Triangular mesh construction based on point cloud matrix and edge feature extraction

Abstract

This paper builds a 3D laser scanner by a one-dimensional pitching rotation pan-tilt and a 2D laser range finder to get the 3D laser point cloud data from the motion environment. Depends on this data, a triangular mesh construction algorithm based on the point cloud matrix is proposed to construct the triangular mesh of the motion environment. Then a triangular plane normal vector clustering algorithm is used to extract the edge feature from the triangular mesh and the mean square deviation is employed as further process to make the edge feature more accurately. The experiment results show that the triangular mesh of motion environment can be constructed effectively and edge feature can be exacted accurately by the algorithms applied above. It lays the foundation of mobile robot autonomous movement in unknown complex environments.