The recent developments in LiDAR technologies has promoted several super high intensity image-grade LiDAR sensors, receiving great interest in the intelligent transportation applications. Although objects detection and high-resolution map construction can benefit from this characteristic, there are several underlying challenges arising from such LiDARs. In this contribution, we present a robust and accurate odometry and mapping scheme for image-grade LiDARs, which addresses many key issues including outliers rejection, moving vehicles filtering, feature extraction and selection. Results from extensive experiments performed in various environments, including feature-poor tunnels and busy urban roads, demonstrate the high accuracy and robustness of the proposed method for state estimation in the real applications.


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    Title :

    Towards Image-Grade LiDAR Odometry and Mapping


    Contributors:
    Wang, Yusheng (author) / Song, Weiwei (author) / Lou, Yidong (author) / Yu, Huan (author)


    Publication date :

    2022-10-08


    Size :

    1397745 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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