A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environments

TL;DR

This paper introduces Quatro, a robust global registration method for 3D point clouds in urban environments that reduces degeneracy issues by leveraging the Atlanta world assumption, improving accuracy in localization tasks.

Contribution

The paper proposes Quatro, a degeneracy-robust global registration method that employs quasi-SO(3) estimation to avoid degeneracy in rotation estimation in urban 3D point cloud registration.

Findings

Outperforms existing methods in robustness and accuracy

Effective in indoor and outdoor LiDAR datasets

Suitable for coarse alignment in localization tasks

Abstract

Global registration using 3D point clouds is a crucial technology for mobile platforms to achieve localization or manage loop-closing situations. In recent years, numerous researchers have proposed global registration methods to address a large number of outlier correspondences. Unfortunately, the degeneracy problem, which represents the phenomenon in which the number of estimated inliers becomes lower than three, is still potentially inevitable. To tackle the problem, a degeneracy-robust decoupling-based global registration method is proposed, called Quatro. In particular, our method employs quasi-SO(3) estimation by leveraging the Atlanta world assumption in urban environments to avoid degeneracy in rotation estimation. Thus, the minimum degree of freedom (DoF) of our method is reduced from three to one. As verified in indoor and outdoor 3D LiDAR datasets, our proposed method yields robust global registration performance compared with other global registration methods, even for distant point cloud pairs. Furthermore, the experimental results confirm the applicability of our method as a coarse alignment. Our code is available: https://github.com/url-kaist/quatro.