外观
论文arXiv 2609.273631 个月前
从 LiDAR 地图到视觉定位：用于鲁棒点-线-面位姿估计的统一视觉关联
原文链接：From LiDAR Maps to Visual Localization: Unified Visual Association for Robust Point-Line-Plane Pose Estimation（arXiv 2609.27363 · 发布日期：2026-09-23）
From LiDAR Maps to Visual Localization: Unified Visual Association for Robust Point-Line-Plane Pose Estimation
提出将LiDAR地图渲染为准图像的统一定位框架，在EuRoC MAV和自采真实序列验证全局定位与6-DoF跟踪。
核心要点
- 问题在于相机图像与点云地图存在显著模态差异，影响长期机器人导航定位。
- 方法将地图几何与反射率渲染为带2D-3D来源的LiDAR准图像，共用视觉特征与匹配器。
- 通过点线对应恢复度量LiDAR几何和线支持平面约束，并引入分布感知优化增强鲁棒性。
- 实验显示仅用预建LiDAR地图作持久先验，可实现准确全局定位和鲁棒连续6-DoF跟踪。
验证范围与局限：验证范围为EuRoC MAV基准和自采真实世界序列，包括强光照变化与动态遮挡场景。
英文摘要 (Abstract)
Camera localization in a prior LiDAR map provides a persistent geometric reference for long-term robotic navigation, yet remains challenging because of the substantial modality gap between camera images and point-cloud maps. We present a unified localization framework that makes the LiDAR map visually addressable rather than relying on a dedicated image-LiDAR correspondence model. Map geometry and reflectivity are rendered into LiDAR-derived quasi-images with explicit 2D-3D provenance, enabling camera observations and rendered map views to share mature visual features and matchers for both global localization and continuous pose tracking. Point and line correspondences are established through this common visual interface, while the retained provenance recovers metric LiDAR geometry and line-supported planar constraints for pose estimation. To improve robustness under ambiguous associations and weak geometry, we further introduce a distribution-aware, observability-complementary optimization strategy. Instead of reducing matching ambiguity to a scalar confidence, candidate association distributions are propagated into directional pose-information uncertainty, and reliable structural factors are selectively reinforced according to their ability to complement the currently weak pose directions. Experiments on the EuRoC MAV benchmark and self-collected real-world sequences demonstrate accurate global localization and robust continuous 6-DoF tracking using only a pre-built LiDAR map as the persistent prior, including under severe illumination variations and dynamic occlusions.
作者：Wentao Zhao, Zikun Chen, Niu, Yihe, Haoyu Chen, Jingchuan Wang
来源
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