在像素级拓扑图中引入闭环，实现更精准的任意点间导航。
PixelLoop: Shortcut Topological Navigation with Pixel-Level Loops
- 直接在像素空间构建拓扑闭环，替代传统稀疏图像边或位姿图修正。
- 仿真测试中成功率与SPL提升超35%，尤其在需捷径时优势明显。
- 适合需要高精度路径规划的移动机器人视觉导航场景。
尽管拓扑地图与导航已被广泛研究，但闭环在纯拓扑表示中的作用及其下游影响仍关注较少。值得注意的是，拓扑地图上的闭环不同于基于全局参考轨迹和度量地图的闭环。基于近期以像素级相对3D几何为基础的更密集拓扑结构，我们提出PixelLoop，直接在像素空间引入闭环。与传统的稀疏图像级边或SLAM中的位姿图修正不同，我们的像素级闭环作为密集的拓扑捷径，改变路径规划连通性与代价传播，而不仅仅是对齐坐标。这种密集连通性实现了稳定的任意点到任意点导航，并生成与几何最短路径高度一致的成本图。特别地，我们展示了将闭环应用于细粒度像素拓扑而非图像级拓扑的优势。在大量模拟实验中，PixelLoop相较于图像相对基线，在成功率和SPL上均取得超过35%的绝对提升，尤其在需要利用捷径的场景中表现最佳。真实世界移动机器人部署进一步验证了其效果，表明密集像素级闭环为拓扑视觉导航提供了实用且鲁棒的基础。
原文摘要 · Abstract (English)
Although topological mapping and navigation have been studied extensively, the specific role and downstream effect of loop closures in purely topological representations has received relatively little attention. Importantly, loop closure over topological maps is distinct from loop closure over globally referenced trajectories and metric maps. Building on recent denser topologies grounded in pixel-level, relative 3D geometry, we propose PixelLoop which introduces loop closures directly in pixel space. Unlike sparse image-level edges or pose-graph corrections in SLAM, our pixel-level closures act as dense topological shortcuts that alter planning connectivity and cost propagation rather than merely aligning coordinates. This dense connectivity enables stable any-point-to-any-point navigation and produces costmaps that align accurately with geometric shortest paths. In particular, we showcase the distinct advantage of applying loop closures to fine-grained pixel topologies rather than image-level topologies. Across extensive simulated experiments, PixelLoop achieves over 35% absolute improvement in both Success Rate and SPL compared to image-relative baselines, with the largest gains in scenarios requiring shortcut exploitation. Results are further validated through real-world mobile robot deployments, demonstrating that dense pixel-level loop closures provide a practical and robust foundation for topological visual navigation. Project Page: https://pixelloop-nav.github.io/
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