osmAG-Nav: A Hierarchical Semantic Topometric Navigation Stack for Robust Lifelong Indoor Autonomy

Abstract

The deployment of mobile robots in large-scale, multi-floor environments demands navigation systems that achieve spatial scalability without compromising local kinematic precision. Traditional navigation stacks, reliant on monolithic occupancy grid maps, face severe bottlenecks in storage efficiency, cross-floor reasoning, and long-horizon planning. To address these limitations, this paper presents osmAG-Nav, a complete, open-source ROS2 navigation stack built upon the hierarchical semantic topometric OpenStreetMap Area Graph (osmAG) map standard. The system follows a "System of Systems" architecture that decouples global topological reasoning from local metric execution. A Hierarchical osmAG planner replaces dense grid searches with an LCA-anchored pipeline on a passage-centric graph whose edge costs derive from local raster traversability rather than Euclidean distance, yielding low-millisecond planning on long campus-scale routes. A Rolling Window mechanism rasterizes a fixed-size local metric grid around the robot, keeping the local costmap memory footprint independent of the total mapped area, while a Segmented Execution strategy dispatches intermediate goals to standard ROS2 controllers for smooth handoffs. System robustness is reinforced by a structure-aware LiDAR localization framework that filters dynamic clutter against permanent architectural priors. Extensive experiments on a real-world multi-story indoor-outdoor campus (>11,025 m^2) show that, on the same-floor benchmark subset, osmAG-Nav delivers up to 7816x lower planning latency than a grid-based baseline on long routes while maintaining low path-length overhead and lifelong localization stability. A single-floor long-range robot mission further validates the integrated stack reliability. The full stack is released as modular ROS2 Lifecycle Nodes.

Figures (10)

• Figure 1: Hierarchical Multi-Floor Navigation with osmAG-Nav. The proposed system leverages the osmAG standard to abstract complex environments into a semantic hierarchy (bottom right tree), where atomic locations (Rooms, blue nodes) are logically grouped into Sectors (teal nodes). This structural abstraction enables efficient global routing across large-scale facilities. The visualization demonstrates an autonomous cross-floor mission: the planner generates a topology-centric path (orange trajectory) that navigates from a 2nd-floor Start pose, identifies and utilizes the elevator (highlighted vertical shaft) as a semantic passage, and seamlessly proceeds to the 1st-floor End goal. By defining the environment through permanent vector structures (walls) and topological connections rather than dense metric grids, the system maintains scalability while keeping the runtime local metric map memory footprint bounded independently of the total mapped area.
• Figure 2: Rendered example of an osmAG map in an OSM-compatible indoor renderer. Rooms, corridors, and larger structural regions are visualized as vector polygons over a georeferenced base layer, while elevator and stair icons expose the vertical-transition semantics directly in the map view. The rendering illustrates that osmAG is not merely a storage format, but a semantic-topological representation that can be inspected, validated, and edited within the OSM ecosystem.
• Figure 3: System architecture of osmAG-Nav. The stack follows a decoupled "system of systems" design. The environment layer maintains the global semantic-topological map and serves a bounded Rolling Window raster through /local_AGgridmap. The deliberative layer combines structure-based localization with hierarchical passage-centric planning in the global semantic frame. The execution layer remains standard Nav2, consuming the injected metric map and intermediate goals through ROS2-native interfaces.
• Figure 4: Topology-to-Metric Bridging with Rolling Window and Segmented Execution. (a) The planner reasons over the full semantic-topological map in AGmap, while only a bounded Rolling Window is rasterized and published as /local_AGgridmap in the map frame for Nav2. (b) Within the local window, area interiors are filled as free space, non-passage boundaries are marked occupied, and passage segments are explicitly reopened to preserve traversability. (c) The planner dispatches intermediate passage goals through NavigateToPose; when the desired passage lies beyond the current local map, a proxy goal is projected to the local boundary and refreshed as the window advances.
• Figure 5: Attach-Lift-Common-Parent Hierarchical Planning. (a) The osmAG hierarchy (Building $\rightarrow$ Floors $\rightarrow$ Sectors $\rightarrow$ Rooms) with start area $A_s$ and goal area $A_g$ highlighted, showing their ancestry paths to the common parent $A_c$. (b) The planner injects virtual passage $s$ and attaches it to the leaf compact graph via multi-source Dijkstra. (c) The frontier is lifted upward through parent lift graphs until reaching the common parent. (d) A* runs on the assembled common-parent compact graph to find the compact trace. (e) The compact trace is expanded back to the full passage sequence.