YOCO: You Only Calibrate Once for Accurate Extrinsic Parameter in LiDAR-Camera Systems

X, X 2024 1 YOCO: Y ou Only Calibrate Once for Accurate Extrinsic Parameter in LiDAR-Camera Systems Tianle Zeng, Dengke He, Feifan Y an, Meixi He Abstract --In a multi-sensor fusion system composed of cameras and LiDAR, precise extrinsic calibration contributes to the system's long-term stability and accurate perception of the environment. However, methods based on extracting and registering corresponding points still face challenges in terms of automation and precision. This paper proposes a novel fully automatic extrinsic calibration method for LiDAR-camera systems that circumvents the need for corresponding point registration. In our approach, a novel algorithm to extract required LiDAR correspondence point is proposed. We avoid the need for corresponding point registration by introducing extrinsic parameters between the LiDAR and camera into the projection of extracted points and constructing co-planar constraints. These parameters are then optimized to solve for the extrinsic. In synthetic experiments, our method demonstrates superior performance compared to current calibration techniques. Real-world data experiments further confirm the precision and robustness of the proposed algorithm, with average rotation and translation calibration errors between LiDAR and camera of less than 0.05 and 0.015m, respectively. This method enables automatic and accurate extrinsic calibration in a single one step, emphasizing the potential of calibration algorithms beyond using corresponding point registration to enhance the automation and precision of LiDAR-camera system calibration. I NTRODUCTION S ENSOR fusion has been widely discussed in the robotics and computer vision fields. Dengke He is with the State Key Labortaory for Fine Exploration and Intelligent Development of Coal Resources, China University of Mining and Technology (Beijing), Beijing 100083, China, and also with the College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China (e-mail: he dengke@126.com). Feifan Y an is with the State Key Labortaory for Fine Exploration and Intelligent Development of Coal Resources, China University of Mining and Technology (Beijing), Beijing 100083, China, and also with the College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China (e-mail: yabiyff@163.com).