To improve the point cloud quality of the 3D laser input point cloud algorithm framework and reduce the impact of moving objects on the accuracy of the point cloud map,a method that removed dynamic objects in real time based on environmen-tal characteristics at the front end of the framework was proposed.The point cloud was projected to obtain the depth matrix and z-value matrix,and the environmental features were extracted from the z-value matrix.Environmental features were used to quickly align the front and rear frame point clouds.Taking the dynamic point cloud as the center,the depth matrix was used for clustering,and the unlabeled point cloud obtained by clustering was labeled and the marked point cloud was discarded when it was passed to the backend.The effectiveness of the method is verified on the Ours dataset and the KITTI dataset respectively.
关键词
实时/环境特征/高度矩阵/深度矩阵/对齐前后帧/聚类/差分矩阵
Key words
real-time/environmental features/height matrix/range matrix/align the front and rear frames/clustering/diffe-rence matrix
维普
万方数据