skills/ar-vr/arkit-advanced/SKILL.md
Advanced ARKit features for complex AR development including scene reconstruction and 3D object tracking on iOS.
npx skillsauth add alphaonedev/openclaw-graph arkit-advancedInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides advanced ARKit capabilities for iOS AR development, focusing on scene reconstruction and 3D object tracking to enable complex applications like virtual try-ons or environmental mapping.
Use this skill for projects requiring high-fidelity AR interactions, such as integrating real-world geometry into apps, handling dynamic object detection, or building multi-user AR experiences on iOS devices with A12+ chips.
To use this skill in OpenClaw, invoke it via the CLI with specific flags for task generation. Start by specifying the skill ID and providing context, then chain commands for refinement. For example, generate code for scene reconstruction by passing a JSON config file. Always include device compatibility checks in your workflow.
Use OpenClaw's CLI to interact with this skill. Prefix commands with openclaw run arkit-advanced and add flags for specifics.
Command: openclaw run arkit-advanced --feature scene-reconstruction --config path/to/config.json
let configuration = ARWorldTrackingConfiguration()
configuration.sceneReconstruction = .mesh
session.run(configuration)
Command: openclaw run arkit-advanced --feature object-tracking --object-id sample_cube
let configuration = ARObjectScanningConfiguration()
configuration.detectionObjects = [ARReferenceObject.referenceObject(for: sampleCube)]
session.run(configuration)
API Endpoint: For OpenClaw integration, use HTTP endpoints like POST /api/skills/arkit-advanced/run with a JSON payload: {"feature": "scene-reconstruction", "params": {"environment": "outdoors"}}.
Config Format: Use JSON files, e.g., {"apiVersion": "2.0", "device": "iPhone 13", "trackingMode": "3D"}. Load via --config flag.
Integrate this skill into your OpenClaw workflow by setting environment variables for authentication if accessing Apple services, e.g., export $APPLE_DEVELOPER_KEY for API calls. Ensure your project includes the ARKit framework in Xcode; add import ARKit at the top of Swift files. For multi-skill setups, chain with other ar-vr skills using openclaw chain arkit-advanced --next-skill unity-vr. Test on a physical iOS device, as simulators don't support AR hardware.
Handle errors by checking ARSession's state; for example, catch ARSession.RunOptions errors with if error != nil { print(error!.localizedDescription) }. In OpenClaw commands, use --verbose flag to log failures, e.g., openclaw run arkit-advanced --feature scene-reconstruction --verbose. Common issues include device incompatibility (check A12+ chip) or poor lighting; implement retry logic with session.run(configuration, options: [.removeExistingAnchors]). Parse OpenClaw responses for error codes like 400 for invalid configs.
Scene Reconstruction for Virtual Furniture App: Run openclaw run arkit-advanced --feature scene-reconstruction --config furniture_app.json to generate code that scans a room and places a virtual chair. Code snippet:
let configuration = ARWorldTrackingConfiguration()
configuration.sceneReconstruction = .meshWithClassification
arView.session.run(configuration)
3D Object Tracking for Product Demo: Execute openclaw run arkit-advanced --feature object-tracking --object-id product_model to track a scanned product in AR. Code snippet:
guard let referenceObject = try? ARReferenceObject(url: productURL) else { return }
let configuration = ARObjectScanningConfiguration()
configuration.detectionObjects = [referenceObject]
session.run(configuration)
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