The autonomous vision-based Unmanned Aerial Vehicles (UAVs) landing is an adaptive way to land in special environments such as the global positioning system denied. There is a risk of collision when multiple UAVs land simultaneously without communication on the same platform. This work accomplishes vision-based autonomous landing and uses a deep-learning-based method to realize collision avoidance during the landing process. Specifically, the landing UAVs are categorized into Level I and II. The YoloV4 deep learning method will be implemented by the Level II UAV to achieve object detection of Level I UAV. Once the Level I UAV’s landing has been detected by the onboard camera of Level II UAV, it will move and land on a relative landing zone beside the Level I UAV. The experiment results show the validity and practicality of our theory.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Autonomous Vision-Based UAV Landing with Collision Avoidance Using Deep Learning


    Additional title:

    Lect. Notes in Networks, Syst.


    Contributors:
    Arai, Kohei (editor) / Liao, Tianpei (author) / Haridevan, Amal (author) / Liu, Yibo (author) / Shan, Jinjun (author)

    Conference:

    Science and Information Conference ; 2022 July 14, 2022 - July 15, 2022



    Publication date :

    2022-07-07


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Ship Collision Avoidance Autonomous Avoidance System using Deep Learning

    CHO SEOK JE / KIM HYUNG JIN / KIM SOO HO et al. | European Patent Office | 2021

    Free access

    Collision Avoidance Using Deep Learning-Based Monocular Vision

    Rill, Róbert-Adrian / Faragó, Kinga Bettina | Springer Verlag | 2021

    Free access

    Vision-guided Collision Avoidance Through Deep Reinforcement Learning

    Song, Sirui / Zhang, Yuanhang / Qin, Xi et al. | IEEE | 2021


    Computer Vision based Animal Collision Avoidance Framework for Autonomous Vehicles

    Gupta, Savyasachi / Chand, Dhananjai / Kavati, Ilaiah | ArXiv | 2020

    Free access

    Autonomous Collision Avoidance System for a Multicopter using Stereoscopic Vision

    Perez, Erwin / Winger, Alexander / Tran, Alexander et al. | IEEE | 2018