We are building an ARKit application targeting iPhone Pro devices on iOS 26.4+. During testing, we consistently observe the following log message at a specific point in our AR session (approximately 90° into a walking arc around a vehicle): ARWorldTrackingTechnique: resource constraints [33] What specifically does resource constraint code [33] represent? Is it a VIO constraint type, a sensor fusion budget limit, or something else entirely? How does it differ from code [1] (which appears to be a general CPU starvation signal for the ARKit sensor fusion thread)? Is there a public API to detect or respond to this specific constraint condition, short of waiting for a full ARCamera.TrackingState downgrade? Was this constraint type introduced or changed in iOS 26.4?

Hello, I am doing a personal research project around ARKit camera frames and camera calibration data. For each accepted ARFrame, I export: ARFrame.timestamp ARFrame.camera.imageResolution ARFrame.camera.intrinsics ARFrame.capturedImage The target video mode is 4K / 30 FPS. In my test captures, I noticed two things: ARFrame.camera.intrinsics is not constant across the recording. Some neighboring frames from ARFrame.capturedImage have noticeably different sharpness: one frame can look sharp, while the next frame can look blurred. Regarding intrinsics, I observe small per-frame changes in fx/fy/cx/cy. For example, in one session: fx/fy changed by approximately 36 px cx changed by approximately 1.5 px cy changed by approximately 2.3 px I understand the standard meaning of the intrinsic matrix: fx / fy = focal length in pixels cx / cy = principal point in pixels relative to the image/reference frame My main question is not about the definition of these values, but about how to correctly interpret their changes over time. In particular, I am interested in cx/cy, because the principal point is important for measurements. I would like to understand whether a change in cx/cy corresponds to a meaningful update of the camera model for the current frame, and what physical or camera-pipeline process may cause this change. Questions about ARFrame.camera.intrinsics: Are ARFrame.camera.intrinsics values expected to change between frames during a single ARWorldTrackingConfiguration session? If fx/fy changes over time, can this reflect autofocus / focus breathing, internal camera calibration updates, digital crop/scaling, stabilization-related mapping, or other camera pipeline changes? If cx/cy changes over time, should I interpret this as an updated principal point for the current ARFrame image/reference frame? Does ARKit update cx/cy to account for any internal crop, scaling, stabilization, virtual camera behavior, lens movement, or calibration changes? Is there a known physical interpretation for small cx/cy changes reported by ARFrame.camera.intrinsics, or should these values simply be treated as ARKit’s best current camera model for that frame? In an ARKit-first pipeline where focus/exposure/stabilization are managed by ARKit/camera pipeline, is the recommended approach to store ARFrame.camera.intrinsics per frame together with ARFrame.timestamp and ARFrame.camera.imageResolution? Is there any public API that exposes the reason for intrinsics changes, such as focus position, stabilization transform, crop transform, active camera constituent, lens movement, or per-frame calibration update reason? I also have a related question about ARFrame.capturedImage frame quality. In some recordings, neighboring frames can have noticeably different sharpness. For example, one frame can look sharp, while the next frame can be visibly blurred, even though the scene and camera movement are continuous. Questions about frame sharpness / camera pipeline behavior: Is frame-to-frame sharpness variation expected when using ARFrame.capturedImage as the video source? Can ARKit change focus, exposure duration, ISO, white balance, crop/scaling, or other camera pipeline parameters between frames during an ARWorldTrackingConfiguration session? Is there any public API to inspect per-frame exposure duration, ISO, focus position, lens position, stabilization state, crop/scaling transform, or other capture parameters for ARFrame.capturedImage? If some frames are sharp and neighboring frames are blurred, should this usually be interpreted as motion blur / exposure behavior / autofocus behavior, or can ARKit internal processing also affect this? Is there any recommended way in an ARKit-first pipeline to reduce frame-to-frame sharpness inconsistency, or is the only reliable approach to use an AVFoundation-first capture pipeline with locked focus/exposure/ISO/white balance? The main goal of my research is to understand how to correctly interpret ARKit-provided intrinsics over time and how much of the camera pipeline behavior is observable through public ARKit APIs. Since fx/fy/cx/cy are important for measurements, I want to know whether treating ARFrame.camera.intrinsics as the Apple-delivered per-frame camera model is the safest approach. Thank you.

Providing a response and feedback to this: https://origin-devforums.apple.com/forums/thread/827311 and https://developer.apple.com/forums/thread/827043?page=1#889020022 I have a created a feedback/bug report with ID FB22823733 Feedback Report: I have created a feedback report as well like recommended with this ID: FB22823733, with more elaborate images of my implementation, also see here More clarity: Yes, this is for an iOS app(iOS 18+) but testing and debugging on Xcode(MacOS 15.7.7, M4 24GB), which traps or hangs on getting to [PhotogrammetrySample] even while using the lazy sequence and the contentsOf as specified in your docs. I also tried using the PhotogrammetrySession folder run but its still failed with : CoreOC.PhotogrammetrySession.Error 6 and I understand to mean alignment failed. What can be done or do you guys expose any functions that can be used to aid, or handle these internally, can't find any internally. The ObjectMasks are actually segmentation masks from an ML algorithm . To replicate try calling PhotogrammetrySession(input: [PhotogrammetrySample]) with contentsOf as captured on your documentation, even with like 30 image set or is there something I'm missing.

Xcode hangs when I call PhotogrammetrySession(input: [PhotogrammetrySample]) with objectMask set and traps on some devices, see the attached screenshot, it gets to the function and hangs. Even the folder reconstruction also doesn't complete as it can't find alignment and displays the CoreOC.PhotogrammetrySession.Error 6 and I understand to mean alignment failed. In this case it failed while object masking was ON, so RealityKit could not find enough consistent feature tracks inside the masked pixels across the image set. What can be done or do you guys expose any functions that can be used to aid, or handle these internally, can't find any internally. The ObjectMasks are actually segmentation masks from an ML algorithm . To replicate try calling PhotogrammetrySession(input: [PhotogrammetrySample]) with contentsOf as captured on your documentation, even with like 30 image set or is there something I'm missing. I will appreciate a timely response and willing to provide more clarity and informations, thank you so much for your understanding

Reconstruction with Object Mask in PhotogrammetrySession Fails and doesn't complete because of alignment and object masks with thing segmentation even after increasing the mask region . Also the PhotogrammetrySample hangs with EXC_BREAKPOINTwhen I usePhotogrammetrySession(input: [PhotogrammetrySample])withobjectMask set and the Apple Developer Forums report crashes (“HelloPhotogrammetry” / sample+mask), and (EXC_BREAKPOINT` was being observed at ~4 GB) with freezing the execution and Xcode interface

Providing a response and feedback to this: https://origin-devforums.apple.com/forums/thread/827311 and https://developer.apple.com/forums/thread/827043?page=1#889020022 I have a created a feedback/bug report with ID FB22823733 Feedback Report: I have created a feedback report as well like recommended with this ID: FB22823733, with more elaborate images of my implementation, also see here More clarity: Yes, this is for an iOS app(iOS 18+) but testing and debugging on Xcode(MacOS 15.7.7, M4 24GB), which traps or hangs on getting to [PhotogrammetrySample] even while using the lazy sequence and the contentsOf as specified in your docs. I also tried using the PhotogrammetrySession folder run but its still failed with : CoreOC.PhotogrammetrySession.Error 6 and I understand to mean alignment failed. What can be done or do you guys expose any functions that can be used to aid, or handle these internally, can't find any internally. The ObjectMasks are actually segmentation masks from an ML algorithm . To replicate try calling PhotogrammetrySession(input: [PhotogrammetrySample]) with contentsOf as captured on your documentation, even with like 30 image set or is there something I'm missing.

Summary We have identified a reproducible world tracking drift regression in ARKit on LiDAR-equipped iOS devices running iOS 26.4 and later. A static virtual node anchored at the world origin visually drifts from its initial position as the user moves around a real-world scene, despite the scene remaining physically static. The same code produces stable, drift-free results on non-LiDAR devices running identical OS versions. Device & OS Observations Testing was performed across four devices on iOS 26.4 using the same application build and ARWorldTrackingConfiguration settings. Non-LiDAR devices — iPhone 14 and iPhone 15 — produced stable, drift-free tracking in all test runs. No world origin displacement was observed regardless of how long or how far the user walked. LiDAR-equipped devices — iPhone 14 Pro and iPhone 16 Pro — exhibited consistent, reproducible drift. A static node placed at the world origin visually shifted from its initial position as the user moved through the scene. The same devices were stable on earlier iOS versions, confirming this is a regression introduced in iOS 26.4. Technical Observations Nature of drift: A SCNNode placed statically at the ARKit world origin (SCNVector3(0, 0, 0)) visually displaces from its original position as the user walks around a static real-world scene. The displacement is not random — it accumulates directionally as the user moves, consistent with a sensor fusion or coordinate anchoring error. Trigger condition: The drift occurs during normal walking motion around a fixed point of interest, such as circling a parked vehicle. It does not appear when the device is held still. LiDAR specificity: The drift is exclusive to devices with a LiDAR scanner. Identical hardware configurations — same iOS build, same ARWorldTrackingConfiguration settings — on non-LiDAR devices produce no drift whatsoever. This isolates the regression to the LiDAR sensor's contribution to ARKit's internal Visual-Inertial Odometry (VIO) fusion pipeline. No API-level workaround found: There is currently no public ARKit API to selectively disable the LiDAR scanner's contribution to VIO. All available configuration-level options have been evaluated without resolving the drift. ARWorldTrackingConfiguration Options Evaluated The following configuration changes were applied individually and in combination. None resolved the drift on LiDAR devices: isAutoFocusEnabled = false — No improvement videoHDRAllowed = false (disabled) — No improvement planeDetection = [] (disabled) — No improvement sceneReconstruction = .mesh — No improvement worldAlignment: .gravity vs .gravityAndHeading — No improvement Minimal Reproduction Case The drift can be reproduced with a minimal ARKit scene: Create an ARSCNView with ARWorldTrackingConfiguration using default settings. Add a single static SCNNode (e.g., a small sphere or axes geometry) at SCNVector3(0, 0, 0) when the session starts. Run the app on a LiDAR-equipped device (iPhone Pro, iPad Pro with LiDAR) on iOS 26.4 or later. Walk in a circle around the node's approximate real-world position. Expected: The node remains visually fixed at its world position throughout the walkthrough. Actual: The node drifts from its initial position, increasingly displaced from its world origin anchor as walking continues. We want to know if Apple has made any internal updates to ARKit, particularly after the OS 26.4 upgrade. Thanks!

FB22720952 (ObjectCaptureSession fails with ARError.Code.sensorFailed on iOS 26.4.2 while RoomPlan and Measure continue to work). 17 pro Max

Hi everyone, I’m currently using the RoomPlan API, which has been working reliably until recently. However, I’ve started encountering an intermittent error and I’m trying to understand what might be causing it. The error is triggered in the ARSession observer method: session(_ session: ARSession, didFailWithError error: Error) It has occurred on at least two devices: iPhone 14 Pro iPhone 17 Pro Here’s the full error message: ARSession failed domain=com.apple.arkit.error code=102 desc=Required sensor failed. userInfo=["NSLocalizedFailureReason": A sensor failed to deliver the required input., "NSUnderlyingError": Error Domain=AVFoundationErrorDomain Code=-11819 "Cannot Complete Action" UserInfo={NSLocalizedDescription=Cannot Complete Action, NSLocalizedRecoverySuggestion=Try again later.}, "NSLocalizedDescription": Required sensor failed.] This seems to indicate that a required sensor (likely LiDAR or camera) failed to provide input, but I’m not sure what’s causing it or why it happens only occasionally. Has anyone experienced something similar or has insight into possible causes or fixes? Thanks in advance!

ARCamera.TrackingState questions: Did the threshold or sensitivity for transitioning ARCamera.TrackingState from .normal to .limited(.excessiveMotion) or .limited(.insufficientFeatures) change between iOS 26.3 and iOS 26.4? What does "ARWorldTrackingTechnique: resource constraints [33]" mean, and is it new in iOS 26.4? Does it correspond to a tracking state degradation? Is there a way for the client to detect or respond to ARKit entering a resource-constrained mode short of the full tracking state transition — for example, a lower-level notification or a flag on ARFrame — so that apps can take protective action without interpreting it as a full tracking failure? ARCamera.unprojectPoint questions: Did the behavior of ARCamera.unprojectPoint(_:ontoPlane:orientation:viewportSize:) change between iOS 26.3 and iOS 26.4 for near-parallel geometry? Specifically, on iOS 26.3 this method returns nil when the camera ray is nearly parallel to the target plane (denominator of the ray-plane intersection → 0 at ~90° of camera rotation). On iOS 26.4, with identical code and environment, it returns a large finite value instead — we observed z = −12.27m. Since the method's optional return type implies nil is the documented signal for no valid intersection, this reads as a behavioral regression rather than an intentional change. If returning the computed value for near-parallel geometry is now the intended behavior, is there a recommended way for the caller to guard against it? For example, should we check abs(dot(rayDirection, planeNormal)) against a threshold before calling, and if so, is there a documented epsilon Apple uses internally? Alternatively, is there a newer API we should prefer over unprojectPoint(:ontoPlane:) for this use case that handles degenerate geometry more gracefully — such as ARSession.raycast(:)? Are there any other ARKit API adjustments between OS 26.3 and 26.4? We are using the same codebase, but it behaves differently in between these 2 OS versions now. Thanks!

I’m trying to build a persistent world map of my college campus using ARKit, but it’s not very reliable. Anchors don’t consistently appear in the same place across sessions. I’ve tried using image anchors, but they didn’t improve accuracy much. How can I create a stable world map for a larger area and reliably relocalize anchors? Are there better approaches or recommended resources for this?

Problem Summary After upgrading to iOS 26.1 and 26.2, I'm experiencing a particle positioning bug in RealityKit where ParticleEmitterComponent particles render at an incorrect offset relative to their parent entity. This behavior does not occur on iOS 18.6.2 or earlier versions, suggesting a regression introduced in the newer OS builds. Environment Details Operating System: iOS 26.1 & iOS 26.2 Framework: RealityKit Xcode Version: 16.2 (16C5032a) Expected vs. Actual Behavior Expected: Particles should render at the position of the entity to which the ParticleEmitterComponent is attached, matching the behavior on iOS 18.6.2 and earlier. Actual: Particles appear away from their parent entity, creating a visual misalignment that breaks the intended AR experience. Steps to Reproduce Create or open an AR application with RealityKit that uses particle components Attach a ParticleEmitterComponent to an entity via a custom system Run the application on iOS 26.1 or iOS 26.2 Observe that particles render at an offset position away from the entity Minimal Code Example Here's the setup from my test case: Custom Component & System: struct SparkleComponent4: Component {} class SparkleSystem4: System { static let query = EntityQuery(where: .has(SparkleComponent4.self)) required init(scene: Scene) {} func update(context: SceneUpdateContext) { for entity in context.scene.performQuery(Self.query) { // Only add once if entity.components.has(ParticleEmitterComponent.self) { continue } var newEmitter = ParticleEmitterComponent() newEmitter.mainEmitter.color = .constant(.single(.red)) entity.components.set(newEmitter) } } } AR Setup: let material = SimpleMaterial(color: .gray, roughness: 0.15, isMetallic: true) let model = Entity() model.components.set(ModelComponent(mesh: boxMesh, materials: [material])) model.components.set(SparkleComponent4()) model.position = [0, 0.05, 0] model.name = "MyCube" let anchor = AnchorEntity(.plane(.horizontal, classification: .any, minimumBounds: [0.2, 0.2])) anchor.addChild(model) arView.scene.addAnchor(anchor) Questions for the Community Has anyone else encountered this particle positioning issue after updating to iOS 26.1/26.2? Are there known workarounds or configuration changes to ParticleEmitterComponent that restore correct positioning? Is this a confirmed bug, or could there be a change in coordinate system handling or transform inheritance that I'm missing? Additional Information I've already submitted this issue via Feedback Assistant(FB21346746)

I have two RealityView: ParentView and When click the button in ParentView, ChildView will be shown as full screen cover, but the camera feed in ChildView will not be shown, only black screen. If I show ChildView directly, it works with camera feed. Please help me on this issue? Thanks. import RealityKit import SwiftUI struct ParentView: View{ @State private var showIt = false var body: some View{ ZStack{ RealityView{content in content.camera = .virtual let box = ModelEntity(mesh: MeshResource.generateSphere(radius: 0.2),materials: [createSimpleMaterial(color: .red)]) content.add(box) } Button("Click here"){ showIt = true } } .fullScreenCover(isPresented: $showIt){ ChildView() .overlay( Button("Close"){ showIt = false }.padding(20), alignment: .bottomLeading ) } .ignoresSafeArea(.all) } } import ARKit import RealityKit import SwiftUI struct ChildView: View{ var body: some View{ RealityView{content in content.camera = .spatialTracking } } }

I’m running into a hardware reality. MEMS sensor thermal drift. If a user zeroes out the tilt indoors at 20°C and then takes the phone outside in the cold, the accelerometer baseline shifts just enough as the device cools to throw off the readings. I want to apply a simple thermal compensation curve to the CoreMotion data to keep the "zero" perfectly level regardless of the weather. However, ProcessInfo.thermalState only gives broad buckets (nominal, fair, etc.) which doesn't help me calculate a continuous offset for a phone cooling down degree by degree. Is there any public API, or even a proxy metric, that can give me a rough battery or internal temperature integer? I don’t need high resolution decimals. Just a general device temp to offset the hardware drift. Any undocumented tricks or proxy metrics anyone has used to handle this?

Hi, I’m working on a real-time head/face tracking pipeline using a standard 2D RGB camera, and I’m trying to better understand how ARKit achieves such stable and responsive results in comparable conditions. To clarify upfront: I’m specifically interested in RGB-only tracking and the underlying vision/ML pipeline. I’m not using TrueDepth or any depth/IR-based sensors, and I’d like to understand how similar stability and responsiveness can be achieved under those constraints. In my current setup, I estimate head pose from RGB frames (facial landmarks + PnP) and apply temporal filtering (e.g., exponential smoothing and Kalman filtering). This significantly reduces jitter, but introduces noticeable latency, especially during faster head movements. What stands out in ARKit is that it appears to maintain both: Very low jitter Very low perceived latency even when operating with camera input alone. I’m trying to understand what techniques might contribute to this behavior. In particular: Does ARKit use predictive tracking (e.g., velocity or acceleration-based pose extrapolation) to compensate for camera and processing delays in RGB-only scenarios? Are there recommended strategies for balancing temporal smoothing and responsiveness without introducing visible lag in camera-based pose estimation pipelines? Is the tracking pipeline internally decoupled from rendering (e.g., asynchronous processing with prediction applied at render time)? Are there general best practices for minimizing end-to-end latency in vision-based head tracking systems beyond standard filtering approaches? I understand that implementation details may not be public, but any high-level insights or pointers would be greatly appreciated. Thanks!

In ARKit there is ARGeoAnchor, which lets you anchor content using latitude and longitude so objects stay fixed to a real-world location. Is there an equivalent feature in RealityKit? I want to place points in the world and make sure they don't move or drift after placement. If RealityKit doesn't support this directly, what is the recommended approach?

I have a question I guess more for the Apple team. But why are there no totally 3D experiences for the Vision Pro lineup? I know they have given us tools to implement unity 3D games into iPhone and I guess you can also build it in RealityKit. But why at this moment are 3D games limited to just iPad and iPhone and can't you bring that into Vision Pro? Just to explain. When I say a totally 3D game, I mean games like Gorn. I mean the Vision Pro is definitely powerful enough, but it just feels limited to tabletop games and AR games. Is this something Apple is thinking about implementing?

Even when making a completely fresh Unity project, if I include ARKit and upload it to testflight, when I open it on my ipad it says 'Couldn't Load App'. If I don't include testflight the app opens fine. If I build the app directly to my ipad the app works fine. It opens if I set ARKit to 'optional' but then the AR doesn't work. I have included a camera and location usage description so it's not that. Really not sure what's going on, any help would be massively appreciated!

I’m working with Reality Composer and noticed that images added directly to a scene appear significantly darker when viewed in AR. This seems different from how other objects in the scene respond to lighting, especially under varying real-world light conditions. Is this expected behavior? Are images treated with a different lighting model in Reality Composer? Is there any recommended way to get more consistent light response for image-based artworks?

Hi, I’m wondering whether RealityKit has its own scene management system, since it uses ARView (backed by ARKit) to present AR content. Does RealityKit manage scenes independently, or does it rely entirely on ARKit’s scene handling? Thank you.