发表机构
Czech Technical University（捷克技术大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对3D LiDAR配准在退化场景下解不唯一的问题，提出基于李理论的LiLi方法，通过扰动优化解并利用se(3)生成元识别全部退化变换，显著降低配准误差并提升真实退化环境中的定位性能。
AI 中文摘要
本文研究了在具有退化性的挑战性场景中的3D LiDAR扫描配准问题，例如笔直走廊或平坦场地，在这些场景中配准解不唯一，从而损害定位和建图精度。现有的退化检测方法忽视了数据点重新关联的可能性，容易对噪声和复杂退化敏感。因此，我们提出了LiLi——一种利用李理论在刚体变换的SE(3)李群中识别全部退化变换集合的新方法。该方法对优化解施加扰动，并比较由此产生的优化位姿，以确保稳健地检测退化。通过利用李代数se(3)的生成元，该方法提供了一种系统性的方法来描述退化变换的集合。在合成数据上的定量评估显示，与最先进的基于Hessian的方法相比，该方法有显著改进，将配准误差降低了50%，并且在含有噪声的数据集上改进更为显著。在真实世界的退化数据集中，将所提出的方法集成到基于LiDAR的里程计中，在260米长的轨迹上，与基于Hessian的退化检测器的参考解决方案相比，产生了更优越的定位性能，并且在430米长的往返隧道轨迹上成功，而参考方法失败。
英文摘要
In this paper, we study 3D LiDAR scan alignment in challenging scenarios with degeneracies, such as straight corridors or flat fields, where the alignment solution is not unique and compromises localization and mapping accuracy. Existing degeneracy detection methods that neglect the potential for reassociating data points are prone to being sensitive to noise and complex degeneracies. Therefore, we propose LiLi - a novel method that leverages Lie theory to identify the full set of degenerate transformations within the SE(3) Lie group of rigid transformations. The method employs perturbations of the optimized solution and compares the resulting optimized poses to ensure robust detection of degeneracies. By leveraging generators from the Lie algebra se(3), the method provides a systematic approach to describing the set of degenerate transformations. Quantitative evaluations on synthetic data show significant improvement over the state-of-the-art Hessian-based method, reducing alignment error by 50%, with more significant improvements for datasets featuring noise. In the real-world degenerate datasets, the proposed method integrated into LiDAR-based odometry yields superior localization performance compared to the reference solution based on the Hessian-based degeneracy detector on a 260 m long trajectory, and succeeds on a 430 m long round-trip tunnel trajectory where the reference fails.
Comments8 pages, 9 figures. Vsevolod Hulchuk and Jan Bayer contributed equally
