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Vision Based Output Feedback Control of Micro Aerial Vehicles in Indoor Environments

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Abstract

We present a new image based visual servoing (IBVS) approach for control of micro aerial vehicles (MAVs) in indoor environments. Specifically, we show how a MAV can be stabilized and guided using only corridor lines viewed on a front facing camera and angular velocity measurements. Since the suggested controller does not include explicit attitude feedback it does not require the use of accelerometers which are susceptible to vibrations, nor complex attitude estimation algorithms. The controller also does not require direct velocity measurements which are difficult to obtain in indoor environments. The paper presents the new method, stability analysis, simulations and experiments.

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References

  1. Araar, O., Aouf, N.: Visual servoing of a quadrotor uav for autonomous power lines inspection. In: MED2014, pp 1418–1424

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

  3. Blosch, M., Scaramuzza, D., Weiss, S., Siegwart, R.: Vision Based Mav Navigation in Unknown and Unstructured Environments. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 2128. 2 (2010)

  4. Bouabdallah, S., Siegwart, R.: Full control of a quadrotor. In: Intelligent robots and systems, pp 153–158 (2007)

  5. Bouabdallah, S., Siegwart, R.: Backstepping and sliding-mode techniques applied to an indoor micro quadrotor. International Conference on Robotics and Automation Barcelona Spain (2005)

  6. Bristeau, P., Callou, F., Vissiere, D., Petit, N.: The Navigation and Control Technology inside the Ar. Drone Micro Uav. In: 18Th IFAC World Congress, Vol. 18, pp. 1477–1484 (2011)

  7. Mark Cutler, N., Kemal, U., Michini, B., How, J.P.: Comparison of fixed and variable pitch actuators for agile quadrotors. AIAA Paper (2011-6406) (2011)

  8. Efraim, H., Arogeti, S., Shapiro, A., Weiss, G.: Output feedback control of micro aerial vehicle in indoor environment. MED, pp. 728–734 (2015)

  9. Carrillo, G., et al.: Stabilization and trajectory tracking of a quad-rotor using vision. J. Intell. Robot. Syst. 61(1–4), 103–118 (2011)

    Article  Google Scholar 

  10. Fernandes, L.A.F., Oliveira, M.M.: Real-time line detection through an improved hough transform voting scheme. Pattern Recogn. 41(1), 299–314 (2008)

    Article  MATH  Google Scholar 

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

    Article  Google Scholar 

  12. Hehn, M., D’Andrea, R.: A Flying Inverted Pendulum. In: 2011 IEEE International Conference on Robotics and Automation (ICRA), pp. 763770. 2 (2011)

  13. Hoffmann, G., Waslander, S., Tomlin, C.: Quadrotor Helicopter Trajectory Tracking Control. In: AIAA Guidance, Navigation and Control Conference and Exhibit, pp. 1–14 (2008)

  14. Sturm, J., Engel, J., Cremers, D.: Camera-Based Navigation of a Low-Cost Quadrocopter. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 28152821. 2 (2012)

  15. Khalil, H.K.: Nonlinear systems. Prentice Hall (2002)

  16. Klein, G., Murray, D.: Parallel Tracking and Mapping for Small Ar Workspaces. In: 6Th IEEE and ACM International Symposium on Mixed and Augmented Reality, ISMAR 2007, pp. 225234. 2 (2007)

  17. Leishman, R., Macdonald, J., Beard, R., McLain, T.: Quadrotors & accelerometers. IEEE Control Systems Magazine (2014)

  18. Liu, C., Zhou, Z., Fu, X.: Attitude determination for mavs using a kalman filter. Tsinghua Sci. Technol. 13, 593–597 (2008)

    Article  Google Scholar 

  19. Euston, R., Mahony, J., Kim, M., Coote, P., Hamel, T.: A Complementary Filter for Attitude Estimation of a Fixed-Wing Uav. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2008

  20. Mellinger, D., Michael, N., Kumar, V.: Trajectory generation and control for precise aggressive maneuvers with quadrotors The International Journal of Robotics Research (2012)

  21. Pounds, P., Mahony, R., Corke, P.: Modelling and Control of a Quad-Rotor Robot. In: Proceedings Australasian Conference on Robotics and Automation 2006. Australian Robotics and Automation Association Inc. (2006)

  22. Cha, S.-H., Mahony, R., Hamel, T.: A Coupled Estimation and Control Analysis for Attitude Stabilisation of Mini Aerial Vehicles. In: Proceedings of the 19Th Australiasian Conference on Robotics and Automation (2006)

  23. Hamel, T., Mahony, R., Pflimlin, J.-M.: Complementary filter design on the special orthogonal group so (3). In: 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference, CDC-ECC05, pp. 14771484. IEEE. (2005)

  24. Schöllig, A., Augugliaro, F., D’Andrea, R.: A platform for dance performances with multiple quadrocopters. Improving Tracking Performance by Learning from Past Data, 147 (2012)

  25. Tournier, G.P., Valenti, M., How, J.P., Feron, E.: Estimation and Control of a Quadrotor Vehicle Using Monocular Vision and Moire Patterns. In: AIAA Guidance, Navigation and Control Conference and Exhibit, pp. 21–24. Citeseer (2006)

  26. Weiss, S., Achtelik, M., Lynen, S., Chli, M., Siegwart, R.: Real-Time Onboard Visual-Inertial State Estimation and Self-Calibration of Mavs in Unknown Environments. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 957–964. 2 (2012)

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Authors and Affiliations

  1. Department of Mechanical Engineering, Ben Gurion University of the Negev, Beersheba, Israel

    Hanoch Efraim, Shai Arogeti & Amir Shapiro

  2. Sami Shamoon College of Engineering, Department of Electrical Engineering, Beer Sheva, Israel

    Hanoch Efraim

  3. Department of Computer Science, Ben Gurion University of the Negev, Beersheba, Israel

    Gera Weiss

Authors
  1. Hanoch Efraim
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  2. Shai Arogeti
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  3. Amir Shapiro
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  4. Gera Weiss
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Correspondence to Hanoch Efraim.

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Efraim, H., Arogeti, S., Shapiro, A. et al. Vision Based Output Feedback Control of Micro Aerial Vehicles in Indoor Environments. J Intell Robot Syst 87, 169–186 (2017). https://doi.org/10.1007/s10846-017-0510-0

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  • DOI: https://doi.org/10.1007/s10846-017-0510-0

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