# GlassGuard：用于机器人导航的经验证玻璃平面建图

> 原文链接：https://robotics.hellobike.com/papers/2026-10-01-2610-02110
> 频道：papers | 更新日期：2026-10-01 | 标签：arxiv, cs.RO
> 核心摘要：GlassGuard面向玻璃导致的LiDAR建图缺失，融合视觉与LiDAR证据重建平面玻璃，并在真实楼宇机器人行驶中验证。

# GlassGuard：用于机器人导航的经验证玻璃平面建图

::: v-pre
> 原文链接：[GlassGuard: Verified Glass Plane Mapping for Robot Navigation](https://arxiv.org/abs/2610.02110)（arXiv 2610.02110 · 发布日期：2026-10-01）

**GlassGuard: Verified Glass Plane Mapping for Robot Navigation**

GlassGuard面向玻璃导致的LiDAR建图缺失，融合视觉与LiDAR证据重建平面玻璃，并在真实楼宇机器人行驶中验证。

## 核心要点

- 透明和镜面表面会让LiDAR回波穿透玻璃，使地图缺少碰撞边界。
- 框架以玻璃覆盖与自由空间污染共同衡量成功，贯穿候选验证和全局建图。
- 利用基础视觉模型生成玻璃实例掩码，结合结构3D线索和平面朝向几何检查。
- 同针孔输入下覆盖率82%，基线最高61%，每帧假体素少5-17倍；项目页已提供。

**验证范围与局限**：验证范围为九个建筑尺度真实场景中的机器人行驶和定性导航规划示例。

## 英文摘要 (Abstract)

Transparent and specular surfaces pose a serious challenge to LiDAR-based SLAM and navigation because laser returns may pass through glass, leaving collision boundaries absent from the map. Prior work attempts to reconstruct the missing surfaces, but inaccurate obstacle placement can create the opposite failure: contamination of traversable free space. Recognizing this dual requirement, we present GlassGuard, a navigation-oriented framework for reconstructing planar architectural glass from complementary visual and LiDAR evidence. We formulate success in terms of both glass coverage and free-space contamination and apply this principle throughout proposal verification and global map construction. A foundation vision model provides glass-instance masks, structural 3D cues generate metric plane hypotheses, and depth-free 2D projective geometry checks their orientations before they enter a consolidated global map. We evaluate GlassGuard in nine building-scale scenes spanning diverse glass structures, spatial scales, and lighting conditions, with more than one hour and 2.1 km of real-world robot traversal. GlassGuard achieves 85% of total glass coverage for its panoramic version. Under identical pinhole inputs, GlassGuard achieves 82% total coverage, compared with at most 61% for the evaluated baselines, while producing 5-17x fewer false voxels per frame. Qualitative examples with a navigation planner illustrate the reconstructed planes blocking paths through glass while leaving traversable routes open. The project page is available at https://glassguardproject.github.io/.

作者：Hanwen Guo, Zhengzhi Lin, Yusen Xie, Ji Zhang
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## 原始参考来源 (Sources)

- [arXiv 2610.02110：GlassGuard: Verified Glass Plane Mapping for Robot Navigation](https://arxiv.org/abs/2610.02110)