Abstract: To achieve real-time monitoring of container ship mooring and loading/unloading operations, ensuring operational safety and enhancing efficiency, we introduce the near-neighbor point cloud center of gravity sampling algorithm, the warp/latitude scanning boundary extracting algorithm based on the distance threshold, and the attitude angle algorithm of container ship. Additionally, we construct a simulation scene model and establish a dataset of motion point clouds for moored container ships to validate the effectiveness of these algorithms. Comparison between calculated and actual values from simulated data collected by radars with varying line counts demonstrates the algorithm's accurate reconstruction of the ship's motion history. The measurement error for transverse/vertical rocking inclination is less than 0.2°, and the algorithm's sensitivity to point cloud density within the effective range is negligible. This initial validation confirms the algorithm's effectiveness and feasibility, offering data support for real-time monitoring and early warning systems for container ship buoyancy and stability.

Key words: LiDAR, point cloud processing, attitude monitoring, mooring ship