Highly accurate extrinsic sensor calibration is crucial for environment perception of robots as it allows to fuse information from different sensors. On todays robotic platforms, e.g. autonomous cars, a variety of different sensors with different measurement characteristics is used. Current calibration approaches ignore the individual sensor characteristics. In this work, we derive an approach for optimal calibration in a probabilistic sense under consideration of these characteristics. Our method can be used with any type of sensors e.g. camera, 3D LiDAR, line scanner and radar. We show in simulation and on real data that our approach significantly outperforms state-of-the-art approaches.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Extrinsic Multi Sensor Calibration under Uncertainties


    Beteiligte:
    Kuhner, Tilman (Autor:in) / Kummerle, Julius (Autor:in)


    Erscheinungsdatum :

    01.10.2019


    Format / Umfang :

    1042574 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Rapid Extrinsic Calibration of Seamless Multi-sensor Navigation System Based on Laser Scanning

    Zhou, Yanglin / Li, Guangyun / Li, Fengyang et al. | British Library Conference Proceedings | 2017


    Automatic extrinsic calibration for lidar-stereo vehicle sensor setups

    Guindel, Carlos / Beltran, Jorge / Martin, David et al. | IEEE | 2017



    ArUco-based Automatic Extrinsic Sensor Calibration for Driverless Train System*

    Pandey, Jyotsna / Takumi, Kudo / Taku, Shimizu et al. | IEEE | 2023


    Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups

    Beltran, Jorge / Guindel, Carlos / de la Escalera, Arturo et al. | IEEE | 2022