Skip to main content
SpringerLink
Log in

Design of a 3D snapshot based visual flight control system using a single camera in hover

  • Published:
Autonomous Robots Aims and scope Submit manuscript

Abstract

The problem of developing a reliable system for sensing and controlling the hover of a Micro Air Vehicle (MAV) using visual snapshots is considered. The current problem is part of a larger project, which is developing an autonomous MAV, controlled by vision only information. A new algorithm is proposed that uses a stored image of the ground, a snapshot taken of the ground directly under the MAV, as a visual anchor point. The absolute translation of the aircraft and its velocity are then calculated by comparing the subsequent frames with the stored image and fed into the position controller. In order to increase the performance, several issues, such as effects of scale uncertainty on the closed loop stability of the platform are investigated. For controller design and testing purposes, we analytically derive a complete model of a small size helicopter with no stabilizing bar (flybar). The simulation results for 2D and 3D snapshots confirm the effectiveness of the proposed algorithm.

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

Fig. 2
Fig. 1
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  • Ahrens, S., Levine, D., Andrews, G., & How, J. (2009). Vision-based guidance and control of a hovering vehicle in unknown, GPS-denied environments. In IEEE international conference on robotics and automation, ICRA’09 (pp. 2643–2648). New York: IEEE Press.

    Chapter  Google Scholar 

  • Amidi, O. (1996). An autonomous vision-guided helicopter. PhD thesis, Dept. of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh.

  • Amidi, O., Kanade, T., & Fujita, K. (1999). A visual odometer for autonomous helicopter flight. Robotics and Autonomous Systems, 28(2), 185–193.

    Article  Google Scholar 

  • Beyeler, A., Zufferey, J., & Floreano, D. (2007). 3D Vision-based navigation for indoor microflyers. In Proceedings of the 2007 IEEE international conference on robotics and automation, Rome, Italy, 10–14 April 2007 (pp. 1336–1341).

    Chapter  Google Scholar 

  • Blosch, M., Weiss, S., Scaramuzza, D., & Siegwart, R. (2010). Vision based MAV navigation in unknown and unstructured environments. In IEEE international conference on robotics and automation (ICRA) (pp. 21–28). New York: IEEE Press.

    Google Scholar 

  • Cartwright, B. A., & Collet, T. S. (1983). How honey bees use landmarks to guide their return to a food source. Journal of Comparative & Physiological Psychology, 151, 521–543.

    Article  Google Scholar 

  • Cartwright, B. A., & Collet, T. S. (1992). Landmark learning in bees. Nature, 295, 560.

    Article  Google Scholar 

  • Castillo, C., Alvis, W., Castillo-Effen, M., Valavanis, K., & Moreno, W. (2005). Small scale helicopter analysis and controller design for non-aggressive flights. In IEEE international conference on SMC, Hawaii, October 2005.

    Google Scholar 

  • Cherian, A., Andersh, J., Morellas, V., Papanikolopoulos, N., & Mettler, B. (2009). Autonomous altitude estimation of a UAV using a single onboard camera. In IROS 2009, IEEE/RSJ international conference on intelligent robots and systems (pp. 3900–3905). New York: IEEE Press.

    Chapter  Google Scholar 

  • Corke, P. (2004). An inertial and visual sensing system for a small autonomous helicopter. Journal of Robotic Systems, 21(2), 43–51.

    Article  Google Scholar 

  • Garratt, M. A. (2007). Biologically inspired vision and control for an autonomous helicopter. PhD thesis, Research School of Biological Sciences, Australian National University, Canberra, Australia.

  • Garratt, M. A., & Chahl, J. S. (2007). An optic flow damped hover controller for an autonomous helicopter. In Proceedings of the 22nd international UAV systems conference, Bristol, UK, 16–18 April 2007 (pp. 16–18).

    Google Scholar 

  • Garratt, M. A., & Chahl, J. S. (2008). Vision-based terrain following for an unmanned rotorcraft. Journal of Field Robotics, 25(4–5), 284–301.

    Article  Google Scholar 

  • Garratt, M. A., Lambert, A., & Guillemette, T. (2009). FPGA implementation of an optic flow sensor using the image interpolation algorithm. In Proceedings of the Australian conference on robotics and automation, Sydney, Australia, 2–4 December 2009.

    Google Scholar 

  • Griffiths, S., Saunders, J., Curtis, A., Barber, B., McLain, T., & Beard, R. (2006). Maximizing miniature aerial vehicles: obstacle and terrain avoidance for MAVs. IEEE Robotics and Automation Magazine, 13(3), 34–43.

    Article  Google Scholar 

  • Hung, A., Pickering, M., & Garratt, M. A. (2011). Fast image registration using a multi-pass image interpolation approach. In 7th international conference on information technology and applications (ICITA 2011), Sydney, 21–24 Nov. 2011.

    Google Scholar 

  • Keyence Corporation (2011). Revolutor H-610 operating instructions. http://hobby.keyence.co.jp/english/manual.html. Accessed 1 Nov. 2011.

  • Mejias, L., Saripalli, S., Campoy, P., & Sukhatme, G. S. (2006). Visual servoing of an autonomous helicopter in urban areas using feature tracking. Journal of Field Robotics, 23, 185–199.

    Article  Google Scholar 

  • Mettler, B. (2003). Identification modeling and characteristics of miniature rotorcraft. Norwell: Kluwer Academic.

    Book  Google Scholar 

  • Mettler, B., Tischler, M. B., Kanade, T., & Messner, W. (2000). Attitude control optimization for a small-scale unmanned helicopter. In AIAA guidance, navigation and control conference (pp. 40–59).

    Google Scholar 

  • Padfield, G. D. (2007). Helicopter flight dynamics. Ames: Blackwell.

    Book  Google Scholar 

  • Prouty, R. W. (1990). Helicopter performance, stability, and control. Melbourne: Robert E. Krieger.

    Google Scholar 

  • Saripalli, S., Montgomery, J. F., & Sukhatme, G. S. (2003). Visually guided landing of an unmanned aerial vehicle. IEEE Transactions on Robotics and Automation, 19, 371–380.

    Article  Google Scholar 

  • Shakernia, O., Vidal, R., Sharp, C., Ma, Y., & Sastry, S. (2002). Multiple view motion estimation and control for landing an unmanned aerial vehicle. In Proceedings of the IEEE international conference on robotics and automation, Nov. 2002 (Vol. 3, pp. 2793–2798).

    Google Scholar 

  • Sharp, C. S., Shakernia, O., & Sastry, S. S. (2001). A vision system for landing an unmanned aerial vehicle. In IEEE international conference on robotics and automation.

    Google Scholar 

  • Srinivasan, M. V. (1994). An image-interpolation technique for the computation of optic flow and egomotion. Biological Cybernetics, 71(5), 401–415.

    Article  MATH  Google Scholar 

  • Zingg, S., Scaramuzza, D., Weiss, S., & Siegwart, R. (2010). MAV navigation through indoor corridors using optical flow. In IEEE international conference on robotics and automation (ICRA) (pp. 3361–3368). New York: IEEE Press.

    Google Scholar 

Download references

Acknowledgements

This work was carried out with funding provided by the Australian Defence Science and Technology Organisation.

Author information

Authors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales at the Australian Defence Force Academy, Canberra, ACT, 2600, Australia

    Matthew A. Garratt, Andrew J. Lambert & Hamid Teimoori

Authors
  1. Matthew A. Garratt
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrew J. Lambert
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hamid Teimoori
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hamid Teimoori.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Garratt, M.A., Lambert, A.J. & Teimoori, H. Design of a 3D snapshot based visual flight control system using a single camera in hover. Auton Robot 34, 19–34 (2013). https://doi.org/10.1007/s10514-012-9310-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10514-012-9310-3

Keywords

Search

Navigation