Science China Technological Sciences

, Volume 60, Issue 3, pp 434–443 | Cite as

Vision algorithms for fixed-wing unmanned aerial vehicle landing system

Article
  • 75 Downloads

Abstract

Autonomous landing has become a core technology of unmanned aerial vehicle (UAV) guidance, navigation and control system in recent years. As a novel autonomous landing approach, computer vision has been studied and applied in rotary-wing UAV landing successfully. This paper aims to fixed-wing UAV and focus on two problems: how to find runway only depending on airborne front-looking camera and how to align UAV with the designated landing runway. The paper can be divided into two parts to solve above two problems respectively. In the first part, the paper firstly presents an algorithm of region of interest (ROI) detection, which is based on spectral residual saliency map, and then an algorithm of feature vector extraction based on sparse coding and spatial pyramid matching (SPM) is proposed, finally, ROI including designated landing runway is recognized by a linear support vector machine. In the second part, the paper presents an approach of relative position and pose estimation between UAV and landing runway. Estimation algorithm firstly selects five feature points on the runway surface, and then establishes a new earth-fixed reference frame, finally uses orthogonal iteration to estimate landing parameters including three parameters of distance, height and offset, and three pose parameters of roll, yaw, pitch. The experimental results verify the effectiveness of the algorithms proposed in this paper.

Keywords

vision-based landing spectral residual sparse coding position and pose estimation orthogonal iteration 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Eisen N D, Gagne A, Stutsman R, et al. Low-cost autonomous landing of a midsize fixed-wing UAV. Technical Report. Pennsylvania: University of Pennsylvania, 2014Google Scholar
  2. 2.
    Duan H, Li H, Luo Q, et al. A binocular vision-based UAVs autonomous aerial refueling platform. Sci China Inf Sci, 2016, 59: 053201CrossRefGoogle Scholar
  3. 3.
    Sanchez-Lopez J L, Pestana J, Saripalli S, et al. An approach toward visual autonomous ship board landing of a VTOL UAV. J Intell Robot Syst, 2014, 74: 113–127CrossRefGoogle Scholar
  4. 4.
    Tang D, Hu T, Shen L, et al. Ground stereo vision-based navigation for autonomous take-off and landing of UAVs: A chan-vese model approach. Int J Adv Robot Syst, 2016, doi: 10.5772/62027Google Scholar
  5. 5.
    Ma Z, Hu T, Shen L. Stereo vision guiding for the autonomous landing of fixed-wing UAVs: A saliency-inspired approach. Int J Adv Robot Syst, 2016, doi: 10.5772/62257Google Scholar
  6. 6.
    Kim J, Lee S, Choi S, et al. Fully automatic taxiing, takeoff and landing of a UAV using a single-antenna GPS receiver only. In: International Conference on Control, Automation and Systems. IEEE, 2007. 821–825Google Scholar
  7. 7.
    Lange S, Sünderhauf N, Protzel P. Autonomous landing for a multirotor UAV using vision. In: Workshop Proceedings of SIMPAR 2008, Venice, Italy, 2008. 482–491Google Scholar
  8. 8.
    Vegula S K, Kashyap S K, Shanthakumar N. Detection of runway and obstacles using electro-optical and infrared sensors before landing. Defence Sci J, 2014, 64: 67–76CrossRefGoogle Scholar
  9. 9.
    Kim H J, Kim M, Lim H, et al. Fully autonomous vision-based netrecovery landing system for a fixed-wing UAV. IEEE/ASME Trans Mechatron, 2013, 18: 1320–1333CrossRefGoogle Scholar
  10. 10.
    Yang Z Z, Zhou J L, Lang F N. Detection algorithm of airport runway in remote sensing images. Telkomnika Indonesian Journal of Electrical Engineering, 2014, 12: 2776–2783Google Scholar
  11. 11.
    Aytekin Ö, Zongur U, Halici U. Texture-based airport runway detection. IEEE Geosci Remote Sens Lett, 2013, 10: 471–475CrossRefGoogle Scholar
  12. 12.
    Alexe B, Deselaers T, Ferrari V. Measuring the objectness of image windows. IEEE Trans Pattern Anal Mach Intell, 2012, 34: 2189–2202CrossRefGoogle Scholar
  13. 13.
    Kang H W, Hebert M, Efros A A, et al. Data-drive objectness. IEEE Trans Pattern Anal Mach Intell, 2014, 37: 189–195CrossRefGoogle Scholar
  14. 14.
    Hou X D, Zhang L. Saliency detection: A spectral residual approach. In: IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2007Google Scholar
  15. 15.
    Li J, Duan L Y, Chen X, et al. Finding the secret of image saliency in the frequency domain. IEEE Trans Pattern Anal Mach Intell, 2015, 37: 2428–2440CrossRefGoogle Scholar
  16. 16.
    Yang J C, Yu K, Gong Y H, et al. Linear spatial pyramid matching using sparse coding for image classification. In: IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2009Google Scholar
  17. 17.
    Ding M, Wei L, Wang B. Vision-based estimation of relative pose in autonomous aerial refueling. Chin J Aeronautics, 2011, 24: 807–815CrossRefGoogle Scholar
  18. 18.
    Lu C P, Hager G D, Mjolsness E. Fast and globally convergent pose estimation from video images. IEEE Trans Pattern Anal Machine Intell, 2000, 22: 610–622CrossRefGoogle Scholar
  19. 19.
    Qiu H X, Duan H B. Multi-objective pigeon-inspired optimization for brushless direct current motor parameter design. Sci China Tech Sci, 2015, 58: 1915–1923CrossRefGoogle Scholar
  20. 20.
    Sun C H, Duan H B. Markov decision evolutionary game theoretic learning for cooperative sensing of unmanned aerial vehicles. Sci China Tech Sci, 2015, 58: 1392–1400CrossRefGoogle Scholar
  21. 21.
    Zhu Z S, Su A, Liu H B, et al. Vision navigation for aircrafts based on 3D reconstruction from real-time image sequences. Sci China Tech Sci, 2015, 58: 1196–1208CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Shenyang Aircraft Design & Research InstituteAviation Industry Corporation of ChinaShenyangChina
  2. 2.College of Civil AviationNanjing University of Aeronautics and AstronauticsNanjingChina
  3. 3.College of AstronauticsNanjing University of Aeronautics and AstronauticsNanjingChina

Personalised recommendations