用射线投射法去除动态物体，提升静态3D地图一致性
Raymoval: Raycasting-based Dynamic Object Removal for Static 3D Mapping
- 通过射线投射比较扫描与地图的最小距离，识别动态点
- 在SemanticKITTI和自建数据集上显著减少残留动态物体
- 适合长期自主导航的机器人地图构建，尤其复杂动态环境
静态地图是机器人导航的基础，提供持久的几何先验和长期自主的稳定参考。然而，动态物体残留痕迹会导致表面缺失，降低地图一致性。本文提出一种基于射线投射的动态物体移除模块：将每帧扫描投影到方位-俯仰网格，对每个视角比较分箱最小距离与地图首次击中距离（由射线投射计算）。进一步引入射线投射一致性测试，分离动态与静态点；最后通过空间一致性验证步骤优化标签，生成残余动态物体更少、过移除更少的静态地图。在SemanticKITTI和一个挑战性自建数据集上进行了定量与定性评估，结果表明该方法能实现一致且高质量的静态地图。
原文摘要 · Abstract (English)
Static mapping is fundamental to robot navigation, providing a persistent geometric prior and a consistent reference for long-term autonomy. However, dynamic objects leave residual traces and cause surface loss, which reduces map consistency. We propose a raycasting-based module for dynamic object removal in static 3D mapping. Each scan is projected onto an azimuth-elevation grid, and for every viewing direction we compare the bin-wise minimum range with the map's first-hit distance computed by raycasting. Furthermore, we apply a raycast consistency test that separates dynamic from static points. Finally, a spatial consistency validation step refines labels, producing static maps with lower residual dynamics and reduced over-removal. We evaluate our approach quantitatively and qualitatively on SemanticKITTI and a challenging custom dataset, and show consistent static mapping results.
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