Real-time data collection and decision making with drones will play an important role in precision livestock and farming. Drones are already being used in precision agriculture. Nevertheless, this is not the case for indoor livestock and farming environments due to several challenges and constraints. These indoor environments are limited in physical space and there is the localization problem, due to GPS unavailability. Therefore, this work aims to give a step toward the usage of drones for indoor farming and livestock management. To investigate on the drone positioning in these workspaces, two visual simultaneous localization and mapping (VSLAM)—LSD-SLAM and ORB-SLAM—algorithms were compared using a monocular camera onboard a small drone. Several experiments were carried out in a greenhouse and a dairy farm barn with the absolute trajectory and the relative pose error being analyzed. It was found that the approach that suits best these workspaces is ORB-SLAM. This algorithm was tested by performing waypoint navigation and generating maps from the clustered areas. It was shown that aerial VSLAM could be achieved within these workspaces and that plant and cattle monitoring could benefit from using affordable and off-the-shelf drone technology.


    Access

    Download


    Export, share and cite



    Title :

    Visual SLAM for Indoor Livestock and Farming Using a Small Drone with a Monocular Camera: A Feasibility Study


    Contributors:


    Publication date :

    2021




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Indoor navigation for aerial vehicle using monocular visual SLAM

    He, Xiang / Cai, Zhihao / Huang, Dongze et al. | IEEE | 2014


    ORB-SLAM based semi-dense mapping with monocular camera

    Wang, Boshi / Wang, Haiying / Yu, Yuan et al. | IEEE | 2017


    UVS: Underwater Visual SLAM - A Robust Monocular Visual SLAM System for Lifelong Underwater Operations

    Leonardi, Marco / Ludvigsen, Martin / Stahl, Annette et al. | BASE | 2023

    Free access

    Fast semi-dense 3D semantic mapping with monocular visual SLAM

    Li, Xuanpeng / Ao, Huanxuan / Belaroussi, Rachid et al. | IEEE | 2017


    Edge landmarks in monocular SLAM

    Eade, E. / Drummond, T. | British Library Online Contents | 2009