Line segment extraction algorithm of point cloud based on slope
In LiDAR simultaneous localization and mapping (SLAM ),whether the feature points are extracted accurately determines the precision of mapping and positioning in the whole system.Using curvature-based feature point registration cannot fully constrain the pose.Aiming at this problem,a slope-based point cloud preprocessing algorithm is proposed,which can quickly extract line segments(horizontal and vertical line segment)from point cloud.Firstly,the point cloud is serialized in the horizontal direction through the angle,and in the vertical direction through the laser channel number,and the invalid partitions are removed through the partition variance.Then,straight line segments are extracted in the horizontal and vertical directions,and the straight line categories are judged.Finally,the horizontal and vertical line segments are output.Analysis result of experimental data show that,compared with the previous Fast algorithm and Efficient algorithm,the processing speed is up to 150 Hz,and the registration effect is better than using the original point cloud directly.
ground and wall segmentationlaser point cloud pretreatmentfeature point extraction of point cloud
万方数据
维普
