This paper presents a novel extrinsic calibration algorithm between a binocular stereo vision system and a 2D LIDAR (laser range finder). Extrinsic calibration of these heterogeneous sensors is required to fuse information obtained separately by vision sensor and LIDAR in the context of intelligent vehicle. By placing a planar chessboard at different positions and orientations in front of the sensors, the proposed method solves the problem based on 3D reconstruction of the chessboard and geometric constraints between views from the stereovision system and the LIDAR. The three principle steps of the approach are: 3D corner points triangulation, 3D plane least-squares estimation, solving extrinsic parameters by applying a non-linear optimization algorithm based on the geometric constraints. To evaluate the performance of the algorithm, experiments based on computer simulation and real data are performed. The proposed approach is also compared with a popular calibration method to show its advantages.
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