Journal of Intelligent & Robotic Systems

, Volume 92, Issue 1, pp 125–143 | Cite as

Quadrotor Autonomous Approaching and Landing on a Vessel Deck

  • Liyang Wang
  • Xiaoli BaiEmail author


Autonomous landing of a quadrotor UAV on a vessel deck is challenging due to the special sea environment. In this paper, we present an on-board monocular vision based solution that provides a quadrotor with the capability to autonomously track and land on a vessel deck platform with simulated high sea state conditions. The whole landing process includes two stages: approaching from a long range and landing after hovering above the landing platform. Only on-board sensors are used in both stages, without external information input. We use Parrot AR.Drone as the experimental quadrotor platform, and a self-designed vessel deck emulator is constructed to evaluate the effectiveness of the proposed vessel deck landing solution. Experimental results demonstrate the accuracy and robustness of the developed landing algorithms.


Autonomous landing Quadrotor Vessel deck Visual tracking 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



The authors would acknowledge the research support from the Air Force Office of Scientific Research (AFOSR) FA9550-16-1-0184 and the Office of Naval Research (ONR) N00014-16-1-2729. The instructive suggestions from Dr. David B. Findlay are also gratefully acknowledged.

Supplementary material

10846_2017_757_MOESM1_ESM.mp4 (24 mb)
(MP4 24.0 MB)
10846_2017_757_MOESM2_ESM.mp4 (21.8 mb)
(MP4 21.8 MB)

(MP4 4.43 MB)

10846_2017_757_MOESM4_ESM.mp4 (14.5 mb)
(MP4 14.5 MB)


  1. 1.
    Jin, S., Zhang, J., Shen, L., Li, T.: On-board vision autonomous landing techniques for quadrotor: a survey. In: Control conference (CCC), 2016 35th Chinese, pp. 10,284–10,289. IEEE, Chengdu (2016)Google Scholar
  2. 2.
    Ling, K., Chow, D., Das, A., Waslander, S.L.: Autonomous maritime landings for low-cost vtol aerial vehicles. In: 2014 Canadian conference on computer and robot vision (CRV), pp. 32–39. IEEE, Montreal (2014)Google Scholar
  3. 3.
    Daly, J.M., Ma, Y., Waslander, S.L.: Coordinated landing of a quadrotor on a skid-steered ground vehicle in the presence of time delays. In: 2011 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp. 4961–4966. IEEE, San Francisco (2011)Google Scholar
  4. 4.
    Sanchez-Lopez, J.L., Pestana, J., Saripalli, S., Campoy, P.: An approach toward visual autonomous ship board landing of a vtol uav. J. Intell. Robot. Syst. 74(1–2), 113–127 (2014)CrossRefGoogle Scholar
  5. 5.
    Gautam, A., Sujit, P., Saripalli, S.: A survey of autonomous landing techniques for uavs. In: 2014 international conference on unmanned aircraft systems (ICUAS), pp. 1210–1218. IEEE, Orlando (2014)Google Scholar
  6. 6.
    Pebrianti, D., Kendoul, F., Azrad, S., Wei, W., Nonami, K.: Autonomous hovering and landing of a quad-rotor micro aerial vehicle by means of on ground stereo vision system. Journal of System Design and Dynamics 4(2), 269–284 (2010)CrossRefGoogle Scholar
  7. 7.
    Kong, W., Zhang, D., Wang, X., Xian, Z., Zhang, J.: Autonomous landing of an uav with a ground-based actuated infrared stereo vision system. In: 2013 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp. 2963–2970. IEEE, Tokyo (2013)Google Scholar
  8. 8.
    Kong, W., Zhou, D., Zhang, D., Zhang, J.: Vision-based autonomous landing system for unmanned aerial vehicle: a survey. In: 2014 international conference on multisensor fusion and information integration for intelligent systems (MFI), pp. 1–8. IEEE, Beijing (2014)Google Scholar
  9. 9.
    Barnard, S.T., Fischler, M.A.: Computational stereo. ACM Comput. Surv. (CSUR) 14(4), 553–572 (1982)CrossRefGoogle Scholar
  10. 10.
    Strydom, R., Thurrowgood, S., Denuelle, A., Srinivasan, M.V.: Uav guidance: a stereo-based technique for interception of stationary or moving targets. In: Conference towards autonomous robotic systems, pp. 258–269. Springer, Liverpool (2015)Google Scholar
  11. 11.
    Chen, X., Phang, S.K., Shan, M., Chen, B.M.: System integration of a vision-guided uav for autonomous landing on moving platform. In: IEEE international conference on control and automation (ICCA), 2016 12th, pp. 761–766. IEEE, Kathmandu (2016)Google Scholar
  12. 12.
    Benini, A., Rutherford, M.J., Valavanis, K.P.: Real-time, gpu-based pose estimation of a uav for autonomous takeoff and landing. In: IEEE international conference on robotics and automation (ICRA), 2016, pp. 3463–3470. IEEE, Stockholm (2016)Google Scholar
  13. 13.
    Cocchioni, F., Frontoni, E., Ippoliti, G., Longhi, S., Mancini, A., Zingaretti, P.: Visual based landing for an unmanned quadrotor. J. Intell. Robot. Syst. 84(1-4), 511–528 (2016)CrossRefGoogle Scholar
  14. 14.
    Benini, A., Mancini, A., Longhi, S.: An imu/uwb/vision-based extended kalman filter for mini-uav localization in indoor environment using 802.15. 4a wireless sensor network. J. Intell. Robot. Syst. 70, 1–16 (2013)CrossRefGoogle Scholar
  15. 15.
    Meguro, J.-I., Murata, T., Takiguchi, J.-I., Amano, Y., Hashizume, T.: Gps multipath mitigation for urban area using omnidirectional infrared camera. IEEE Trans. Intell. Transp. Syst. 10(1), 22–30 (2009)CrossRefGoogle Scholar
  16. 16.
    Wenzel, K.E., Masselli, A., Zell, A.: Automatic take off, tracking and landing of a miniature uav on a moving carrier vehicle. J. Intell. Robot. Syst. 61(1), 221–238 (2011)CrossRefGoogle Scholar
  17. 17.
    Hu, B., Lu, L., Mishra, S.: Fast, safe and precise landing of a quadrotor on an oscillating platform. In: American control conference (ACC), 2015, pp. 3836–3841. IEEE, Chicago (2015)Google Scholar
  18. 18.
    Dougherty, J., Lee, D., Lee, T.: Laser-based guidance of a quadrotor uav for precise landing on an inclined surface. In: American control conference (ACC), 2014, pp. 1210–1215. IEEE, Portland (2014)Google Scholar
  19. 19.
    Das, P.I.T.M., Swami, S., Conrad, J.M.: An algorithm for landing a quadrotor unmanned aerial vehicle on an oscillating surface. In: Southeastcon, 2012 proceedings of IEEE, pp. 1–4. IEEE, Orlando (2012)Google Scholar
  20. 20.
    Venugopalan, T., Taher, T., Barbastathis, G.: Autonomous landing of an unmanned aerial vehicle on an autonomous marine vehicle. In: Oceans, 2012, pp. 1–9. IEEE, Hampton Roads (2012)Google Scholar
  21. 21.
    Chaves, S.M., Wolcott, R.W., Eustice, R.M.: Neec research: toward gps-denied landing of unmanned aerial vehicles on ships at sea. Nav. Eng. J. 127(1), 23–35 (2015)Google Scholar
  22. 22.
    Krajník, T., Vonásek, V., Fišer, D., Faigl, J.: Ar-drone as a platform for robotic research and education. In: International conference on research and education in robotics, pp. 172–186. Springer, Prague (2011)Google Scholar
  23. 23.
    Garratt, M., Pota, H., Lambert, A., Eckersley-Maslin, S., Farabet, C.: Visual tracking and lidar relative positioning for automated launch and recovery of an unmanned rotorcraft from ships at sea. Nav. Eng. J. 121(2), 99–110 (2009)CrossRefGoogle Scholar
  24. 24.
    Björck, Å.: Numerical methods for least squares problems. SIAM (1996)Google Scholar
  25. 25.
    Yakimenko, O.A., Kaminer, I.I., Lentz, W.J., Ghyzel, P.: Unmanned aircraft navigation for shipboard landing using infrared vision. IEEE Trans. Aerosp. Electron. Syst. 38(4), 1181–1200 (2002)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Mechanical and Aerospace EngineeringRutgers UniversityPiscatawayUSA

Personalised recommendations