摘要
针对现有的激光里程计在面临室外大场景建图时,普遍会出现定位精度低、鲁棒性差的问题,提出一种16线激光雷达和惯性测量单元(inertial measurement unit, IMU)紧耦合的同时定位与建图(simultaneous localization and mapping, SLAM)算法。首先,对IMU进行估计位姿,通过线性插值矫正激光点云的运动畸变;其次,通过曲率提取场景特征,并根据不同特征性质进行分类;再次,利用帧间匹配模块在滑动窗口内构建局部地图;最后,利用帧与局部地图匹配得到的距离和IMU数据构建联合优化函数。借助KITTI数据集和自行录制的园区数据集,对改进算法与主流的Lego-LOAM和同样使用紧耦合方案的LIO-Mapping进行分模块和整个系统的精度评定。实测结果表明,在符合里程计实时性的要求下,改进激光里程计精度高于Lego-LOAM和LIO-Mapping方案。
Aiming at the problems of low precision location and poor robustness of the existing laser odometer in the outdoor scene mapping.A 16 wire LiDAR and inertial measurement unit(IMU)tightly coupled simultaneous localization and mapping(SLAM)algorithm was proposed.Firstly,the IMU was estimated,and the motion distortion of the laser point cloud was corrected by linear interpolation.Secondly,scene features were extracted by curvature and classified according to different feature properties.Thirdly,the local map was constructed in the sliding window by using the inter frame matching module.Finally,the joint optimization function was constructed by using the distance and IMU data obtained by matching the frame with the local map.By using the KITTI dataset and self-recorded datasets,accuracy evaluation was performed using the improved algorithm Lego-LOAM and tightly coupling scheme LIO-Mapping.The experimental result show that the laser odometer precision location is better than Lego-LOAM scheme and LIO-Mapping under the odometer real-time.
作者
刘振宇
惠泽宇
郭旭
李刚
LIU Zhen-yu;HUI Ze-yu;GUO Xu;LI Gang(School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,China;SIASUN Robot&Automation CO.,Ltd.,Shenyang 110169,China)
出处
《科学技术与工程》
北大核心
2022年第21期9167-9175,共9页
Science Technology and Engineering
基金
山东省重大科技创新工程项目(2019JZZY010128)
辽宁省自然科学基金(20180520022)。
