退化环境下LiDAR里程计定位方法  

LiDAR Odometry Positioning Method for Degenerate Environment

作　　者：徐爱功[1] 高佳鑫 隋心[1] 王长强[1] 史政旭 XU Aigong;GAO Jiaxin;SUI Xin;WANG Changqiang;SHI Zhengxu(School of Geomatics,Liaoning Technical University,Fuxin 123000,China)

机构地区：[1]辽宁工程技术大学测绘与地理科学学院,阜新123000

出　　处：《地球信息科学学报》2024年第10期2316-2334,共19页Journal of Geo-information Science

基　　金：国家自然科学基金项目(42074012);辽宁省“兴辽英才计划”项目(XLYC2002101、XLYC2008034)。

摘　　要：针对基于常见点云帧间配准算法所构建的传统LiDAR里程计在退化环境中定位鲁棒性差的问题,本文借助修正后的激光强度提出了一种面向退化环境的LiDAR里程计定位方法,并提出了一种准确的LiDAR退化环境检测方法。首先,基于激光强度性质和消元思想提出一种强度修正方法,并采用无监督位置修正方法共同优化原始点云。以此为基础,提取4种点云特征并采用模糊综合评价方法准确地检测每帧点云的退化情况。针对非退化点云,提取线、面特征构建兴趣点集合;针对退化点云,借助激光强度并提出一种“米字搜索”方法提取非退化特征,同有效的线、面特征构建兴趣点集合。最后,通过合适的配准算法处理帧间兴趣点集合,从而构建鲁棒的LiDAR里程计。实验结果表明,本文方法修正激光强度的正确率为93.34%;LiDAR退化点云正确检测率为98.58%,非退化点云错误检测率仅为2.24%;本文提出的LiDAR里程计定位方法相较于基于特征配准算法和ICP算法所构建的LiDAR里程计,定位均方根误差分别降低了90.00%、83.96%,最大误差分别降低了86.23%、79.07%,单次帧间配准所需时长为0.0069 s,有效地提高了退化环境中传统LiDAR里程计的定位精度,并兼顾了数据处理效率;相较于同领域的对比方法,本文方法展现出了更显著的优势。Simultaneous Localization and Mapping(SLAM)based on Light Detection and Ranging(LiDAR)is one of the core technologies widely used in the field of indoor and outdoor integrated positioning and spatial data acquisition.It has the advantage of strong anti-interference without considering light conditions.However,in degenerate environments lacking geometric features,the traditional LiDAR odometry based on feature registration algorithm or Iterative Closest Point(ICP)algorithm usually produce inaccurate results.To address the above problem,this paper proposes a LiDAR odometer positioning method for degenerate environments using modified laser intensity and an accurate LiDAR degenerate environment detection method.Firstly,an intensity correction method is proposed based on laser intensity properties and the elimination idea,and an unsupervised position correction method is used to jointly optimize the original point cloud.Based on this,four point cloud features are extracted,and the fuzzy comprehensive evaluation method is used to accurately detect the degradation of each frame point cloud.For well-conditioned point clouds,line and surface features are extracted to construct the interest point set.For degenerate point clouds,a"MI word search"method is proposed to extract well-conditioned features based on laser intensity,and the interest point set is constructed with effective line and surface features.Finally,the robust LiDAR odometry is constructed by processing the inter-frame interest point sets through suitable registration algorithms.The experimental results show that the correct rate of laser intensity correction is 93.34%.The correct detection rate of LiDAR degenerate point cloud is 98.58%,and the error detection rate of well-conditioned point cloud is only 2.24%.Compared with the LiDAR odometry based on feature registration algorithm and ICP algorithm,the positioning Root Mean Square Error(RMSE)of the LiDAR odometry positioning method proposed in this paper is reduced by 90.00%and 83.96%,respectively,and the M

关 键 词：LiDAR退化环境 LiDAR里程计 激光强度 模糊综合评价 LOAM ICP 特征配准 

分 类 号：TN958.98[电子电信—信号与信息处理]