无人驾驶扫地机道路可行驶区域的融合提取研究  

Fusion extraction of road drivable areas for unmanned sweepers

作　　者：李思纯 王建军[1] 宋伟润 陈波 王文心 Li Sichun;Wang Jianjun;Song Weirun;Chen Bo;Wang Wenxin(School of Mechanical Engineering,Shandong University of Technology,Zibo 255049,China)

机构地区：[1]山东理工大学机械工程学院,淄博255049

出　　处：《仪器仪表学报》2024年第12期190-200,共11页Chinese Journal of Scientific Instrument

基　　金：山东省自然科学基金项目(ZR2023MF046);山东省创新型中小企业能力提升工程项目(2022TSGC2278);淄博市重点研发项目(2021SNCG0053);张店区校城融合项目(2021JSCG0020)资助。

摘　　要：真实有效的检测出道路可行驶区域,对无人驾驶扫地机路径规划、实时导航和避障至关重要。采用三维激光雷达获得道路环境点云后,首先采用改进的地面分割算法,分割出地面和非地面点云。然后,对于结构化道路,根据点云几何特征判断道路边界候选点和障碍物,采用随机抽样一致性与最小二乘法相结合,提取了路牙石边界线及排除出路面上障碍物的隔离线;对于非结构化道路,采用激光反射率聚类处理提取出道路面,通过滑动窗口法判断出边界点并采用B样条曲线提取出边界。继而,通过距离判据融合上述两种算法所获得的边界线,得到道路可行驶区域。最后,采用无人驾驶实验系统进行了可行驶区域提取实验。结果表明,所提出的融合算法在混合道路上的可行驶区域提取精确率和召回率分别为96.5%和92.7%,平均处理时间仅为29 ms,对道路宽度测量准确率可达97.1%,证明该融合算法具有高精度和高效性。Real and effective detection of the drivable area of roads is crucial for the path planning,real-time navigation,and obstacle avoidance of unmanned sweeping machines.After obtaining the laser point cloud of the road environment using 3D LiDAR,an improved ground segmentation algorithm is first used to segment the ground point cloud and non-ground point cloud.Then,for structured roads,candidate road boundary points and obstacles are determined based on the geometric features of the point cloud.The random sampling consistency algorithm is combined with the least squares method to extract the curb boundary lines and the isolation lines that remove obstacles on the road surface;For unstructured roads,laser reflectivity clustering is used to extract the road surface,and the sliding window method is used to determine the boundary points and extract the boundary curves using B-spline.In turn,by integrating the boundary lines obtained from the two algorithms using distance criteria,the drivable area of the road is obtained.Finally,an unmanned driving experimental system is used to extract drivable areas.The experimental results show that the fusion algorithm proposed has an accuracy of 96.5%and a recall rate of 92.7%for extracting the drivable area of laser point cloud data on mixed roads,with an average processing time of only 29 milliseconds.The accuracy of measuring the width of the real drivable area can reach 97.1%,proving that the road drivable area fusion algorithm has high accuracy and efficiency.Real and effective detection of the drivable area on roads is essential for the path planning,real-time navigation,and obstacle avoidance of unmanned sweeping machines.After obtaining the laser point cloud of the road environment using 3D LiDAR,an improved ground segmentation algorithm is first used to segment the ground and non-ground point cloud.Then,for structured roads,candidate road boundary points and obstacles are determined based on the geometric features of the point cloud.The random sampling consistency algorith

关 键 词：三维激光雷达 道路提取 点云反射强度 可行驶区域检测 全覆盖路径规划 

分 类 号：TH86[机械工程—仪器科学与技术] TP242[机械工程—精密仪器及机械]