This work presents a novel real-time algorithm for runway detection and tracking applied to unmanned aerial vehicles (UAVs). The algorithm relies on a combination of segmentation-based region competition and minimization of a particular energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates can be updated using a Kalman filter (KF) that integrates additional kinematic estimates such as position and attitude angles, derived from video, inertial measurement unit data, or positioning data. This allows a more robust tracking of the runway under turbulence. The performance of the proposed lane detection and tracking scheme is illustrated on various experimental UAV flights conducted by the Saudi Aerospace Research Center (KACST), by the University of Texas, Austin, and on simulated landing videos obtained from a flight simulator. Results show an accurate tracking of the runway edges during the landing phase, under various lighting conditions, even in the presence of roads, taxiways, and other obstacles. This suggests that the positional estimates derived from the video data can significantly improve the guidance of the UAV during takeoff and landing phases.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Fusing Vision and Inertial Sensors for Robust Runway Detection and Tracking


    Contributors:

    Published in:

    Publication date :

    2018-09-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    A robust vision-based runway detection and tracking algorithm for automatic UAV landing

    Abu-Jbara, Khaled / Alheadary, Wael / Sundaramorthi, Ganesh et al. | IEEE | 2015



    FUSING LOW-COST IMAGE AND INERTIAL SENSORS FOR PASSIVE NAVIGATION

    Veth, M. / Raquet, J. | British Library Online Contents | 2007


    Airborne FLIR sensors for runway incursion detection

    Archer, Cynthia / White, Joseph / Neece, Robert | SPIE | 2009


    Fusing visual contour tracking with inertial sensing to recover robot egomotion

    Alenyà, Guillem / Martínez Marroquín, Elisa / Torras, Carme | BASE | 2003

    Free access