Low-overlap point cloud registration algorithm based on variable-length least trimmed squares

Abstract

Point cloud registration is a key technology in point cloud processing, aiming to align two point clouds by estimating the optimal rigid transformation matrix. When the overlap rate of the point clouds to be registered is low, it is difficult for the existing point cloud registration algorithms to achieve satisfactory results. To achieve accurate registration of point clouds with low overlap rate, an ICP point cloud registration algorithm based on variable-length least trimmed squares (VLTS-ICP) is proposed, which enables the accurate registration of point clouds with low overlap rate by varying the truncated length of the LTS to make more pairs of ideal matching points be used in the current iteration for the estimation of pose transformation. It is verified that the VLTS-ICP algorithm has better accuracy and robustness, especially for low overlap point cloud registration, and its comprehensive performance is significantly better than ICP algorithm and TrICP algorithm.