论文标题
一种基于优化的IMU/LIDAR/摄像机共校准方法
An optimization-based IMU/Lidar/Camera Co-calibration method
论文作者
论文摘要
最近，多传感器融合已在自动化领域取得了重大进展，以提高导航和位置性能。作为融合算法的先决条件，对多传感器的外在校准的需求正在增长。为了计算外部参数，许多研究专门用于两步方法，该方法将各个校准成对整合。由于失去了所有传感器的约束，因此效率低下且无效。关于减轻此负担，本文中提出了一种基于优化的IMU/LIDAR/摄像机共校准方法。首先，分别进行了IMU/相机和IMU/LIDAR在线校准。然后，棋盘中的角和表面特征点与粗糙的结果相关联，并构建了相机/激光镜头的约束。最后，构建共校准优化以完善所有外部参数。我们在模拟中评估了所提出的方案的性能，结果表明我们所提出的方法的表现优于两步方法。
Recently, multi-sensors fusion has achieved significant progress in the field of automobility to improve navigation and position performance. As the prerequisite of the fusion algorithm, the demand for the extrinsic calibration of multi-sensors is growing. To calculate the extrinsic parameter, many researches have been dedicated to the two-step method, which integrates the respective calibration in pairs. It is inefficient and incompact because of losing sight of the constrain of all sensors. With regard to remove this burden, an optimization-based IMU/Lidar/Camera co-calibration method is proposed in the paper. Firstly, the IMU/camera and IMU/lidar online calibrations are conducted, respectively. Then, the corner and surface feature points in the chessboard are associated with the coarse result and the camera/lidar constraint is constructed. Finally, construct the co-calibration optimization to refine all extrinsic parameters. We evaluate the performance of the proposed scheme in simulation and the result demonstrates that our proposed method outperforms the two-step method.
