Vision-based unmanned aerial vehicle (UAV) control is a core technology in global positioning system (GPS)-denied environments. However, small UAVs have difficulty processing image data in real time because of their limited payload capacity and relatively weak processor. Development of an image-processing system that is suitable for small UAVs is therefore needed. In this paper, an approach for a vision-based simultaneous localization and mapping (SLAM) system for small UAVs is suggested. For real-time localization, a method wherein Kanade-Lucas-Tomasi-based localization and tracking are performed within small UAVs in real time is adopted. At the same time, scale-invariant feature transform–based mapping and more accurate localization are performed at the ground-control station. A vision-based three-dimensional map-building method for small UAVs using a monocular camera is also proposed. The proposed method first extracts straight-line information from images and calculates their equations in three-dimensional space. It then constructs plane information from line information.


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    Title :

    Vision-Based SLAM System for Small UAVs in GPS-Denied Environments


    Contributors:

    Published in:

    Publication date :

    2011-09-10


    Size :

    112012-01-01 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






    Vision-based SLAM system for MAVs in GPS-denied environments

    Urzua, Sarquis / Munguía Alcalá, Rodrigo Francisco / Grau Saldes, Antoni | BASE | 2017

    Free access