基于摆动单线激光雷达的大场景稠密点云地图创建系统

Swinging Single-Layer LiDAR Based Dense Point Cloud Map Reconstruction System for Large-Scale Scenes

在创建大场景稠密点云地图时,由于当前的各类环境3维测量系统难以兼顾大范围和高密度的点云测量要求,为此设计了一种基于摆动单线激光雷达的大场景稠密点云地图创建系统.首先,实现了大型激光雷达稳定精确的全向摆动.然后,给出了单点采集点云的拼接方法和多点采集点云的配准方法.最后,提出了一种3维点云投影密度的分析方法,并对仿真测量结果进行了对比与评价.实验结果表明,本系统的有效测量距离超过75m、测量范围覆盖俯仰±45°、点云间距小于20cm、点云分布均匀,装置的视野范围和点云分布可进行调节,并能通过多点配准对更大场景进行建图.

When creating dense point cloud maps for large-scale scenes, it's difficult for current 3D measurement systems to balance their measurement range and point cloud density. Therefore, a swinging single-layer LiDAR based dense point cloud map reconstruction system for large-scale scenes is designed. Firstly, the stable and accurate omnidirectional swing of a large LiDAR is realized. Then, the point cloud concatenation method at a single measuring point and the registration method at multiple measuring points are given. Finally, a density analysis method for projected 3D point cloud is proposed, and the simulation results are compared and evaluated. Experimental results show that the effective measurement distance of the system exceeds 75 m, the measurement range covers ±45° pitching angle, the point cloud spacing is less than 20 cm, and the point cloud distribution is uniform. Meanwhile, the view field and point cloud distribution of the device can be adjusted, and a larger scene can be reconstructed by point cloud registration at multiple measuring points.