Mapping and ground segmentation method based on backpack type laser radar system

Abstract

The invention discloses a mapping and ground segmentation method based on a backpack type laser radar system. The method comprises the following steps: acquiring first point cloud data of a plurality of laser radars; performing space-time calibration on the first point cloud data of each laser radar to obtain space-time calibration data, wherein the space-time calibration is used for representing calibration of the time dimension and the space dimension of the point cloud data; and extracting a feature point set of the space-time calibration data, and performing point cloud registration on the feature point set to obtain a reconstructed map, wherein the feature point set comprises a first surface feature point set, a first angle feature point set and an edge feature point set. According to the embodiment of the invention, time and space calibration is carried out on the point cloud data of the plurality of laser radars to realize point cloud merging, and then the surface feature point set, the angle feature point set and the edge feature point set of the time and space calibration data are extracted, so that the subsequent point cloud registration precision can be improved, and meanwhile, the ground points can be rapidly extracted. 本发明公开了一种基于背包式激光雷达系统的建图和地面分割方法，所述方法包括：获取若干激光雷达的第一点云数据；对每一个激光雷达的所述第一点云数据进行时空标定，得到时空标定数据；其中，所述时空标定用于表征对点云数据的时间维度和空间维度的标定；提取所述时空标定数据的特征点集，并对所述特征点集进行点云配准，得到重建的地图；其中，所述特征点集包括第一面特征点集、第一角特征点集和边特征点集。本发明实施例通过对若干激光雷达的点云数据进行时间和空间的标定实现点云合并，然后提取所述时空标定数据的面特征点集、角特征点集和边特征点集，能提高的后续点云配准精度，同时实现快速提取地面点。