Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-02T19:08:23.758Z Has data issue: false hasContentIssue false
  • English
  • Français

Waypoint navigation for a micro air vehicle using vision-based attitude estimation

Published online by Cambridge University Press:  03 February 2016

J. J. Kehoe ,
R. S. Causey ,
M. Abdulrahim  and
R. Lind
J. J. Kehoe
Affiliation:
Department of Mechanical and Aerospace Engineering, University of Florida, Florida, USA
R. S. Causey
Affiliation:
Department of Mechanical and Aerospace Engineering, University of Florida, Florida, USA
M. Abdulrahim
Affiliation:
Department of Mechanical and Aerospace Engineering, University of Florida, Florida, USA
R. Lind
Affiliation:
Department of Mechanical and Aerospace Engineering, University of Florida, Florida, USA
Get access Rights & Permissions [Opens in a new window]

Abstract

Missions envisioned for micro air vehicles may require a high degree of autonomy to operate in unknown environments. As such, vision is a critical technology for mission capability. This paper discusses an autopilot that uses vision coupled with GPS and altitude sensors for waypoint navigation. The vision processing analyses a horizon to estimate roll and pitch information. The GPS and altitude sensors then command values to roll and pitch for navigation between waypoints. A flight test of a MAV using this autopilot demonstrates the resulting closed-loop system is able to autonomously reach several waypoints. The vehicle actually uses a telemetry link to a ground station on which all vision processing and related guidance and control is performed. Several issues, such as estimating heading to account for slow updates, are investigated to increase performance.

Type
Research Article
Information
The Aeronautical Journal , Volume 110 , Issue 1114 , December 2006 , pp. 821 - 829
Copyright
Copyright © Royal Aeronautical Society 2006 

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. Castro, A.P.A., Silva, J.D. and Simoni, P.O., Image-based autonomous navigation with fuzzy logic control, 2001, International Joint Conference on Neural Networks, 15-19 July 2001, Volume 3, pp 2200–2205.Google Scholar
2. Choi, J.Y., Kim, C.S., Hong, S., Lee, M.H., Bae, J.I. and Harashima, F., Vision-based lateral control by yaw rate feedback, 2001, 27th Annual Conference of the IEEE Industrial Electronics Society, 29 November-3 December 2001, Volume 3, pp 2135–2138.Google Scholar
3. Juberts, M. and Raviv, D., Vision-based vehicle control of AVCS, 1993, Intelligent Vehicles Symposium, 14-16 July 1993, pp 195–200.Google Scholar
4. Kosecka, J., Blasi, R., Taylor, C.J. and Malik, J., A comparative study of vision-based control strategies for autonomous highway driving, 1998, IEEE International Conference on Robotics & Automation, May 1998, pp 1903–1908.Google Scholar
5. Manigel, J. and Leonhard, W., Vehicle control by computer vision 1992, IEEE Transactions on Industrial Electronics, June 1992, 39, (3), pp 181–188.Google Scholar
6. Thomas, B.T., Lotufo, R.A., Morgan, A.D., Milford, D.J. and Dagless, E.L., Real-time image analysis for vision-guided vehicle control, 1990, UK IT Conference, 19-22 March 1990, pp 66–70.Google Scholar
7. Campos, M.F.M. and Coelho, L., De, S., Autonomous dirigible navigation using visual tracking and pose estimation, 1999, IEEE International Conference on Robotics and Automation, May 1999.Google Scholar
8. Rock, S.M., Frew, E.W., Hank, J., Lemaster, E.A. and Woodley, B.R., Combined CDGPS and vision-based control of a small autonomous helicopter, 1998, American Control Conference, June 1998, pp 694–698.Google Scholar
9. Silveira, G.F., Carvalho, J.R.H., Madirid, M.K., Rives, P. and Bueno, S.S., A fast vision-based road following strategy applied to the control of aerial robots, 2001, Brazilian Symposium on Computer Graphics and Image Processing, 15-18 October 2001, pp. 226–231.Google Scholar
10. Causey, R., A Lateral Vision-based Control Autopilot for Micro Air Vehicles using a Horizon Detection Approach, December 2003, MSc Thesis, Department of Mechanical and Aerospace Engineering, University of Florida.Google Scholar
11. Chatterji, G.B., Menon, P.K. and Sridhar, B., Vision-based position and attitude determination for aircraft night landing, J Guidance, Control and Dynamics, January-February 1998, 21, (1), pp 84–92.Google Scholar
12. Ettinger, S.M., Nechyba, M.C., Ifju, P.G. and Waszak, M.R., Visionguided flight stability and control for micro air vehicles, 2002, IEEE International Conference on Intelligent Robots and Systems, October 2002.Google Scholar
13. Frew, E., McGee, T., Kim, Z., Xiao, X., Jackson, S., Morimoto, M., Rathinam, S., Padial, J. and Sengupta, R., Vision-based road-following using a small autonomous aircraft, 2004, IEEE Aerospace Conference, March 2004.Google Scholar
14. Kwolek, B., Kapuscinski, T. and Wysocki, M., Vision-based implementation of feedback control of unicycle robots, 1999, Robot Motion and Control Workshop, 28-29 June 1999, pp 101–106.Google Scholar
15. Ifju, P.G., Jenkins, D.A., Ettinger, S., Lian, Y., Shyy, W. and Waszak, M.R., Flexible-wing-based micro air vehicles, 2002, AIAA 2002–0705.Google Scholar
16. Stevens, B. and Lewis, F., Aircraft Control and Simulation, 1992, Wiley Inter-Science, New York.Google Scholar