Xiangcheng Hu1 · Xieyuanli Chen2 · Mingkai Jia1 ·
Jin Wu 3*
Ping Tan1· Steven L. Waslander4†
1HKUST 2NUDT 3USTB 4U of T
†Project lead *Corresponding author
DCReg (Decoupled Characterization for ill-conditioned Registration) is a principled framework that addresses ill-conditioned point cloud registration problems, achieving 20% - 50% accuracy improvement and 5-100 times speedup over state-of-the-art methods.
- Reliable ill-conditioning detection: Decouples rotation and translation via Schur complement decomposition for ill-conditioning detection,eliminating coupling effects that mask degeneracy patterns.
- Quantitative characterization: Maps mathematical eigenspace to physical motion space, revealing which and to what extent specific motions lack constraints
- Targeted mitigation: Employs targeted preconditioning that stabilizes only degenerate directions while preserving observable information.
DCReg seamlessly integrates with existing registration pipelines through an efficient PCG solver with a single interpretable parameter.
2025/09/09: the preprint paper is online, baseline codes will be published first!
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For referencing our work, please use:
@misc{hu2025dcreg,
title={DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration},
author={Xiangcheng Hu and Xieyuanli Chen and Mingkai Jia and Jin Wu and Ping Tan and Steven L. Waslander},
year={2025},
eprint={2509.06285},
archivePrefix={arXiv},
primaryClass={cs.RO},
url={https://arxiv.org/abs/2509.06285},
}
The authors gratefully acknowledge the valuable contributions that made this work possible.
- We extend special thanks to Dr. Binqian Jiang and Dr. Jianhao Jiao for their insightful discussions that significantly contributed to refining the theoretical framework presented in this paper.
- We also appreciate Mr. Turcan Tuna for his technical assistance with the baseline algorithm implementation.

































