《计算机应用研究》|Application Research of Computers

基于IMU紧耦合的LeGO-LOAM改进算法研究

Research on improved LeGO-LOAM algorithm based on IMU tight coupling

免费全文下载 (已被下载 次)  
获取PDF全文
作者 陈文浩,刘辉席,杨林涛,刘守印
机构 华中师范大学 物理科学与技术学院,武汉 430070
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2021)04-009-1013-04
DOI 10.19734/j.issn.1001-3695.2020.02.0097
摘要 基于LiDAR和SLAM (simultaneous localization and mapping)的LeGO-LOAM算法在低分辨率的LiDAR设备上,由于LiDAR数据的运动畸变、采样的地面数据稀疏等问题,存在重力矢量漂移现象和严重的高程估计误差。为了改善这一点,LeGO-LOAM改进算法引入了一种LiDAR和IMU(inertial measurement unit)紧耦合的方式。通过IMU估计运动状态,消除LiDAR数据的运动畸变,并使用IMU数据构建联合优化函数,约束位置姿态估计的重力方向。实验结果表明,这种方法有效抑制了LeGO-LOAM算法的重力矢量漂移,高程估计精度和高速状态下的定位精度均有显著提升。
关键词 实时实位与地图重建; LiDAR; IMU紧耦合; LeGO-LOAM
基金项目 中央高校基本科研业务费资助项目(CCNU19CG006)
本文URL http://www.arocmag.com/article/01-2021-04-009.html
英文标题 Research on improved LeGO-LOAM algorithm based on IMU tight coupling
作者英文名 Chen Wenhao, Liu Huixi, Yang Lintao, Liu Shouyin
机构英文名 College of Physical Science & Technology,Central China Normal University,Wuhan 430070,China
英文摘要 LeGO-LOAM algorithm based on LiDAR and SLAM on low-resolution LiDAR devices, due to problems such as motion distortion of the LiDAR data and sparse sampled ground data, there are gravity vector drift phenomena and serious elevation estimation errors. In order to improve this, the improved LeGO-LOAM algorithm introduced a way of tight coupling of LiDAR and IMU. It estimated the motion state through IMU, eliminated the motion distortion of LiDAR data, and constructed the joint optimization function using IMU data to constrain the direction of gravity for position and attitude estimation. The experimental results show that this method effectively suppresses the gravity vector drift of the LeGO-LOAM algorithm, and the accuracy of elevation estimation and positioning accuracy at high speeds are significantly improved.
英文关键词 SLAM; LiDAR; IMU tight coupling; LeGO-LOAM
参考文献 查看稿件参考文献
 
收稿日期 2020/2/9
修回日期 2020/3/30
页码 1013-1016
中图分类号 TP242
文献标志码 A