关键词: 激光雷达惯性测量单元, 外参标定, 外点剔除, 退化运动, 固定外参

Abstract: Aiming at the problems that the degraded sensor data were difficult to calibrate external parameters when the vehicles were moving in an approximate plane, a highly robust two-stage LiDAR-IMU external parameters online calibration algorithm was proposed. The calibration algorithm included two stages: initial value calculation and online iterative optimization using nonlinear sliding window. In the first stage, the outliers in the pre-data set were eliminated, the hand-eye calibration model that contained only the rotation components was solved multiple times in the form of a sliding window, meanwhile, the conditions of the analytical solution screening were improved, the singular value decomposition（SVD） analytical solution of multiple weighted rotation external parameters was solved. The second stage minimized the residual function containing the external parameters, and used the rotational analytical solution as the initial value sliding window to iteratively optimize the six-degree-of-freedom external parameters, so that the external parameters converged quickly. In order to avoid the degradation of external parameters, when the degenerate motion and error history constraints were too large, the external parameters would be fixed. Compared with the original algorithm, the algorithm is robust to degraded sensor data, which may achieve accurate and robust online calibration of external parameters without the initial values of the external parameters.

Key words: laser detection and ranging-inertial measurement unit(LiDAR-IMU), external parameter calibration, outlier elimination, degraded motion judgment, fixed external parameter