehicles and sensor implementation.

Seul Jung received the B.S. degree in Electrical and Computer Engineering from Wayne State University, Detroit, MI, USA in 1988, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of California, Davis, in 1991 and 1996, respectively. In 1997, he joined the Department of Mechatronics Engineering, Chungnam National University, where he is presently a professor. His research interests include intelligent Mechatronics systems, intelligent robotic systems, mobile manipulators for home service applications, and robot education. He is a member of IEEE, ACA, ICROS, KROS, KIIS, KIEE, IEMEK, and IEEK.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jeong, S.H., Jung, S. Cartesian space control of a quadrotor system based on low cost localization under a vision system. Int. J. Control Autom. Syst. 14, 549–559 (2016). https://doi.org/10.1007/s12555-013-0504-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-013-0504-z

Keywords

Navigation