IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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A Real Time Quadrotor Autonomous Navigation and Remote Control Method

실시간 쿼드로터 자율주행과 원격제어 기법

  • Received : 2013.02.15
  • Accepted : 2013.04.12
  • Published : 2013.08.31
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Abstract

In recent, the demand of Unmanned Aerial Vehicles (UAVs) that can autonomous navigation and remote control has been increased in military, civil and commercial field. Particularly, existing researches focused on autonomous navigation method based on vanish point and remote control method based on event processing in indoor environments. However, the existing methods have some problems. For instance, a detected vanish point in intersection point has too much detection errors. In addition, the delay is increased in existing remote control system for processing images in real time. Thus, we propose improved vanish point algorithm by removing detection errors in intersection point. We also develop a remote control system with android platform by separating flying control and image process. Finally, we compare the proposed methods with existing methods to show the improvement of our approaches.

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References

  1. R.S. Pressman, "Software Engineering A Practitioners' Approach," 6th Edition, McGraw Hill, New York, 2005.
  2. N. Dijkshoorn, A. Visser, "Integrating sensor and motion model to localize an autonomous Ar.Drone," Intl. Journal of Micro Air Vehicles, Vol. 3, No. 4, pp.183-200, 2011. https://doi.org/10.1260/1756-8293.3.4.183
  3. C. Bills, "Autonomous MAV flight in indoor environments using single image perspective cues," Proceedings on IEEE Intl. Conference of Robotics and Automation, pp.5776-5783, 2011.
  4. K. Celik, S. Chung, M. Clausman, A. Somani, "Monocular vision SLAM for indoor aerial vehicles," Proceedings on IEEE Intl. Conference of Intelligent Robots and Systems, pp.1566-1573, 2009.
  5. Z. Zhou, T. Chen, D. Wu, C. Yu, "Corridor navigation and obstacle distance estimation for monocular vision mobile robots," JDCTA: Intl. Journal of Digital Content Technology and its Applications, Vol. 5, No. 3. pp.192-202, 2011. https://doi.org/10.4156/jdcta.vol5.issue3.19
  6. "Parrot Ar.Drone", the resource available at http://ardrone.parrot.com [online].
  7. "JavaDrone", the resource available at http://code.google.com/pjavadrone/2011 [online].
  8. "FusionDrone", the resource available at https://projects.ardrone.org [online].
  9. J. Roberts, T. Stirling, J. Zuffery, D. Floreano, "Quadrotor using minimal sensing for autonomous indoor flight," Proceedings on the European Micro Air Vehicle Conference and Flight Competition, 2007.
  10. R. Carelli, E. Freire, "Corridor navigation and wall-following stable control for sonar-based mobile robots," Robotics and Autonomous Systems, Vol. 45, No. 4, pp.235-247, 2003. https://doi.org/10.1016/j.robot.2003.09.005
  11. S. Se, D. Lowe, J. Little,"Vision-based mobile robot localization and mapping using scaleinvariant features," Proceedings on IEEE Intl. Conference of Robotics and Automation, pp.2051-2058, 2001.
  12. M. Quigley, B. Gerkey, K. Conley, J. Faust, T. Foote, J. Leibs, E. Berger, R. Wheller, A. Ng, "ROS: an open-source Robot Operating System," Proceedings on IEEE Intl. Conference of Robotics and Automation workshop on open source software, 2009.
  13. "Robot Operating System Documentation", the resource available at http://www.ros.org/ [online].
  14. W.S. Ng, E. Sharlin, "Collocated interaction with flying robots," Proceedings on IEEE Intl. Conference of RO-MAN, pp.143-149, 2011.
  15. S. Piskorski, N. Brulez, "AR.Drone Developer Guide," Revision SDK 1.6, 2011.
  16. J. Canny, "A computational approach to edge detection," IEEE Transactions on. Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp.679-698, 1986.
  17. N. Kiryati, Y. Eldar, A.M. Bruckstein, "A probabilistic Hough transform," Pattern Recognition, Vol. 24, No. 4, pp.303-316, 1991. https://doi.org/10.1016/0031-3203(91)90073-E

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