Skip to main content
Log in

Autonomous feature following for visual surveillance using a small unmanned aerial vehicle with gimbaled camera system

  • Special Section on Advances in Intelligent Visual Surveillance Systems
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

This paper represents the development of feature following control and distributed navigation algorithms for visual surveillance using a small unmanned aerial vehicle equipped with a low-cost imaging sensor unit. An efficient map-based feature generation and following control algorithm is developed to make an onboard imaging sensor to track a target. An efficient navigation system is also designed for real-time position and velocity estimates of the unmanned aircraft, which is used as inputs for the path following controller. The performance of the proposed autonomous path following capability with a stabilized gimbaled camera onboard a small unmanned aerial robot is demonstrated through flight tests with application to target tracking for real-time visual surveillance.

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. D. A. Schoenwald, “AUVs: in space, air, water, and on the ground,” IEEE Control Systems Magazine, vol. 20, no. 6, pp. 15–18, 2000.

    Article  Google Scholar 

  2. I. Kaminer, O. Yakimenko, V. Dobrokhodov, A. Pascoal, N. Hovakimyan, A. Young, C. Cao, and V. Patel, “Coordinated path following for time-critical missions of multiple UAVs via L1 adaptive output feedback controllers,” AIAA Guidance, Navigation, and Control Conference and Exhibit, Hilton Head, SC, 2007.

  3. M. E. Campbell, J.-W. Lee, and E. Scholte, “Simulation and flight test of autonomous aircraft estimation, planning, and control algorithms,” Journal of Guidance, Control, and Dynamics, vol. 30, no. 6, pp. 1597–1609, 2007.

    Article  Google Scholar 

  4. K. Jones, V. Dobrokhodov, I. Kaminer, D.-J. Lee, E. Bourakov, and M. Clement, “Development, system integration and flight testing of a high-resolution imaging system for small unmanned aerial systems,” Proc. of the 47th AIAA Aerospace Sciences Meeting, Orlando, Florida, Jan. 5–8 2009.

  5. R. Rysdyk, “Unmanned aerial vehicle path following for target observation in wind,” AIAA Journal of Guidance, Control, and Dynamics, vol. 29, no. 5, pp. 1092–1100, 2007.

    Article  Google Scholar 

  6. E. Frew, T. Mc-Gee, Z. Kim, X. Xiao, S. Jackson, M. Morimoto, S. Rathinam, J. Padial, and R. Senguta, “Vision-based road following using a small autonomous aircraft,” Proc. of the IEEE Aerospace Conference, pp. 3006–3015, 2004.

  7. J. Egbert and R. W. Beard, “Low altitude road fol lowing control constraints using strap-down EO cameras on miniature air vehicles,” Proc. of the IEEE American Control Conference, pp. 353–358, 2007.

  8. M. S. Grewal, A. P. Andrews, and L. R. Weill, Global Positioning Systems, Inertial Navigation, John Wiley & Sons, Inc., New York, 2007.

    Book  Google Scholar 

  9. O, Yakimenko, “Direct method for rapid prototyping of near-optimal aircraft trajectories,” AIAA Journal of Guidance, Control, and Dynamics, vol. 23, no. 5, pp. 865–875, 2000.

    Article  Google Scholar 

  10. R. G. Brown and P. Y. C. Hwang, Introduction to Random Signals and Applied Kalman Filtering, 3rd ed., John Wiley & Sons, Inc., New York, NY, 1997.

    MATH  Google Scholar 

  11. D. B. Kingston and R. W. Beard, “Real-time attitude and position estimation for small UAVs using low-cost sensors,” Proc. of AIAA Unlimited Systems Conference and Workshop, Chicago, IL, Paper. No. AIAA-2004-6533, 2004.

  12. R. van der Merwe, E. A. Wan, and S. J. Julier, “Sigma-point Kalman filters for nonlinear estimation and sensor fusion: applications to integrated navigation,” AIAA Guidance, Navigation, and Control Conference and Exhibit, Providence, Rhode Island, 2004.

  13. D. H. Titterton and J. L. Weston, “Strapdown inertial navigation technology,” IEE Radar, Sonar, Navigation and Avionics Series 5, London, UK, 1997.

  14. Piccolo Documentation, http://www.cloudcaptech.com.

  15. Microspace PC-104, http://www.adlogic-pc104.com.

  16. Wave Relay QUAD Radio Router, http://www.persistentsystems.com/products/.

  17. PelcoNet Video Server, http://www.pelco.com/producets.

  18. Sony FCB-IX11A Color Bock-Camera, http://www.aegis-elec.com/producets.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Deok-Jin Lee.

Additional information

Recommended by Guest Editor Seong G. Kong. This work was supported by SOCOM under NPS-SOCOM TNT cooperative. The research of the first author is supported by the National Research Council Associateship tenured at the Center for Autonomous Vehicle Research at the Naval Postgraduate School.

Deok-Jin Lee received his Ph.D. degree in Aerospace Engineering from Texas A&M University in May 2005. He worked for Agency for Defense Development (ADD) from 2006 to 2007. He is currently an adjunct research professor at the Center for Autonomous Vehicle Research, Naval Postgraduate School, Monterey, CA, U.S.A. His research interests include autonomous robotic vehicle control, sensor fusion and sensor networks, decentralized cooperative control, and integrated navigation and localization.

Isaac Kaminer received his Ph.D. degree in Aerospace Engineering Sciences from University of Michigan, Ann Arbor, 1992. He is currently co-director at the Center for Autonomous Vehicle Research, Naval Postgraduate School, Monterey, CA, U.S.A. His research interests include unmanned aerial vehicles, adaptive control, and real-time flight control systems.

Vladimir Dobrokhodov received his Ph.D. degree in Aerospace Engineering Sciences from Zhukovskiy Air Force Engineering Academy, Moscow, 1999. He is currently a research assistant professor at the Center for Autonomous Vehicle Research, Naval Postgraduate School, Monterey, CA, U.S.A. His research interests include guidance, navigation and control of unmanned aerial vehicles, applied nonlinear control, and real-time embedded flight control systems.

Kevin Jones received his Ph.D. degree in Aerospace Engineering Sciences from University of Colorado in May 1993. He is currently a research associate professor at the Center for Autonomous Vehicle Research, Naval Postgraduate School, Monterey, CA, U.S.A. His research interests include micro unmanned aerial vehicles, multidisciplinary design and optimization, fluid mechanics, and aircraft design.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, DJ., Kaminer, I., Dobrokhodov, V. et al. Autonomous feature following for visual surveillance using a small unmanned aerial vehicle with gimbaled camera system. Int. J. Control Autom. Syst. 8, 957–966 (2010). https://doi.org/10.1007/s12555-010-0504-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-010-0504-1

Keywords

Navigation