Unmanned aerial vehicles (UAVs) find astounding applications in some of the key areas of search and rescue operations, precision agriculture (PA), remote sensing, etc. The unique ability of a UAV to hover right above the target location and collect useful information makes it a suitable candidate for many such applications. UAV has been utilized in many key applications such as navigation and control, and visual-based detection, but autonomous decision-making and carrying out mid-air actions, such as PA for weed control, is an open research area. In the proposed study, a novel framework has been presented for detecting multiple targets (crop, weed, mud, etc.), recognition and navigation, and subsequent movement of UAVs towards the proposed targets. The successful implementation of the model in UAV would enable it for weed control in PA, among others. The presented framework utilizes a robust computation, convolutional neural network (CNN) model for target detection and recognition, while proximate probing is performed using a PID-based algorithm, ensuring UAV hover right above the target. The proposed framework has been developed in five successive steps by adopting Lawson’s sense, process, compare, decide, and act model. The framework is successfully validated on simulation flights conducted in Gazebo and PX4 and real field experiments. The experiments’ results showed the versatility of the developed system to many complex missions where targets are added or removed.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    An Intelligent Vision-Guided Framework of the Unmanned Aerial System for Precision Agriculture


    Weitere Titelangaben:

    Algorithms for Intelligent Systems


    Beteiligte:
    Bansal, Jagdish Chand (Herausgeber:in) / Uddin, Mohammad Shorif (Herausgeber:in) / Khan, Shahbaz (Autor:in) / Tufail, Muhammad (Autor:in) / Khan, Muhammad Tahir (Autor:in) / Khan, Zubair Ahmad (Autor:in) / Iqbal, Javaid (Autor:in) / Khan, Razaullah (Autor:in)


    Erscheinungsdatum :

    01.08.2023


    Format / Umfang :

    18 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Intelligent pesticide spreading unmanned aerial vehicle for intelligent agriculture

    SUN HAICHUAN | Europäisches Patentamt | 2025

    Freier Zugriff

    Special intelligent unmanned aerial vehicle for agriculture and forestry

    XU FENG | Europäisches Patentamt | 2015

    Freier Zugriff

    Pesticide spraying unmanned aerial vehicle based on intelligent agriculture

    XIAO JIAJIA | Europäisches Patentamt | 2022

    Freier Zugriff

    Unmanned aerial vehicle for agriculture

    YANG JUNG HAWN | Europäisches Patentamt | 2016

    Freier Zugriff

    Precision Agriculture as a Commercial Application for Solar-Powered Unmanned Aerial Vehicles

    Herwitz, Stanley / Johnson, Lee / Arvesen, John et al. | AIAA | 2002