一种融合惯性测量单元（IMU）和里程计的激光雷达（LiDAR）畸变校准方法。

A Method of Calibration for the Distortion of LiDAR Integrating IMU and Odometer.

作者信息

Wu Qiuxuan, Meng Qinyuan, Tian Yangyang, Zhou Zhongrong, Luo Cenfeng, Mao Wandeng, Zeng Pingliang, Zhang Botao, Luo Yanbin

机构信息

School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.

Electric Power Research Institute of State Grid Henan Electric Power Company, Zhengzhou 450018, China.

出版信息

Sensors (Basel). 2022 Sep 5;22(17):6716. doi: 10.3390/s22176716.

DOI:10.3390/s22176716

PMID:36081173

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9459914/

Abstract

To improve the motion distortion caused by LiDAR data at low and medium frame rates when moving, this paper proposes an improved algorithm for scanning matching of estimated velocity that combines an IMU and odometer. First, the information of the IMU and the odometer is fused, and the pose of the LiDAR is obtained using the linear interpolation method. The ICP method is used to scan and match the LiDAR data. The data fused by the IMU and the odometer provide the optimal initial value for the ICP. The estimated speed of the LiDAR is introduced as the termination condition of the ICP method iteration to realize the compensation of the LiDAR data. The experimental comparative analysis shows that the algorithm is better than the ICP algorithm and the VICP algorithm in matching accuracy.

摘要

为了改善移动时中低帧率下激光雷达数据引起的运动失真，本文提出了一种结合惯性测量单元（IMU）和里程计的估计速度扫描匹配改进算法。首先，融合IMU和里程计的信息，采用线性插值方法获得激光雷达的位姿。使用迭代最近点（ICP）方法对激光雷达数据进行扫描匹配。IMU和里程计融合的数据为ICP提供了最优初始值。引入激光雷达的估计速度作为ICP方法迭代的终止条件，以实现对激光雷达数据的补偿。实验对比分析表明，该算法在匹配精度上优于ICP算法和可变ICP（VICP）算法。