LP-DSG: A LiDAR Point-Based Docking Spot Generation System for Unmanned Surface Vehicles in Berthing Environments

Abstract

We propose a LiDAR point-based docking spot generation system for autonomous docking using point clouds from a low-density LiDAR sensor in berthing environments. The system consists of four key stages: scan matching, 3D object detection, long-term object perception, and docking spot generation. Scan matching estimates the unmanned surface vehicle's position within the global coordinate system using scan-to-map matching. In the 3D object detection stage, high-quality point clouds are generated from low-density LiDAR data to enhance detection performance, and detected object information is transformed into the global coordinate system. In the long-term object perception stage, object information beyond the LiDAR's field of view is stored on the map for continuous environmental perception. Finally, the docking spot generation stage employs an algorithm to generate valid docking spots. Experimental validation in real-world environments demonstrates that the proposed system achieves an average 3D mAP improvement of 23.38 percentage points across multiple detection architectures. Notably, for small object detection, the average 3D AP improvement reaches 38.12 percentage points, demonstrating significant effectiveness in challenging scenarios. These improvements enhance long-term perception, object management, and docking spot generation stability.