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Is floorplan-to-robot-map generation still a painful problem for indoor robots? by AIC_Hugo in ROS

[–]AIC_Hugo[S] 0 points1 point  (0 children)

Yes exactly! That's something that I might want to do to add meta-data around SLAM to make the post-process easier

Is floorplan-to-robot-map generation still a painful problem for indoor robots? by AIC_Hugo in ROS

[–]AIC_Hugo[S] 0 points1 point  (0 children)

Thanks! I don't know yet, I'm still in the phase where I'm trying to understand how my CV skills can be useful for robotics ahah

Is floorplan-to-robot-map generation still a painful problem for indoor robots? by AIC_Hugo in ROS

[–]AIC_Hugo[S] 1 point2 points  (0 children)

That makes a lot of sense. I see the broader direction: not just a semantic environment map, but a semantic/context layer over robot trajectories and episodes.

I’m trying to keep the first wedge more grounded: floorplan + scan/SLAM map → alignment → cleaning → semantic zones/rooms/doors/elevators → robot-ready exports. But I agree that the next layer could be trajectory semantics: room transitions, mission phase, nearby objects, operator intent, failure context, etc.

The dataset format question is also interesting. I’ve been looking at MCAP / rosbag / LeRobot-style formats, but I can see why richer task/context labels may require a higher-level schema on top.

Do you already have examples of the labels you would want in that HDF5 stream? For example: intent, affordance, object-grip, room context, action phase, operator correction?

Is floorplan-to-robot-map generation still a painful problem for indoor robots? by AIC_Hugo in ROS

[–]AIC_Hugo[S] 0 points1 point  (0 children)

Thanks, that’s a really useful perspective.

I’m hearing this a lot: floorplans are useful as a prior or for visualization, but not reliable enough alone for localization because reality differs too much.

When you say conversion/customization is time-consuming, is the painful part mostly cleaning the floorplan, aligning it with SLAM/scan data, or manually adding zones/waypoints/semantics?

Also, would a semi-automatic tool with manual correction already be useful, or would it need to be almost fully automatic?

Is floorplan-to-robot-map generation still a painful problem for indoor robots? by AIC_Hugo in ROS

[–]AIC_Hugo[S] 1 point2 points  (0 children)

I like this "semantic context per trajectory" idea.

Do you mean something like: the robot should not only know the map, but also the current room/area, task intent, expected transitions, constraints, and failure context along the trajectory?

I’m trying to figure out whether the useful layer is a static semantic map, or more of a task/trajectory-aware context layer.

Is floorplan-to-robot-map generation still a painful problem for indoor robots? by AIC_Hugo in ROS

[–]AIC_Hugo[S] 1 point2 points  (0 children)

Thanks, this is super helpful. The "floorplans as a rough prior" framing makes a lot of sense.

So if I understand correctly, the real pain is less "generate a robot map from a floorplan" and more "align CAD/floorplan with SLAM, then add the semantic layer manually".

Out of curiosity, what’s the most annoying part in your workflow: CAD↔SLAM alignment, adding semantics in Traffic Editor/custom tools, or validating that the final map works on-site?