Skip to main content
SpringerLink
Log in

Development of a vision-based ground target detection and tracking system for a small unmanned helicopter

  • Published:
Science in China Series F: Information Sciences Aims and scope Submit manuscript

Abstract

It is undoubted that the latest trend in the unmanned aerial vehicles (UAVs) community is towards visionbased unmanned small-scale helicopter, utilizing the maneuvering capabilities of the helicopter and the rich information of visual sensors, in order to arrive at a versatile platform for a variety of applications such as navigation, surveillance, tracking, etc. In this paper, we present the development of a visionbased ground target detection and tracking system for a small UAV helicopter. More specifically, we propose a real-time vision algorithm, based on moment invariants and two-stage pattern recognition, to achieve automatic ground target detection. In the proposed algorithm, the key geometry features of the target are extracted to detect and identify the target. Simultaneously, a Kalman filter is used to estimate and predict the position of the target, referred to as dynamic features, based on its motion model. These dynamic features are then combined with geometry features to identify the target in the second-stage of pattern recognition, when geometry features of the target change significantly due to noise and disturbance in the environment. Once the target is identified, an automatic control scheme is utilized to control the pan/tilt visual mechanism mounted on the helicopter such that the identified target is to be tracked at the center of the captured images. Experimental results based on images captured by the small-scale unmanned helicopter, SheLion, in actual flight tests demonstrate the effectiveness and robustness of the overall system.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Sarris Z, Atlas S. Survey of UAV applicatins in civil markets. In: Proceedings of the 9th Mediterranean Conference on Control and Automation, Dubrovnik, Croatia, 2001. 1–11

  2. Herwitz S R, Dunagan S, Sullivan D, et al. Solar-powered UAV mission for agricultural decision support. In: Proceedings of Geoscience and Remote Sensing Symposium, Toulouse, France, 2003. 1692–1694

  3. Ludington B, Johnson E, Vachtsevanos G. Augmenting UAV autonomy. IEEE Rob Autom Mag, 2006, 13(3): 63–71

    Article  Google Scholar 

  4. Campbell M E, Whitacre W W. Cooperative tracking using vision measurements on seascan UAVs. IEEE Trans Control Syst Technol, 2007, 15(4): 613–626

    Article  Google Scholar 

  5. Santana P, Barata J. Unmanned helicopters applied to humanitarian demining. In: Proceedings of 10th IEEE Conference on Emerging Technologies and Factory Automation, Catania, Italy, 2005. 729–738

  6. Cai G W, Chen B M, Peng K M, et al. Modeling and control system design for a UAV helicopter. In: Proceedings of the 14th Mediterranean Conference on Control and Automation, Ancona, Italy, 2006. 1–6

  7. Gavrilets V, Shterenberg A, Dahleh M A, et al. Avionics system for a small unmanned helicopter performing aggressive maneuvers. In: Proceedings of the 19th Digital Avionics Systems Conferences, Philadelphia, USA, 2000. 1–7

  8. Roberts J M, Corke P, Buskey G. Low-cost flight control system for a small autonomous helicopter. In: Proceedings of the 2002 Australian Conference on Robotics and Automation, Auckland, New Zealand, 2002. 546–551

  9. Sprague K, Gavrilets V, Dugail D, et al. Design and applications of an avionic system for a miniature acrobatic helicopter. In: Proceedings of the 20th Digital Avionics Systems Conferences, Daytona Beach, USA, 2001. 1–10

  10. Guenard N, Hamel T, Mahony R A. Practical visual servo control for an unmanned aerial vehicle. IEEE Trans Rob, 2008, 24(2): 331–340

    Article  Google Scholar 

  11. Amidi O, Kanade T, Miller R. Vision-based autonomous helicopter research at carnegie mellon robotics institute 1991–1997. In: Proceedings of American Helicopter Society International Conference, Gifu, Japan, 1998. 1–12

  12. Mejias L, Saripalli S, Cervera P, et al. Visual servoing of an autonomous helicopter in urban areas using feature tracking. J Field Rob, 2006, 23(3): 185–199

    Article  Google Scholar 

  13. Meingast M, Geyer C, Sastry S. Vision based terrain recovery for landing unmanned aerial vehicles. In: Proceedings of IEEE Conference on Decision and Control, Atlantis, Bahamas, 2004. 1670–1675

  14. Hrabar S, Sukhatme G S, Corke P, et al. Combined optic-flow and stereobased navigation of urban canyons for a UAV. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. 3309–3316

  15. Kim J, Sukkarieh S. Slam aided gps/ins navigation in gps denied and unknown environments. In: The 2004 International Symposium on GNSS/GPS, Sydney, Australia, 2004. 1–14

  16. Hu W M, Tan T N, Wang L, et al. A survey on visual surveillance of object motion and behaviors. IEEE Trans Syst Man Cybern, 2004, 34(3): 334–352

    Article  Google Scholar 

  17. Sadjadi F. Theory of invariant algebra and its use in automatic target recognition. Phys Autom Target Recognit, 2007, 3: 23–40

    Google Scholar 

  18. Sattigeri R, Johnson E, Calise A, et al. Vision-based target tracking with adaptive target state estimator. In: Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Hilton Head, USA, 2007. 1–13

  19. Johnson E N, Calise A J, Watanabe Y, et al. Real-time visionbased relative aircraft navigation. J Aerosp Comput Inf Commun, 2007, 4(4): 707–738

    Article  Google Scholar 

  20. Betser A, Vela P, Tannenbaum A. Automatic tracking of flying vehicles using geodesic snakes and kalman filtering. In: Proceedings of 43rd IEEE Conference on Decision and Control, Atlantis, Bahama, 2004. 1649–1654

  21. Zhou Q M, Aggarwalb J K. Object tracking in an outdoor environment using fusion of features and cameras. Image Vision Comput, 2006, 24(11): 1244–1255

    Article  Google Scholar 

  22. Veeraraghavan H, Schrater P, Papanikolopoulos N. Robust target detection and tracking through integration of motion, color and geometry. Comput Vis Image Und, 2006, 103(2): 121–138

    Article  Google Scholar 

  23. Hu M K. Visual pattern recognition by moment invariants. IEEE Trans Inf Theory, 1962, 8(2): 179–187

    Article  Google Scholar 

  24. Chen C C, Tsai T I. Improved moment invariants for shape discrimination. Pattern Recogn, 1993, 26(5): 683–686

    Article  MathSciNet  Google Scholar 

  25. Cai G W, Peng K M, Chen B M, et al. Design and assembling of a UAV helicopter system. In: Proceedings of International Conference on Control and Automation, Budapest, Hungary, 2005. 697–702

  26. Li X R, Jilkov V P. Survey of maneuvering target tracking, Part I: Dynamic models. IEEE Trans Aerosp Electron Syst, 2003, 39(4): 1333–1364

    Article  Google Scholar 

  27. Chaumette F, Hutchinson S. Visual servo control part I: Basic approaches. IEEE Rob Autom Mag, 2006, 13(4): 82–90

    Article  Google Scholar 

  28. Chaumette F, Hutchinson S. Visual servo control part II: Advanced approaches. IEEE Rob Autom Mag, 2007, 14(1): 109–118

    Article  Google Scholar 

  29. Franklin G, Powell J D, Emami-Naeini A E. Feedback Control of Dynamic Systems. 4th ed. New Jersey: Prentice-Hall, 2002

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical & Computer Engineering, National University of Singapore, 117576, Singapore, Singapore

    Feng Lin, Kai-Yew Lum, Ben M. Chen & Tong H. Lee

Authors
  1. Feng Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kai-Yew Lum
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ben M. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tong H. Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ben M. Chen.

Additional information

Supported by Temasek Defence Systems Institute of Singapove (Grant No. TDSI/07-003/1A)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lin, F., Lum, KY., Chen, B.M. et al. Development of a vision-based ground target detection and tracking system for a small unmanned helicopter. Sci. China Ser. F-Inf. Sci. 52, 2201–2215 (2009). https://doi.org/10.1007/s11432-009-0187-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-009-0187-5

Keywords

Search

Navigation