Comparative Analysis of 3D Point Cloud Libraries with Focus on Efficiency and Practical Use

Point cloud processing is essential for modern robotics and three-dimensional mapping systems. This study investigates the computational efficiency of the Open3D, PyntCloud, and Trimesh libraries when handling point cloud data in PCD, PLY, and LAS formats. The approach evaluates usability, visualization, and algorithmic support under different computational demands. The results indicate that Open3D consistently outperforms the other libraries in terms of memory efficiency, execution time, and scalability across datasets of increasing size, while maintaining a simple and consistent Python interface. These characteristics make Open3D particularly effective for large-scale point cloud processing workflows.