BRISK based target localization for fixed-wing UAV's vision-based autonomous landing

In this paper, a Binary Robust Invariant Scalable Keypoints (BRISK) based detection is utilized to facilitate the flying unmanned aerial vehicle (UAV) localization within its autonomous landing on the runway. Specifically, two target detection algorithms are proposed and developed as the BRISK-supported approach. Dataset of images and differential GPS are recorded by a ground stereo vision guidance system. By virtue of the landing dataset, experiments are conducted then. Experimental results validate the effectiveness, in terms of efficiency and accuracy, of the proposed target localization algorithms for the fixed-wing aerial vehicle's autonomous landing.

[1]  Tom Drummond,et al.  Machine Learning for High-Speed Corner Detection , 2006, ECCV.

[2]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[3]  Darius Burschka,et al.  Adaptive and Generic Corner Detection Based on the Accelerated Segment Test , 2010, ECCV.

[4]  Roland Siegwart,et al.  BRISK: Binary Robust invariant scalable keypoints , 2011, 2011 International Conference on Computer Vision.

[5]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[6]  Xiang Zhou,et al.  Airborne Vision-Based Navigation Method for UAV Accuracy Landing Using Infrared Lamps , 2013, J. Intell. Robotic Syst..

[7]  Xiang Zhou,et al.  Videometric terminal guidance method and system for UAV accurate landing , 2012, Defense, Security, and Sensing.

[8]  Jianwei Zhang,et al.  Autonomous landing of an UAV with a ground-based actuated infrared stereo vision system , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Christopher Hunt,et al.  Notes on the OpenSURF Library , 2009 .

[10]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[11]  François Chaumette,et al.  Visual detection and 3D model-based tracking for landing on an aircraft carrier , 2011, 2011 IEEE International Conference on Robotics and Automation.

[12]  Kong Weiwei,et al.  Autonomous control of running takeoff and landing for a fixed-wing unmanned aerial vehicle , 2012, 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV).

[13]  Xin Li,et al.  Airborne vision-aided landing navigation system for fixed-wing UAV , 2014, 2014 12th International Conference on Signal Processing (ICSP).

[14]  David Hyunchul Shim,et al.  A Vision-Based Automatic Landing Method for Fixed-Wing UAVs , 2010, J. Intell. Robotic Syst..

[15]  Yu Zhang,et al.  A ground-based optical system for autonomous landing of a fixed wing UAV , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Cordelia Schmid,et al.  A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.