Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-19T17:28:19.529Z Has data issue: false hasContentIssue false
  • English
  • Français

Implementation of vision-based automatic guidance system on a fixed-wing unmanned aerial vehicle

Published online by Cambridge University Press:  27 January 2016

C-S Lee  and
F-B Hsiao
C-S Lee
Affiliation:
Institute of Aeronautics and Astronautics, National Cheng Kung University, Tainan City, Taiwan
F-B Hsiao*
Affiliation:
Institute of Aeronautics and Astronautics, National Cheng Kung University, Tainan City, Taiwan
*
fbhsiao@mail.ncku.edu.tw
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents the design and implementation of a vision-based automatic guidance system on a fixed-wing unmanned aerial vehicle (UAV). The system utilises a low-cost ordinary video camera and simple but efficient image processing techniques widely used in computer-vision technology. The paper focuses on the identification and extraction of geographical tracks such as rivers, coastlines, and roads from real-time aerial images. The image processing algorithm primarily uses colour properties to isolate the geographical track of interest from its background. Hough transform is eventually used to curve-fit the profile of the track which yields a reference line on the image plane. A guidance algorithm is then derived based on this information. In order to test the vision-based automatic guidance system in the laboratory without actually flying the UAV, a hardware-in-the-loop simulation system is developed. Description regarding the system and significant simulation result are presented in the paper. Finally, an actual test flight where the UAV successfully follows a stretch of a river under automatic vision-based guidance is also presented and discussed.

Type
Research Article
Information
The Aeronautical Journal , Volume 116 , Issue 1183 , September 2012 , pp. 895 - 914
Copyright
Copyright © Royal Aeronautical Society 2012 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Ettinger, S.M., Nechyba, M.C., Ifju, P.G. and Waszak, M. Vision-guided flight stability and control for micro air vehicles, 2002, IEEE International Conference on Intelligent Robots and Systems, IEEE, 3, pp 2134–2140.Google Scholar
2. Schulz, H.W. Towards vision-based autonomous landing for small unmanned aerial vehicles:image processing hardware development, J Aerospace Computing, Information and Communication, 2008, 5, (10), pp 380–395.Google Scholar
3. Morgan, Q., Griffiths, S. and Beard, R.W. Target acquisition, localization and surveillance using a fixed-wing mini-UAV and gimbaled camera, 2005, IEEE International Conference on Robotics and Automation, Barcelona, Spain.Google Scholar
4. Stepanyan, V. and Hovakimyan, N. Visual tracking of a maneuvering target, J Guidance, Control, and Dynamics, 2008, 31, (1), pp 66–80.Google Scholar
5. Oh, S–M. and Johnson, E.N. Relative motion estimation for vision-based formation flight using unscented Kalman filter, 2007, AIAA Guidance, Navigation and Control Conference and Exhibition, Hilton Head, SC, USA.Google Scholar
6. Kimmett, J., Valasek, J. and Junkins, J.L. Autonomous aerial refueling utilizing a vision based navigation system, 2002, AIAA Guidance, Navigation, and Control Conference and Exhibition, Monterey, CA, USA.Google Scholar
7. Johnson, E.N., Calise, A.J., Watanabe, Y., Ha, J. and Neidhoefer, J.C. Real-time vision-based relative aircraft navigation, J Aerospace Computing, Information and Communication, 2007, 4, (4), pp 707–738.Google Scholar
8. Frew, E., McGee, T., Kim, Z., Xiao, X., Jackson, S., Morimoto, S., Rathinam, S., Padial, J. and Sengupta, R., Vision-based road following using a small autonomous aircraft, 2004, IEEE Aerospace Conference, Big Sky, MT, USA.Google Scholar
9. Rathinam, S., Almeida, P., Kim, Z., Jackson, S., Tinka, A., Grossman, W. and Sengupta, R. Autonomous searching and tracking of a river using an UAV, 2007, 2007 American Control Conference, Marriot Marquis Hotel, New York, USA.Google Scholar
10. Baker, P. and Kamgar-Parsi, B. Using shorelines for autonomous air vehicle guidance, Computer Vision and Image Understanding, 2010, 114, pp 723–729.Google Scholar
11. Zhang, J., Wu, Y., Liu, W. and Chen, X. Novel approach to position and orientation estimation in vision-based UAV navigation, IEEE Transactions on Aerospace and Electronic Systems, April 2010, 46, (2), pp 687–700.Google Scholar
12. Lee, C.S., Chan, W.L. and Hsiao, F.B. A linear-quadratic-Gaussian approach for automatic flight control of fixed-wing unmanned air vehicles, Aeronaut J, January 2011, 115, (1163), pp 29–41.Google Scholar
13. Gonzalez, R.C. and Woods, R.E. Digital Image Processing, 2002, Prentice-Hall International.Google Scholar
14. HaralickR.,M. R.,M. and Shapiro, L.G. Computer Vision and Robot Vision, 1, 1992, Addison-Wesley Publishing Company, USA.Google Scholar
15. Umbaugh, S.E. Computer Vision and Image Processing: A Practical Approach Using CVIPtools, 1998, Prentice Hall PTR, Upper Saddle River, NJ. USA.Google Scholar
16. Lee, C.S., Hsiao, F.B. and Jan, S.S. Design and implementation of linear-quadratic-Gaussian stability augmentation autopilot for unmanned air vehicle, Aeronaut J, May 2009, 113, (1143), pp 275–290.Google Scholar