In response to the need for inventory management in large-scale warehousing environments, traditional manual counting methods are inefficient and pose safety risks. Additionally, relying solely on the endurance of a single unmanned aerial vehicle (UAV) is limited. Therefore, we propose a warehousing inventory solution based on vehicle-to-drone collaboration, where the solution equips unmanned vehicles with tethered power sources to provide endurance for the UAV. Within this framework, we focus on the key technology of relative positioning during the vehicle-to-drone collaboration process. In this paper, we present a lidar-based vehicle-to-drone collaborative relative positioning algorithm. This algorithm utilizes an upward-facing lidar mounted on the unmanned vehicle to recognize and locate the UAV flying above, thereby enhancing the collaboration between the vehicle and the drone. Compared to traditional methods, the approach described in this paper is less affected by variations in ambient light intensity and exhibits robustness and high accuracy, meeting the requirements for collaborative inventory management in large-scale warehousing environments.


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    Titel :

    Relative Localization of Vehicle-to-Drone Coordination Based on Lidar


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qu, Yi (Herausgeber:in) / Gu, Mancang (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Fu, Wenxing (Herausgeber:in) / Chen, Junzhu (Autor:in) / Chen, Yanchao (Autor:in) / Huang, Dingliang (Autor:in) / Hang, Shuwen (Autor:in) / Zhang, Junrui (Autor:in) / Sun, Chenyang (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2023 ; Nanjing, China September 09, 2023 - September 11, 2023



    Erscheinungsdatum :

    18.04.2024


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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