论文标题
强大的实时激光惯性初始化
Robust Real-time LiDAR-inertial Initialization
论文作者
论文摘要
对于大多数激光惯性的探测器，精确的初始状态，包括LiDAR和6轴IMU之间的时间偏移和外在变化，起着重要作用，通常被视为先决条件。但是，在定制的激光惯性系统中可能不会始终获得此类信息。在本文中，我们提出了Li-Init：一个完整的实时激光惯性系统初始化过程，该过程校准了激光雷达和IMU之间的时间偏移和外部参数，以及通过与IMU测量的激光雷达测量结果对齐的重力矢量和IMU偏置。我们将提出的方法实施为初始化模块，如果启用了初始化模块，它将自动检测到收集的数据和校准的激发程度，即直接偏移，外部偏移，外部，重力矢量和IMU偏置，然后将其用作实时的LIDAR INSERTICE INSERTILERERTIAL ODARERERTIAL ODERETIAL ODEMOTIAL ODEMOTERY系统的高质量初始状态值。用不同类型的LIDARS和LIDAR惯性组合进行的实验表明我们初始化方法的鲁棒性，适应性和效率。我们的LIDAR惯性初始化过程LI-INIT和测试数据的实现在GitHub上开源，并集成到最先进的激光射击速度计算系统Fast-LiO2中。
For most LiDAR-inertial odometry, accurate initial states, including temporal offset and extrinsic transformation between LiDAR and 6-axis IMUs, play a significant role and are often considered as prerequisites. However, such information may not be always available in customized LiDAR-inertial systems. In this paper, we propose LI-Init: a full and real-time LiDAR-inertial system initialization process that calibrates the temporal offset and extrinsic parameter between LiDARs and IMUs, and also the gravity vector and IMU bias by aligning the state estimated from LiDAR measurements with that measured by IMU. We implement the proposed method as an initialization module, which, if enabled, automatically detects the degree of excitation of the collected data and calibrate, on-the-fly, the temporal offset, extrinsic, gravity vector, and IMU bias, which are then used as high-quality initial state values for real-time LiDAR-inertial odometry systems. Experiments conducted with different types of LiDARs and LiDAR-inertial combinations show the robustness, adaptability and efficiency of our initialization method. The implementation of our LiDAR-inertial initialization procedure LI-Init and test data are open-sourced on Github and also integrated into a state-of-the-art LiDAR-inertial odometry system FAST-LIO2.
