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.
翻译:对于大多数LiDAR-肾上腺测量,准确的初始状态,包括LiDAR和6-Axis IMUs之间的时间偏移和外部变异,可以发挥重要作用,而且往往被视为先决条件。然而,这种信息不一定总能在定制的LiDAR-肾上腺系统中提供。在本文件中,我们建议Li-Init:一个完整和实时的LiDAR-肾上腺系统初始化进程,该程序将LIDAR和IMUs之间的时间偏差和外部参数校准,以及重力矢量和IMU偏差,其方法是将LIDAR测量结果的状态估计数与IMU测量结果相匹配。我们将拟议方法作为初始化模块,如果启用,将自动检测所收集数据和校准的程度,即实时、时间偏移、极限、重力矢量矢量和IMU偏差,然后作为实时的开放度初始值初始状态值,然后用不同类型LDAR-AAR测量结果的测测测测测结果,然后用不同类型对LDAR系统进行实验,在我们的IDAR-AR-A-R-A的初始性测试程序上,也显示我们IAR-IAR-A-IAR-ID-ID-ID-ID-ID-ID-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-A-A-I-A-A-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I-I