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3D scene reconstruction and digitalization without occlusions serves as an essential task for robots to work in complex indoor environment. To meet the demand of dealing with complex computation caused by large-scale environment, a fast voxelization algorithm is proposed for indoor environment modeling and reconstruction. This algorithm can automatically search partition strategy which divides the 3D range data into unified blocks represented as voxels. Compared with the octrees, the proposed algorithm is much faster and easier to be applied in multiple scans registration and reconstruction, which can reduce the computational cost significantly. Since the 26-neighborhood and parent-child models are constructed in the proposed voxelization algorithm, it makes large-scale environment digitalization much easier to be accomplished in a more efficient way. The experiment results show that the algorithm is effective for large-scale scene reconstruction.