冯绍权,花向红,段成文,刘程,吴伟

• 1:武汉大学测绘学院
• 2:武汉大学灾害监测和防治研究中心
• 3:武汉环宇智行科技有限公司

摘要(Abstract)：

针对城市道路斜坡地形场景中地面欠分割或过分割的问题,提出了一种自适应的激光雷达地面分割算法。首先将激光点云按照水平角度分辨率进行有序组织,然后求取同一水平角度下前后扫描圈间激光点云的距离和局部坡度,最后采用自适应水平距离、局部高度和全局高度阈值区分地面点和非地面点。结合40线激光雷达进行多场景实例分析,结果表明本文算法分割的准确率更高,处理每帧数据均用时约1 ms,满足无人驾驶汽车的实时性需求。提出了一种自适应的激光雷达地面分割算法,实现了对激光雷达地面点云的准确分割。

关键词(KeyWords)： 斜坡地形;激光雷达;地面分割;自适应阈值;实时性

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目（41674005,41871373）;; 武汉大学地球空间环境与大地测量教育部重点实验室开放基金资助项目（18-01-02）

作者(Author): 冯绍权,花向红,段成文,刘程,吴伟

DOI: 10.16251/j.cnki.1009-2307.2021.01.021

参考文献(References)：

• [1] NARKSRI P,TAKEUCHI E,NINOMIYA Y,et al.A slope-robust cascaded ground segmentation in 3D point cloud for autonomous vehicles[C]//2018 21st International Conference on Intelligent Transportation Systems (ITSC).[S.l.]:IEEE,2018:497-504.
• [2] 朱株,刘济林.基于马尔科夫随机场的三维激光雷达路面实时分割[J].浙江大学学报(工学版),2015,49(3):464-469.(ZHU Zhu,LIU Jinlin.Real-time Markov random field based ground segmentation of 3D LiDAR data[J].Journal of Zhejiang University(Engineering Science),2015,49(3):464-469.)
• [3] 张银,任国全,程子阳,等.三维激光雷达在无人车环境感知中的应用研究[J].激光与光电子学进展,2019,56(13):9-19.(ZHANG Yin,REN Guoquan,CHEN Ziyang,et al.Application research of there-dimensional LiDAR in unmanned vehicle environment perception[J].Laser & Optoelectronics Progress,2019,56(13):9-19.)
• [4] HIMMELSBACH M,HUNDELSHAUSEN F V,WUENSCHE H J.Fast segmentation of 3D point clouds for ground vehicles[C]//2010 IEEE Intelligent Vehicles Symposium.[S.l.]:IEEE,2010.
• [5] GOLOMBEK Y,MARSHALL W E.Use of aerial LiDAR in measuring streetscape and street trees[J].Transportation Research Record,2019,2673(4):125-135.
• [6] BEKEY G A.Springer handbook of robotics[M].Robotics and Automation Magazine.[S.l.]:Springer,2008:110.
• [7] ASVADI A,PEIXOTO P,NUNES U.Detection and tracking of moving objects using 2.5D motion grids[C]∥IEEE International Conference on Intelligent Transportation Systems.[S.l.]:IEEE,2015.
• [8] SEBASTIAN T,MIKE M,HENDRIK D,et al.Stanley:The robot that won the DARPA grand challenge[J].Journal of Fiels Robotics,2004,23(9):661-692.
• [9] THRUN S,MONTEMERLO M,DAHLKAMP H,et al.Stanley:the robot that won the DARPA grand challenge[J].Journal of Field Robotics,2009,23(9):661-692.
• [10] Motion field estimation for a dynamic scene using a 3D LiDAR[J].Sensors,2014,14(9):16672-16691.
• [11] BIOSCA J M,JOSé LUIS LERMA.Unsupervised robust planar segmentation of terrestrial laser scanner point clouds based on fuzzy clustering methods[J].ISPRS Journal of Photogrammetry & Remote Sensing,2008,63(1):84-98.
• [12] ZERMAS D,IZZAT I,PAPANIKOLOPOULOS N.Fast segmentation of 3D point clouds:a paradigm on LiDAR data for autonomous vehicle applications[C]//International Conference on Robotics and Automation.[S.l.]:IEEE,2017.
• [13] ASVADI A,PREMEBIDA C,PEIXOTO P,et al.3D LiDAR-based static and moving obstacle detection in driving environments[J].Robotics & Autonomous Systems,2016,83(C):299-311.
• [14] NARKSRI P,TAKEUCHI E,NINOMIYA Y,et al.A slope-robust cascaded ground segmentation in 3D point cloud for autonomous vehicles[C]//2018 21st International Conference on Intelligent Transportation Systems (ITSC).[S.l.]:IEEE,2018:497-504.
• [15] 张名芳,付锐,郭应时,等.基于三维不规则点云的地面分割算法[J].吉林大学学报(工学版),2017,47(5):1387-1394.(ZHANG Mingfang,FU Rui,GUO Yingshi,et al.Road segmentation method based on irregular three dimensional point cloud[J].Journal of Jilin University(Engineering and Technology Edition),2017,47(5):1387-1394.)