Abstract: The driving environment of the intelligent vehicle is complex and diverse, which inevitably leads to the change of the relative pose of the sensors. Aiming to solving the problem of recalibration after the drift of camera or LiDAR equipped on the intelligent vehicle, the automatic recalibration method using sensor fusion odometry is proposed. First, based on the principle of point cloud projection and image registration, the 3D-2D point correspondences between the reference point cloud and the observed image are established, and the camera motion with inaccurate translation scale is estimated by the Perspective-n-Point method; Then, the accurate camera motion is recovered by fusing the estimated LiDAR motion, the reference point cloud is transformed to the observation position using the camera motion, and registrated with the observation point cloud, the final extrinsic parameter is obtained using the average filtering method. Finally, the real vehicle experiments are implemented in indoor and outdoor scenario on an intelligent vehicle. The results show that the proposed sensor fusion odometry based method does not need to set up the calibration board, and is unrestricted with the environment and data features. It is able to achieve accurate recalibration of camera and LiDAR, and has high robustness to sensor drift.

Key words: intelligent vehicle, camera and LiDAR, sensor drift, sensor fusion odometry, recalibration