基于LiDAR扫描角度修正的障碍目标定位方法  

Obstacle Target Positioning Based on LiDAR Scanning Angle Correction

作　　者：张铭坤 蔡文郁[1] 张帅 ZHANG Mingkun;CAI Wenyu;ZHANG Shuai(School of Electronics and Information,Hangzhou Dianzi University,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学电子信息学院,浙江杭州310018

出　　处：《电子科技》2024年第1期41-47,共7页Electronic Science and Technology

基　　金：浙江省自然科学基金(LZ22F010004,LZJWY22E090001);浙江省属高校基本科研业务费专项资金(GK209907299001-001);浙江省教育厅一般科研项目(Y202146775)。

摘　　要：在二维激光雷达(LiDAR)用于障碍物检测时,移动机器人自身姿态变化导致LiDAR基准位置变化,对障碍目标进行定位计算时会产生较大误差。文中提出了一种基于LiDAR扫描角度修正的障碍目标定位方法,用K-means聚类算法对激光雷达点云数据进行聚类划分,然后对聚类后数据进行角度修正处理,使处理后的数据信息更符合真实值。最后包络每个聚类数据,从而提高LiDAR扫描数据的准确性。测试结果表明,文中所提方法能够提高定位精度,满足障碍物精准定位的需求。When two-dimensional Laser Radar(LiDAR)is used for obstacle detection,the position change of mobile robot′s own attitude usually leads to the change of LiDAR reference position,which will produce a large error in the positioning calculation of obstacle.In this study,an obstacle target location method based on LiDAR scanning angle correction is proposed.The K-means clustering algorithm is used to divide the LiDAR point cloud data,and then the angle correction processing is performed on the clustered data,so that the processed data information is more consistent with the real value.Finally,each cluster data is enveloped to improve the accuracy of LiDAR scanning data.The test results show that the the proposed method can improve the positioning accuracy and meet the requirement of accurate obstacle positioning.

关 键 词：二维激光雷达 移动机器人 姿态变化 基准位置 聚类划分 角度修正 障碍目标定位 准确性 

分 类 号：TN401[电子电信—微电子学与固体电子学]