数据采集与处理2025，Vol.40Issue(5)：1294-1305,12.DOI:10.16337/j.1004-9037.2025.05.015
基于三级去畸变和分层降采样机制的F-LOAM改进算法
Improved F-LOAM Algorithm Based on Three-Stage De-distortion and Hierarchical Downsampling Mechanism
摘要
Abstract
The traditional fast LiDAR odometry and mapping(F-LOAM)algorithm performs a two-stage de-distortion process on the feature points,but only the first stage de-distorts the feature points,and the second-stage de-distortion is used for building the map,which leads to the lack of accuracy in the bit-position estimation.In order to solve this problem,this paper proposes an improved three-stage de-distortion mechanism combined with a voxelized grid-based hierarchical downsampling mechanism to improve the real-time performance of the algorithm.The improved F-LOAM algorithm shows excellent test results on the KITTI dataset.The three-stage de-distortion mechanism and the hierarchical downsampling strategy not only reduce the computational burden effectively,but also ensure the validity of feature points and the accuracy of the global map.关键词
快速激光雷达里程计与建图算法/激光雷达/运动畸变/匀速模型/去畸变/分层降采样Key words
fast LiDAR odometry and mapping(F-LOAM)/LiDAR/motion distortion/constant velocity model/de-distortion/hierarchical downsampling分类
信息技术与安全科学引用本文复制引用
徐鹤,张阔,李鹏..基于三级去畸变和分层降采样机制的F-LOAM改进算法[J].数据采集与处理,2025,40(5):1294-1305,12.基金项目
国家重点研发计划(2019YFB2103003)资助项目. （2019YFB2103003）
