Within the next few years, unmanned quadrotors are likely to become an important vehicle in humans' daily life. However, their automatic navigation and landing in indoor environments are among the commonly discussed topics in this regard. In fact, the quadrotor should be able to automatically find the landing point from the nearby position, navigate toward it, and finally, land on it accurately and smoothly. In this paper, we proposed a low-cost and thorough solution to this problem by using both bottom-facing and front-facing cameras of the drone. In addition, in the case that vision data were unavailable, inertial measurements alongside a Kalman filter were used to navigate the drone to achieve the promising continuity and reliability. An AR.Drone 2.0 quadrotor, as well as an ArUco marker, were employed in order to test the proposed method experimentally. The results indicated that the drone successfully landed on the predefined position with an acceptable time and accuracy.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Automatic navigation and landing of an indoor AR. drone quadrotor using ArUco marker and inertial sensors


    Beteiligte:


    Erscheinungsdatum :

    01.11.2017


    Format / Umfang :

    298842 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Drone Position Tracking System based on Object Detection and ArUco Marker for Autonomous Navigation Applications

    Arie Wicaksana, Hendra Bagus / Mardiyanto, Ronny / Irfansyah, Astria Nur | IEEE | 2024


    Indoor Navigation of an Autonomous Guided Vehicle Using ArUco Markers

    Figueiredo, Fernando A. V. / Pereira, Eduardo G. C. / Vasques, César M. A. | Springer Verlag | 2023


    Computer Vision-Driven Precision Landing in Quadcopter Drones Using ArUco Markers

    Putra, Karisma Trinanda / Zidni, Hasan / Mustar, Muhamad Yusvin et al. | IEEE | 2024


    ArUco markers pose estimation in UAV landing aid system

    Marut, Adam / Wojtowicz, Konrad / Falkowski, Krzysztof | IEEE | 2019


    Embedded ArUco: a novel approach for high precision UAV landing

    Khazetdinov, Artur / Zakiev, Aufar / Tsoy, Tatyana et al. | IEEE | 2021