Advertisement

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

  • Deok-Jin Lee
  • Isaac Kaminer
  • Vladimir Dobrokhodov
  • Kevin Jones
Special Section on Advances in Intelligent Visual Surveillance Systems

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.

Keywords

Autonomous navigation imaging sensors path following control real-time visual surveillance stabilized gimbaled camera unmanned aerial robots 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [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.CrossRefGoogle Scholar
  2. [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.Google Scholar
  3. [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.CrossRefGoogle Scholar
  4. [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.Google Scholar
  5. [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.CrossRefGoogle Scholar
  6. [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.Google Scholar
  7. [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.Google Scholar
  8. [8]
    M. S. Grewal, A. P. Andrews, and L. R. Weill, Global Positioning Systems, Inertial Navigation, John Wiley & Sons, Inc., New York, 2007.CrossRefGoogle Scholar
  9. [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.CrossRefGoogle Scholar
  10. [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.zbMATHGoogle Scholar
  11. [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.Google Scholar
  12. [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.Google Scholar
  13. [13]
    D. H. Titterton and J. L. Weston, “Strapdown inertial navigation technology,” IEE Radar, Sonar, Navigation and Avionics Series 5, London, UK, 1997.Google Scholar
  14. [14]
    Piccolo Documentation, http://www.cloudcaptech.com.
  15. [15]
    Microspace PC-104, http://www.adlogic-pc104.com.
  16. [16]
    Wave Relay QUAD Radio Router, http://www.persistentsystems.com/products/.
  17. [17]
    PelcoNet Video Server, http://www.pelco.com/producets.
  18. [18]
    Sony FCB-IX11A Color Bock-Camera, http://www.aegis-elec.com/producets.

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Deok-Jin Lee
    • 1
  • Isaac Kaminer
    • 2
  • Vladimir Dobrokhodov
    • 2
  • Kevin Jones
    • 2
  1. 1.Center for Autonomous Vehicle Research (CAVR)Naval Postgraduate SchoolMontereyUSA
  2. 2.Department of Mechanical and Astronautical EngineeringNaval Postgraduate SchoolMontereyUSA

Personalised recommendations