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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    ArUco markers pose estimation in UAV landing aid system


    Contributors:


    Publication date :

    2019-06-01


    Size :

    1604171 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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

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


    Embedded ArUco: a novel approach for high precision UAV landing

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


    Vision-Based Autonomous Ship Deck Landing of an Unmanned Aerial Vehicle Using Fractal ArUco Markers

    Prachand, Chiranjeev / Rustagi, Rahul / Shankar, Ritwik et al. | AIAA | 2025


    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