Sensor calibration is a prerequisite for autonomous driving and is vital for accurate perception, ensuring precise planning and control of the autonomous vehicle. The modern self-driving car considers data inputs from multiple sensors to construct an understanding of its surroundings. These sensors are inherently susceptible to errors arising from measurement uncertainty, and the risk is multiplied under sensor fusion, a critical function for vehicle localization and object detection. Existing works in this field of study largely focus on offline sensor calibration methods where the vehicle is assumed to have undergone the calibration process prior to vehicle operation on the road, typically using a known calibration target such as a checkerboard pattern target. This paper proposes a sensor calibration method for the LiDAR and the inertial navigation system (INS) using high definition (HD) maps as a readily available source of ground truth, giving potential to an online approach to calibration. To match the data between the LiDAR and the INS system, the trajectory from LiDAR odometry based on the normal distributions transform (NDT) and the trajectory from the INS are utilized. The HD map acts as an online calibration target and provides real positional coordinates which can correct for errors inherent to the sensor outputs and enhance the trajectory estimations. Upon the detection of miscalibration, the algorithm finds the optimum transformation matrix that aligns the LiDAR with the INS. Real-world data was used to verify the proposed approach and can be applied to find the correct extrinsic transformation matrix.


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    Titel :

    HD-Map Aided LiDAR-INS Extrinsic Calibration


    Beteiligte:
    Wong, Henry (Autor:in) / Zhang, Xiaolong (Autor:in) / Wen, Tuopu (Autor:in) / Yang, Mengmeng (Autor:in) / Jiang, Kun (Autor:in) / Yang, Diange (Autor:in)


    Erscheinungsdatum :

    19.09.2021


    Format / Umfang :

    3100180 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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