外观
论文arXiv 2609.149031 个月前
HydroMap：用于内河语义场景表示的概率式水面高程建图
原文链接：HydroMap: Probabilistic Water Surface Elevation Mapping for Semantic Scene Representation in Inland Waterways（arXiv 2609.14903 · 发布日期：2026-09-14）
HydroMap: Probabilistic Water Surface Elevation Mapping for Semantic Scene Representation in Inland Waterways
HydroMap用立体视觉重建并融合水面高程，在内河数据集上验证可补全LiDAR地图缺失的水面表示。
核心要点
- 内河自主水面车辆需要持久表示周围结构与水面，但LiDAR SLAM常缺少水面回波。
- 该框架与里程计解耦，由逐帧水点构成联合栅格观测，并传播立体视觉与位姿不确定性。
- 连续观测被融合为持久概率高程图，再与结构几何结合为统一2.5D语义表示。
- 在Pohang Canal和Leuven Vaart数据集上，相对同地图坐标系LiDAR参考的高程RMSE低于5厘米。
验证范围与局限：验证范围为Pohang Canal和Leuven Vaart数据集上的内河水道场景。
英文摘要 (Abstract)
Autonomous surface vehicles operating in inland waterways require a persistent representation of both surrounding structures and the water surface. LiDAR-based simultaneous localization and mapping often produces sparse or missing water returns, leaving this operational surface absent from the reconstructed scene. We propose HydroMap, an odometry-decoupled framework that reconstructs water surface elevation from stereo observations and integrates it with the structural map. Per-frame water points form joint cell observations with propagated stereo and pose uncertainty, and successive observations are fused into a persistent probabilistic elevation map. Semantic map conversion then combines the elevation map with structural geometry in a unified 2.5D representation of water, boundaries, structures, and overhead regions. On the Pohang Canal and Leuven Vaart datasets, the elevation RMSE remains below 5 cm relative to LiDAR references expressed in the same map frame. The elevation and semantic maps are published at 2 Hz and 1 Hz, respectively. HydroMap thereby complements LiDAR maps with a persistent representation of the water surface for downstream navigation in inland waterways.
作者：Zhongbi Luo, Yunjia Wang, Herman Bruyninckx, Peter Slaets
来源
本页事实对应的公开页面，以原文为准。