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  • Title

    Autopilot model for returning an unmanned aerial vehicle to its starting point in case of electromagnetic noise

  • Authors

    Antoshchuk S. G.
    Maksymov Оleksiy М.
    Wendl М.

  • Subject


  • Year 2017
    Issue 3(53)
    UDC 62-529
    DOI 10.15276/opu.3.53.2017.13
    Pages 94-101
  • Abstract

    The possibility of returning an unmanned aerial vehicle in case of electromagnetic interference, which blocks the use of the global positioning system and radio control system, is considered. It has been shown that in the situation of gathering information about the area over which the route of unmanned aerial vehicle runs, using passive sensors and cameras, it is possible to position the machine to return to the starting point. An analysis of models, which allowed creating a simulation of flight process and positioning, was made.

  • Keywords autopilot, simultaneous localization and mapping, computer vision
  • Viewed: 1308 Dowloaded: 15
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  • References

    1. Chris Patton. Photography Without Lenses. 2007. 39 p. URL: http://pinhole.stanford.edu/ imag-es/cpbeyond.pdf (Last accessed 03.09.2017).
    2. Camera Models and Fundamental Concepts Used in Geometric Computer Vision / Sturm P. et al. 2011. 187 p. URL: http://www.merl.com/publications/docs/TR2011-069.pdf (Last accessed 02.09.2017).
    3. Wilhelm Burger. Zhang’s Camera Calibration Algorithm:In-Depth Tutorial and Implementation. Tech-nical Report HGB16-05 16th May, 2016. 2016. 55 p. URL: https://www.researchgate.net/ publica-tion/303233579 (Last accessed 03.09.2017).
    4. Juyang Weng, Paul Cohen, Marc Herniou (1992). Camera Calibration with Distortion Models and Ac-curacy Evaluation Distortion. IEEE TRANSACTIONS ON PAmRN ANALYSIS AND MACHINE INTEL-LIGENCE. Vol. 14, №10. 1992. P. 965–980. URL: https://www.cs.auckland.ac.nz/courses/ comp-sci773s1c/lectures/camera%20distortion.pdf (Last accessed 07.09.2017).
    5. Oskarsson M. Two-View Orthographic Epipolar Geometry: Minimal and Optimal Solvers. J Math Imaging Vis. 2017. P. 1–11 DOI: 10.1007/s10851-017-0753-1 (Last accessed 05.09.2017).

    6. Ethan Rublee, Vincent Rabaud, Kurt Konolige, Gary Bradski. ORB: an efficient alternative to SIFT or SURF. Willow Garage, Menlo Park, California. URL: http://www.willowgarage.com/sites/ de-fault/files/orb_final.pdf (Last accessed 02.09.2017).

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