Recently, UAV usage spread to various areas of life. In many cases, UAVs carry expensive equipment onboard. Most of the aircraft damage occurs during the landing due to hard landings. To decrease the number of such situations landing aid systems are being developed. Since most of those systems need special airfield infrastructure, in this project a simple and low-cost system is proposed. This paper provides an overview of the UAV landing aid systems and a concept of the computer vision-based landing aid system. The proposed solution uses ArUco markers as reference points during the landing. By using marker pose estimation algorithm it is possible to determine the height of the flight during the touchdown with high accuracy. The fusion of the data acquired from the inertial sensors generates precise information about the path of the approach of the UAV. In addition, markers placed across the airstrip may be used to navigate during taxing. The developed solution has been tested for accuracy of position determination and for an influence of marker size on accuracy and measurement divergence.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    ArUco markers pose estimation in UAV landing aid system


    Beteiligte:


    Erscheinungsdatum :

    2019-06-01


    Format / Umfang :

    1604171 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Optical multi-camera UAV positioning system via ArUco fiducial markers

    De Corso, Tony / De Vito, Luca / Picariello, Francesco et al. | IEEE | 2023



    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


    Embedded ArUco: a novel approach for high precision UAV landing

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


    Modelling of a Vibration Robot Using Localization Ground Truth Assisted by ArUCo Markers

    Matos, Diogo / Lima, José / Rohrich, Ronnier et al. | Springer Verlag | 2022