This paper proposes a method for topological mapping and navigation using a monocular camera. Based on AnyLoc, keyframes are converted into descriptors to construct topological relationships, enabling loop detection and map building. Unlike metric maps, topological maps simplify path planning and navigation by representing environments with key nodes instead of precise coordinates. Actions for visual navigation are determined by comparing segmented images with the image associated with target nodes. The system relies solely on a monocular camera, ensuring fast map building and navigation using key nodes. Experiments show effective loop detection and navigation in real and simulation environments without pre-training. Compared to a ResNet-based method, this approach improves success rates by 60.2% on average while reducing time and space costs, offering a lightweight solution for robot and human navigation in various scenarios.

翻译：本文提出了一种基于单目相机实现拓扑建图与导航的方法。该方法基于AnyLoc框架，将关键帧转换为描述符以构建拓扑关系，从而实现回环检测与地图构建。与度量地图不同，拓扑地图通过关键节点而非精确坐标来表示环境，从而简化了路径规划与导航过程。视觉导航中的动作决策通过将分割图像与目标节点关联图像进行比较来实现。该系统仅依赖单目相机，利用关键节点确保了快速的地图构建与导航。实验表明，该方法在真实环境与仿真环境中均能实现有效的回环检测与导航，且无需预训练。与基于ResNet的方法相比，此方法在平均成功率上提升了60.2%，同时降低了时间与空间开销，为机器人与人类在各种场景下的导航提供了一种轻量级解决方案。