Word of warning, below is a textwall that may be interesting to some, but may not answer the posters question. Read at your own peril.
I did some research as part off my Master thesis where I created a map using JOSM (java editor for OpenStreetMap) using indoor mapping plugins and then hosted the database (map nodes and relations) locally (could also be hosted online). A simple python node can then be used to query this database using overpass API. I put in information like different floors, hallways, door colours, which sensors could be used in which area. It was all kind of experimental, but technically possible. It gave me a multi-layered map containing the low level x-,y-, occupancy information, a low level topological map, high level topological map all the way up to a high-level semantic map. I never got to the point of actually using the map for navigation though
(the mapping effort was luckily enough to graduate on).
The advantage of creating such a map is that the robot does not have to think a lot. All of the information about traffic rules and which methods of localization and navigation to use in which area are all embedded in the map. The obvious disadvantage is the insane mapping effort required to get such a map. Additionally there is no standard way to this that I am aware of. I came up with my own model, my own hierarchy and own key-value combinations. I just wanted to share my experience and point out that OSM can be used for indoor mapping as well and that OSM has a pretty big open source community so lots of tools and plugins are available.
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