Research on Fitting Algorithm of Scattered Point Cloud Based on 3D Laser Scanning

Abstract

3D laser scanning equipment is an important equipment for reverse engineering. It is used as an information sensing device for the Industrial IoT. After analyzing and processing the measured data, it can issue construction instructions to equipment such as TBMs and shotcrete manipulator. It can be used to solve the problems of initial support contour detection, flatness detection, monitoring measurement, and so on in tunnel engineering. This paper considers that 3D laser scanning point cloud is a scattered point cloud and cannot be used directly. In order to extract the point cloud information as much as possible, it is necessary to fit the point cloud obtained by scanning first. This paper uses the triangulation method, the Poisson reconstruction method, and the Lagrange method, etc. to fit the scattered point cloud, analyzes the advantages and disadvantages of several fitting methods, and analyzes the accuracy of the surfaces generated by several fitting methods. This creates conditions for the subsequent utilization of the tunnel 3D laser scanning point cloud.