A Robust Method of Fitting Cylindrical Surface with Laser Point Cloud
Aiming at the problem of data fitting of complete and partial cylindrical point cloud and the robustness of cylin-drical fitting results in 3D modeling application of Laser point cloud,a robust spatial cylindrical fitting method is proposed. Firstly,the random sample consensus (RANSAC) algorithm is used to fit the line and circle,and the initial values of the cylinder model parameters are determined,Then the RANSAC algorithm is combined with the least squares meth-od to fit the spatial cylinder surface. Simulation experiments were performed to test the cylindrical point clouds containing various horizontal noises with 100％,50％ and 25％ cylindri-cal integrity,and the maximum error between the fitted cylin-drical radius and the real radius was 0.2mm. The results show that,compared with the traditional RANSAC method and the least squares method,the proposed method not only has very high fitting accuracy,but also has high robustness to data integrity and noise.
laser point cloudcylindrical fittingRANSAC algorithmLSrobustness
万方数据
维普
