Aiming at the problems of high density, long reconstruction time and low reconstruction efficiency for scattered point cloud data, a new uniform simplification algorithm for scattered point cloud data is proposed. This algorithm is based on the open-source C++ programming library point cloud library (PCL). Firstly, a K-nearest neighborhood voxel grid is built by voxel grid class in PCL. Next, according to the bounding box algorithm the K-nearest neighborhood distance of the point cloud data is calculated and the normal of the point cloud data is estimated. Then the barycenter of each small voxel grid is established, which replaces all point cloud data in the voxel grid to achieve point cloud simplification. Finally, the simplified point cloud data is reconstructed and displayed with triangular mesh by greedy projection triangulation class. The experimental results show that in the premise of fully retaining geometric characteristics of point cloud data, the proposed algorithm can effectively remove partial redundancy of the point cloud data and simplify the data uniformly without large-scale blank area, and the reconstruction efficiency is improved.