Hi, I'm building an iOS LiDAR scanning app using ARWorldTrackingConfiguration with sceneReconstruction = .mesh. During scanning I save the RGB image, ARFrame.camera.transform, intrinsics and per-frame scene depth. At the end of the scan I also have the final ARMeshAnchor mesh. When I place the saved depth observations into the ARSession world using their original ARCamera.transform, they broadly form the same scene, but over a longer walk I can see several-centimetre discrepancies between observations of the same surfaces. My question is very specific: After ARKit has built its world map / reconstructed the environment, is there any public API that provides a globally refined or corrected historical pose for previously captured ARFrames, rather than the original ARCamera.transform recorded at each frame? In other words, is there an API or ARKit data structure from which I can obtain something equivalent to: frame timestamp → refined world-space camera transform after the session has accumulated more information? I am aware of ARWorldMap and worldMappingStatus, but I'm unclear whether the world map contains information that can be used to recover or refine the historical camera trajectory, or whether ARCamera.transform is the only historical pose available to an app. I'm not looking for advice on implementing ICP or my own SLAM/registration. I just want to know whether ARKit already exposes a refined trajectory or the underlying information needed to obtain one. Thanks.

We are developing a LiDAR-based spatial capture application using ARKit and RealityKit. We are investigating whether PhotogrammetrySession can be used as part of a capture pipeline where we collect: RGB frames LiDAR depth camera intrinsics camera transforms IMU/device motion data and then reconstruct a textured 3D model. The documentation states that PhotogrammetrySample can include depthDataMap, depthConfidenceMap, gravity, and camera metadata. Could someone clarify how PhotogrammetrySession uses the depth information when supplied? Specifically: Is LiDAR depth used during reconstruction to improve geometry (for example as a constraint during reconstruction), or is it primarily used for scale/orientation metadata? When camera transforms and intrinsics are available from ARKit, does PhotogrammetrySession consume this information, or does it independently estimate camera poses from the image sequence? Is the recommended Apple workflow for RGB + LiDAR capture: ARKit capture → PhotogrammetrySample → PhotogrammetrySession or is ObjectCaptureSession the intended capture pipeline for photogrammetry workflows? We are trying to understand the intended relationship between ARKit, ObjectCaptureSession, and PhotogrammetrySession before choosing an architecture. Thanks.