A Symmetry-Based Method for LiDAR Point Registration

LiDAR point registration is a key procedure for the acquisition of complete point cloud datasets. It has great significance for the fusion of multisource LiDAR data. In general, the widely used methods for LiDAR point registration can be categorized into three types: auxiliary methods, direct methods, and feature methods. However, for the registration of complex objects (e.g., stadium and tower), such methods may face varying degrees of technical problems owing to the unavailability of auxiliary data or targets, requirement of sufficient overlapping areas, and difficulty in feature extraction and matching. In the real world, numerous objects with extremely complicated geometric shapes have the characteristic of symmetry. This study focuses on complex objects with symmetry and tries to exploit their intrinsic symmetry characteristic in order to facilitate their point cloud registration. A symmetry-based method for LiDAR point registration is proposed, in which the general idea is to derive 3-D central axes from multisource point clouds, based on the symmetry of objects. The proposed method consists of six main steps: detection of rotational symmetry, adaptive point cloud slicing, central point extraction, central axis fitting, central axis matching, and orientation and positioning. Comparative experiments and quantitative evaluations are conducted. The experimental results indicate that the proposed framework can achieve satisfactory registration of objects with rotational symmetry.