Map information is of crucial importance to ensure the safety and reliability of vehicle, no matter indoor or outdoor, it should reflect the real-time changes of environment. Existing indoor map update mechanisms have several common limitations such as small update range, long cycle, large amount of update data, high cost and poor currency. Therefore, we present a multi-vehicle collaborative indoor map update scheme based on edge-cloud architecture to realize real-time autonomous map updating. This scheme can be achieved through continuous monitoring, tagging, identification, and layering of the environment during driving process. Compared with traditional map update schemes, experimental results show that our scheme can effectively realize the collaborative map update in indoor environment, enhance the map update efficiency, reduce the update delay, and improve the adaptability of vehicles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Edge-Cloud Based Vehicle SLAM for Autonomous Indoor Map Updating


    Contributors:
    Zhu, Zepeng (author) / Liu, Jiajia (author) / Wang, Jiadai (author) / Kato, Nei (author)


    Publication date :

    2020-11-01


    Size :

    1918491 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    vSLAM: vision-based SLAM for autonomous vehicle navigation

    Goncalves, Luis / Karlsson, Niklas / Ostrowski, Jim et al. | SPIE | 2004


    End-cloud collaborative urban road condition updating method based on Occ and SLAM

    FENG CHENGTAO / QIAN RUI | European Patent Office | 2024

    Free access



    Indoor navigation for aerial vehicle using monocular visual SLAM

    He, Xiang / Cai, Zhihao / Huang, Dongze et al. | IEEE | 2014