Skip to main content
SpringerLink
Log in

Framework for Autonomous On-board Navigation with the AR.Drone

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

We present a framework for autonomous flying using the AR.Drone low cost quadrotor. The system performs all sensing and computations on-board, making the system independent of any base station or remote control. High level navigation, computer vision and control tasks are carried out in an external processing unit that steers the vehicle to a desired location. We experimentally demonstrate the properties and capabilities of three systems to autonomously following several trajectory patterns, visually estimate its position and detecting and following a person and evaluate the performance of the systems.

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. Lupashin, S., Schöllig, A., Sherback, M., D’Andrea, R.: A simple learning strategy for high-speed quadrocopter multi-flips. In: IEEE International Conference on Robotics and Automation, pp. 1642–1648 (2010)

  2. Muller, M., Lupashin, S., D’Andrea, R.: Quadrocopter ball juggling. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5113–5120 (2011)

  3. Mellinger, D., Michael, N., Kumar, V.: Trajectory generation and control for precise aggressive manuevers with quadrotors. Int. J. Robot. Res. 31(5), 664–674 (2012)

    Google Scholar 

  4. Hoffmann, G., Rajnarayan, D.G., Waslander, S.L., Dostal, D., Jang, J.S., Tomlin, C.J.: The Stanford testbed of autonomous rotorcraft for multi-agent control (STARMAC). In: 23rd Digital Avionics Systems Conference, Salt Lake City (2004)

  5. Meier, L., Tanskanen, P., Fraundorfer, F., Pollefeys, M.: Pixhawk: a system for autonomous flight using onboard computer vision. In: IEEE International Conference on Robotics and Automation (ICRA), 2011, pp. 2992–2997 (2011)

  6. Lim, H., Park, J., Lee, D., Kim, H.J.: Build your own quadrotor: open-source projects on unmanned aerial vehicles. IEEE Robot. Automat. Mag. 19(3), 33–45 (2012)

    Article  Google Scholar 

  7. Tayebi, A., McGilvray, S., Roberts, A., Moallem, M.: Attitude estimation and stabilization of a rigid body using low-cost sensors. In: 46th IEEE Conference on Decision and Control, 2007, pp. 6424–6429 (2007)

  8. Wenzel, K., Masselli, A., Zell, A.: Automatic take off, tracking and landing of a miniature uav on a moving carrier vehicle. J. Intell. Robot. Syst. 61, 221–238 (2011). doi:10.1007/s10846-010-9473-0

    Article  Google Scholar 

  9. Wenzel, K.E., Masselli, A., Zell, A.: Visual tracking and following of a quadrocopter by another quadrocopter. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4993–4998 (2012). doi:10.1109/IROS.2012.6385635

  10. Saska, M., Krajník, T., Faigl, J., Vonásek, V., Preucil, L.: Low cost mav platform ar-drone in experimental verifications of methods for vision based autonomous navigation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012), pp. 4808–4809 (2012)

  11. Faigl, J., Krajník, T., Vonásek, V., Přeučil, L.: Surveillance planning with localization uncertainty for UAVs. In: 3rd Israeli Conference on Robotics, Ariel (2010)

  12. Bills, C., Chen, J., Saxena, A.: Autonomous mav flight in indoor environments using single image perspective cues. In: IEEE International Conference on Robotics and Automation, pp. 5776–5783 (2011)

  13. Engel, J., Sturm, J., Cremers, D.: Camera-based navigation of a low-cost quadrocopter. In: Proc. of the International Conference on Intelligent Robot Systems (IROS) (2012)

  14. Klein, G., Murray, D.: Parallel tracking and mapping for small AR workspaces. In: Proc. Sixth IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR’07), Nara, Japan (2007)

  15. Jimenez Lugo, J., Zell, A.: Framework for autonomous onboard navigation with the ar.drone. In: 2013 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 575–583 (2013)

  16. Bristeau, P.-J., Callou, F., Vissiere, D., Petit, N.: The navigation and control technology inside the AR.Drone micro uav. In: 18th IFAC World Congress, pp. 1477–1484, Milano, Italy (2011)

  17. Trajkovic, M., Hedley, M.: Fast corner detection. Image Vis. Comput. 16(2), 75–87 (1998)

    Article  Google Scholar 

  18. Masselli, A., Zell, A.: A novel marker based tracking method for position and attitude control of MAVs. In: Proceedings of International Micro Air Vehicle Conference and Flight Competition, pp. 1–6, DGON, Braunschweig (2012)

Download references

Author information

Authors and Affiliations

  1. Cognitive Systems, University of Tübingen, Tübingen, Germany

    Jacobo Jiménez Lugo & Andreas Zell

Authors
  1. Jacobo Jiménez Lugo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andreas Zell
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jacobo Jiménez Lugo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jiménez Lugo, J., Zell, A. Framework for Autonomous On-board Navigation with the AR.Drone. J Intell Robot Syst 73, 401–412 (2014). https://doi.org/10.1007/s10846-013-9969-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-013-9969-5

Keywords

Search

Navigation