Outliers, such as sensor noise, abnormal measurements, or dynamic objects, can damage the overall accuracy of a Simultaneous Localization and Mapping (SLAM) system. Aiming at to improve the performance of Lidar SLAM systems in urban scenes containing a large number of outliers, we propose a real-time, feature-based, and outliers-rejection Lidar SLAM system. By embedding an outlier elimination method based on 4-points congruent sets into a state-of-the-art SLAM framework and further optimizing the traditional single-step registration to coarse-to-fine registration, we can solve the problem of time-consuming, high motion drift, and wrong mapping caused by the current Lidar SLAM systems which cannot effectively detect and eliminate the outliers in surrounding environment.


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    Titel :

    Robust and Fast Registration for Lidar Odometry and Mapping


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Wu, Tsu-Yang (Herausgeber:in) / Ni, Shaoquan (Herausgeber:in) / Chu, Shu-Chuan (Herausgeber:in) / Chen, Chi-Hua (Herausgeber:in) / Favorskaya, Margarita (Herausgeber:in) / Liu, Wenbo (Autor:in) / Sun, Wei (Autor:in)


    Erscheinungsdatum :

    30.11.2021


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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