Autonomous reconfigurable hybrid tail-sitter UAV U-Lion

Moop

Abstract

We present in this work the development of a novel hybrid unmanned aircraft platform, U-Lion, which has both vertical take-off and landing (VTOL) and cruising flight capabilities. Our design is in tail-sitter structure with reconfigurable wings, which combines the advantages of a fixed-wing plane and a rotor helicopter effectively. This allows it to transit from vertical take-off to hovering, before flying in cruise mode for efficient long duration flight. The propulsion comes from two coaxial contra-rotating motors fixed on a gimbal mechanism, which can change the direction of the motors for the required thrust. This thrust-vectored propulsion system primarily provides control in the VTOL mode but also enhances flight capabilities in the cruise mode. The hybrid aircraft is equipped with GPS and airspeed sensors, and has an onboard avionic system with advanced flight control algorithms to perform fully autonomous VTOL and cruising flights, in addition to transiting effectively between VTOL and cruising flight modes. The overall design has been successfully verified by actual flight experiments.

Keywords

unmanned aerial vehicle vertical take-off and landing hybrid platform aircraft platform design flight control system 

Supplementary material

11432_2016_9002_MOESM1_ESM.mp4 (58.5 mb)
Supplementary material, approximately 59891 KB.

References

  1. 1.
    Bapst R, Ritz R, Meier L, et al. Design and implementation of an unmanned tail-sitter. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, 2015. 1885–1890Google Scholar
  2. 2.
    Oosedo A, Abiko S, Konno A, et al. Development of a quad rotor tail-sitter vtol uav without control surfaces and experimental verification. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, 2013. 317–322Google Scholar
  3. 3.
    Ang K Y Z, Cui J Q, Pang T, et al. Design and implementation of a thrust-vectored unmanned tail-sitter with reconfigurable wings. Unmanned Syst, 2015, 3: 143–162CrossRefGoogle Scholar
  4. 4.
    Selig M S, Guglielmo J J, Broeren A P, et al. Summary of Low-Speed Airfoil Data. Virginia Beach: SoarTech Publications, 1995Google Scholar
  5. 5.
    Anderson Jr J D. Fundamentals of Aerodynamics. 5th ed. Boston: McGraw-Hill, 2010Google Scholar
  6. 6.
    Meier L, Honegger D, Pollefeys M. PX4: a node-based multithreaded open source robotics framework for deeply embedded platforms. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Seattle, 2015. 6235–6240Google Scholar
  7. 7.
    Wang K L, Ke Y J, Chen B M. Development of fully autonomous hybrid UAV U-Lion with vertical and cruise flying capabilities. In: Proceedings of IEEE International Conference on Advanced Intelligent Mechatronics, Banff, 2016Google Scholar
  8. 8.
    Brescianini D, Hehn M, D’Andrea R. Nonlinear quadrocopter attitude control. Technical Report. Department of Mechanical and Process Engineering, ETHZ. 2013Google Scholar
  9. 9.
    Faessler M, Fontana F, Forster C, et al. Automatic re-initialization and failure recovery for aggressive flight with a monocular vision-based quadrotor. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Seattle, 2015. 1722–1729Google Scholar
  10. 10.
    Mayhew C G, Sanfelice R G, Teel A R. Quaternion-based hybrid control for robust global attitude tracking. IEEE Trans Automat Control, 2011, 56: 2555–2566MathSciNetCrossRefGoogle Scholar
  11. 11.
    Ke Y J, Wang K L, Chen BM. A preliminary modeling and control framework for a hybrid UAV J-Lion. In: Proceedings of International Micro Air Vehicle Conference, Beijing, 2016Google Scholar
  12. 12.
    Lai S P, Wang K L, Qin H L, et al. A robust online path planning approach in cluttered environments for micro rotorcraft drones. Control Theory Technol, 2016, 14: 83–96MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Phang S K, Lai S P, Wang F, et al. Systems design and implementation with jerk-optimized trajectory generation for UAV calligraphy. Mechatronics, 2015, 30: 65–75CrossRefGoogle Scholar
  14. 14.
    Park S, Deyst J, How J. A new nonlinear guidance logic for trajectory tracking. In: Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit, 2004. AIAA 2004-2900Google Scholar
  15. 15.
    Lambregts A A. US Patent, 6062513, 2000Google Scholar
  16. 16.
    Lin F, Lum K Y, Chen B M, et al. Development of a vision-based ground target detection and tracking system for a small unmanned helicopter. Sci China Ser F-Inf Sci, 2009, 52: 2201–2215CrossRefMATHGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Unmanned Systems Research Group, 4 Engineering Drive 3National University of SingaporeSingaporeSingapore

Personalised recommendations