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Computationaly simple obstacle avoidance control law for small unmanned aerial vehicles

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The investigations of the system which allow to avoid obstacles by the unmanned aerial vehicles (UAV) are presented in the paper. The system is designed to enable the full autonomous UAV flight in an unknown environment. As an information source about obstacles digital camera was used. Developed algorithm uses the existing relations between the imaging system and the parameters read from the UAV autopilot. Synthesis of the proposed obstacle avoidance control law was oriented for computational simplicity. Presented algorithm was checked during simulation studies and in-flight tests.
Rocznik
Strony
50--56
Opis fizyczny
Bibliogr. 16 poz., rys., wykr.
Twórcy
autor
  • Faculty of Mechanical Engineering, Automatic Control and Robotics Department, Bialystok University of Technology, ul. Wiejska 45C, 15-351 Białystok, Poland
autor
  • Faculty of Mechanical Engineering, Automatic Control and Robotics Department, Bialystok University of Technology, ul. Wiejska 45C, 15-351 Białystok, Poland
autor
  • Faculty of Mechanical Engineering, Automatic Control and Robotics Department, Bialystok University of Technology, ul. Wiejska 45C, 15-351 Białystok, Poland
autor
  • Faculty of Mechanical Engineering, Automatic Control and Robotics Department, Bialystok University of Technology, ul. Wiejska 45C, 15-351 Białystok, Poland
Bibliografia
  • 1. Bresciani T. (2008), Modelling, Identification and Control of a Quadrotor Helicopter, Master’s thesis, Lund University, Sweden.
  • 2. Cieśluk J., Gosiewski Z. (2012), Vision sky detection system used to obstacle avoidance by unmanned aerial, Mechanics in Aviation XV, 2012, pp. 509-523.
  • 3. Cieśluk J., Gosiewski Z. (2013), A Stereovision System for Real Time Obstacle Avoidance by Unmanned Aerial Vehicle, Solid State Phenomena, Vol 198, pp. 159-164.
  • 4. Cieśluk J., Gosiewski Z. (2014), Image brightness control method used for obstacles avoidance by unmanned aerial vehicle, Mechanics in Aviation, 16, 2014, 279-290.
  • 5. Guzel M. S., Bicker R. (2011), Vision Based Obstacle Avoidance Techniques, Recent Advances in Mobile Robotics, Dr. AndonTopalov (Ed.), InTech, UK, 83-101.
  • 6. Herisse B., Russotto, F.-X., Hamel, T., Mahony, R. (2008), Hovering flight and vertical landing control of a VTOL Unmanned Aerial Vehicle using Optical Flow, IEEE International Conference on Intelligent Robots and Systems,pp. 801 – 806.
  • 7. Hoffmann G. M., Huang H., Waslander S. L, Tomlin C. J. (2011), Precision flight control for a multi-vehicle quadrotor helicopter testbed, Control Engineering Practice, Vol. 19, 1023–1036.
  • 8. Khatib O. (1985), The Potential Field Approach and Operational Space Formulation in Robot Control, Proc. Fourth Yale Workshop on Applications of Adaptive Systems Theory, Yale University, New Haven, Connecticut, 208-214.
  • 9. Kownacki C. (2013), Successful Application of Miniature Laser Rangefinders in Obstacle Avoidance Method for Fixed Wing MAV, International Journal of Robotics and Automation, 10.2316/ Journal.206.2013.3.206-3936.
  • 10. Meier L., Tanskanen P., Heng L., Lee G. H., Fraundorfer F., Pollefeys M. (2012), PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision, Autonomous Robots, 33 (1-2), 21-39.
  • 11. Mellinger D., Michael N., Kumar K. (2012), Trajectory generation and control for precise aggressive maneuvers with quadrotors, The International Journal of Robotics Research, Vol. 31, No. 5, 664-674.
  • 12. Modi S. B., Chandak P., Murty V. S., Hall E. L. (2001), Comparison of three obstacle-avoidance methods for a mobile robot, Proc. SPIE 4572, Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision, pp. 290-297.
  • 13. Sabatini R., Gardi A., Richardson M. A. (2014), LIDAR Obstacle Warning and Avoidance System for Unmanned Aircraft, International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, Vol. 8, No 4, 702-713.
  • 14. Shojaeipour S. (2010), Webcam-based mobile robot path planning using Voronoi diagrams and image processing, Proceedings of the 9th WSEAS international conference on Applications of electrical engineering, World Scientific and Engineering Academy and Society (WSEAS), Penang, Malaysia, 151-156.
  • 15. Soumare S., Ohya A., Yuta S. (2002), Real-Time Obstacle Avoidance by an Autonomous Mobile Robot using an Active Vision Sensor and a Vertically Emitted Laser Slit, Intelligent Autonomous Systems, 7, 301-308.
  • 16. Wang L. (2001), Continuous time model predictive control design using orthonormal functions, International Journal of Control, Vol. 74(16), 1588-1600.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6556ab68-39b2-49d9-9127-6cd9d3bf299d
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