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Reply to Questions about RoomPlan, Room API, USDZ/STEP comparison, and extended spatial scanning
RoomPlan and ARKit already provide most of the components required for professional as-built verification: semantic room reconstruction, LiDAR scene meshes, world tracking, relocalization, reference-object tracking, and on-device ML. What is still missing is a system-level, hardware-accelerated API that compares a reference design with the live reconstructed physical environment. The proposed API should accept reference geometry or a semantic spatial model, persistent object identifiers, a reference/world transform, and configurable dimensional tolerances, and continuously return measured deviations between the design model and the observed scene. Example outputs: Wall W103 Endpoint deviation: -31 mm Status: Out of tolerance Pipe P204 Centerline deviation: +12 mm Status: Within tolerance Valve V204 Status: Expected but not observed Confidence: 0.93 Door D14 Status: Matched Deviation: 6 mm The API should expose measured deviation, confidence, tracking quality, and estimated measurement accuracy. The important capability is not support for another CAD or BIM file format. Third-party applications can convert IFC, STEP, USD, USDZ, or other engineering formats into the reference representation required by the framework. The important system-level workflow is: Design intent → Spatial registration → Live LiDAR / camera reconstruction → Reference-to-reality comparison → Quantified deviations This would allow an engineer to walk through a construction site or industrial plant with an iPhone, iPad Pro, or Vision Pro and receive real-time verification such as: this wall is positioned correctly this wall is 31 mm too short this pipe is within installation tolerance this valve is missing this opening is too small this equipment is installed at the wrong elevation RoomPlan currently answers: “What is here?” A comparison API would allow Apple spatial frameworks to also answer: “How does what is here differ from what should be here?” This could support construction QA/QC, BIM as-built verification, renovation, industrial installation, commissioning, digital twins, facility management, and automated progress inspection. Developers can already implement custom mesh comparison algorithms themselves, but this requires recreating functionality that could be much more accurate and efficient when implemented close to Apple’s calibrated camera, LiDAR, IMU, Neural Engine, and ARKit tracking stack. A native reference-to-reality comparator would therefore be much more valuable than simply adding additional export formats.
Topic: ARKit SubTopic:
ARKit Q&A
1d
Reply to Questions about RoomPlan, Room API, USDZ/STEP comparison, and extended spatial scanning
The one feature which will be good and can be used on iPad and iPhone pro and vision pro would be on device Hardware acelerated comparator API and extend ScenerecostructionProvider to iPhone and iPad with lidars , second for custom ML (but can be also maked that you send object to detection to ai model in cloud which generate 3d model from lidar detection and paste in usdz file) yes is possible but this also need to be combine to have detection and also add to roomplan api geometry combine api end export custom detected object with simple api in swift this would be beneficial also for vision pro and for the end continuous scanning for multifloor floor where we have lobby with big stairs or angle sloops would be visionOS beneficial
Topic: ARKit SubTopic:
ARKit Q&A
Jun ’26
Reply to Support for ifc and furniture recognition and solid scan in AR6 kit
Hi, thank you for your answer, also would be great to have also 3d comparator api like we import floor plan ( ifc or internal polygons, stl) and then with LiDAR scan room or part to see the differences compare virtual model with real model , also for solid parts in mechanical engineer like shafts , valves , to take 2d dimension like flatten function in cad programs (Flatten 3d to 2d) api function. best regards
Topic: Spatial Computing SubTopic: ARKit Tags:
Jun ’23
Reply to Questions about RoomPlan, Room API, USDZ/STEP comparison, and extended spatial scanning
RoomPlan and ARKit already provide most of the components required for professional as-built verification: semantic room reconstruction, LiDAR scene meshes, world tracking, relocalization, reference-object tracking, and on-device ML. What is still missing is a system-level, hardware-accelerated API that compares a reference design with the live reconstructed physical environment. The proposed API should accept reference geometry or a semantic spatial model, persistent object identifiers, a reference/world transform, and configurable dimensional tolerances, and continuously return measured deviations between the design model and the observed scene. Example outputs: Wall W103 Endpoint deviation: -31 mm Status: Out of tolerance Pipe P204 Centerline deviation: +12 mm Status: Within tolerance Valve V204 Status: Expected but not observed Confidence: 0.93 Door D14 Status: Matched Deviation: 6 mm The API should expose measured deviation, confidence, tracking quality, and estimated measurement accuracy. The important capability is not support for another CAD or BIM file format. Third-party applications can convert IFC, STEP, USD, USDZ, or other engineering formats into the reference representation required by the framework. The important system-level workflow is: Design intent → Spatial registration → Live LiDAR / camera reconstruction → Reference-to-reality comparison → Quantified deviations This would allow an engineer to walk through a construction site or industrial plant with an iPhone, iPad Pro, or Vision Pro and receive real-time verification such as: this wall is positioned correctly this wall is 31 mm too short this pipe is within installation tolerance this valve is missing this opening is too small this equipment is installed at the wrong elevation RoomPlan currently answers: “What is here?” A comparison API would allow Apple spatial frameworks to also answer: “How does what is here differ from what should be here?” This could support construction QA/QC, BIM as-built verification, renovation, industrial installation, commissioning, digital twins, facility management, and automated progress inspection. Developers can already implement custom mesh comparison algorithms themselves, but this requires recreating functionality that could be much more accurate and efficient when implemented close to Apple’s calibrated camera, LiDAR, IMU, Neural Engine, and ARKit tracking stack. A native reference-to-reality comparator would therefore be much more valuable than simply adding additional export formats.
Topic: ARKit SubTopic:
ARKit Q&A
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1d
Reply to Questions about RoomPlan, Room API, USDZ/STEP comparison, and extended spatial scanning
And also tanks you for your answer
Topic: ARKit SubTopic:
ARKit Q&A
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Jun ’26
Reply to Questions about RoomPlan, Room API, USDZ/STEP comparison, and extended spatial scanning
The one feature which will be good and can be used on iPad and iPhone pro and vision pro would be on device Hardware acelerated comparator API and extend ScenerecostructionProvider to iPhone and iPad with lidars , second for custom ML (but can be also maked that you send object to detection to ai model in cloud which generate 3d model from lidar detection and paste in usdz file) yes is possible but this also need to be combine to have detection and also add to roomplan api geometry combine api end export custom detected object with simple api in swift this would be beneficial also for vision pro and for the end continuous scanning for multifloor floor where we have lobby with big stairs or angle sloops would be visionOS beneficial
Topic: ARKit SubTopic:
ARKit Q&A
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Jun ’26
Reply to Questions about RoomPlan, Room API, USDZ/STEP comparison, and extended spatial scanning
This is holy grail in construction industry ifc lite few weeks ago after few years try to solve this with two ifc files compare https://liteaeco.com/tools/IFC_Compare.html
Topic: Spatial Computing SubTopic: ARKit Tags:
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Jun ’26
Reply to Acess to the point cloud/mesh created by LiDAR with the new Ipad Pro
Yes there is a mesh2mesh converter on macOS
Topic: Graphics & Games SubTopic: RealityKit Tags:
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Dec ’23
Reply to Support for ifc and furniture recognition and solid scan in AR6 kit
Hi, can you support in ARKIT export floorplan api like in usdz to .bim simple xml file format https://dotbim.net , also include in usdz semantics for blender conversion in ifc but dotBIM would be great , already have element catalogue , so this is just write xml in .bim file format
Topic: Spatial Computing SubTopic: ARKit Tags:
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Sep ’23
Reply to Support for ifc and furniture recognition and solid scan in AR6 kit
Can you just add for v18 API in Roomplan kit export to simple ifc thru https://ifcjs.github.io/info/docs/introduction just wall, openings, doors, windows, rooms, or make simple usdz to ifc converter maybe in macOS viewer best regards, Ivo
Topic: Spatial Computing SubTopic: ARKit Tags:
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Jun ’23
Reply to Support for ifc and furniture recognition and solid scan in AR6 kit
Hi, thank you for your answer, also would be great to have also 3d comparator api like we import floor plan ( ifc or internal polygons, stl) and then with LiDAR scan room or part to see the differences compare virtual model with real model , also for solid parts in mechanical engineer like shafts , valves , to take 2d dimension like flatten function in cad programs (Flatten 3d to 2d) api function. best regards
Topic: Spatial Computing SubTopic: ARKit Tags:
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Jun ’23