alphaonedev/ar-vr-design

ar-vr-design

Purpose

This skill designs interactive AR/VR experiences by integrating 3D modeling, spatial computing, and UI optimization, enabling creation of immersive environments for applications like virtual training or augmented overlays.

When to Use

Use this skill for projects requiring 3D asset manipulation, spatial interactions, or VR-specific UI tweaks, such as developing a virtual museum tour or AR product visualization in e-commerce apps.

Key Capabilities

• Import and export 3D models in formats like GLTF or OBJ using built-in parsers.
• Perform spatial computing tasks, such as room-scale mapping with algorithms for occlusion and collision detection.
• Optimize UI for AR/VR devices, including rendering adjustments for headsets like Oculus or HoloLens to reduce latency below 20ms.
• Simulate user interactions in a virtual environment to test gesture controls or haptic feedback.

Usage Patterns

To accomplish tasks, follow these steps: First, initialize a project with required configs; then, build and manipulate 3D assets; next, apply spatial computing for interactions; finally, optimize and simulate. Always set environment variables for authentication, e.g., export SERVICE_API_KEY=your_key before running commands. For integration, wrap skill outputs in a main application loop.

Common Commands/API

Use the arvr-cli tool for core operations. Authenticate via $ARVR_API_KEY environment variable.

• Command: arvr-cli init --project myvrapp --type vr

  • Initializes a new VR project; add --ar flag for AR mode.
  • Example snippet:

    export ARVR_API_KEY=abc123
    arvr-cli init --project myvrapp
    

• API Endpoint: POST /api/vr/models

  • Uploads a 3D model; requires JSON payload with { "model": "path/to/model.gltf", "scale": 1.5 }.
  • Example snippet:

    curl -H "Authorization: Bearer $ARVR_API_KEY" -X POST -d '{"model": "asset.gltf"}' https://api.openclaw.com/api/vr/models
    

• Command: arvr-cli optimize --input model.obj --device oculus

  • Optimizes model for specific devices; outputs optimized file.
  • Example snippet:

    arvr-cli optimize --input scene.glb --device hololens
    

• API Endpoint: GET /api/ar/spatial-map

  • Retrieves spatial data; query with parameters like ?roomSize=10x10.
  • Example snippet:

    curl -H "Authorization: Bearer $ARVR_API_KEY" https://api.openclaw.com/api/ar/spatial-map?roomSize=5x5
    

Config formats: Use JSON for project configs, e.g., { "assets": ["model1.obj"], "spatialSettings": { "gravity": 9.8 } }.

Integration Notes

Integrate this skill into workflows by importing outputs into engines like Unity or Unreal. For example, after running arvr-cli init, copy generated files to a Unity project and reference them in scripts. Use $ARVR_API_KEY for API calls in custom code. To chain with other skills, pipe outputs via stdin/stdout, e.g., output from a 3D modeling skill into this one's input. Ensure compatibility by matching formats: always convert models to GLTF before integration.

Error Handling

Handle errors by checking exit codes from commands; for API calls, parse HTTP responses. Common issues:

• Authentication failure: If $ARVR_API_KEY is invalid, commands return code 401—fix by verifying and exporting the correct key.
• Invalid model format: Use arvr-cli validate --file model.obj; if it fails with code 400, convert the file using a tool like Blender.
• Example snippet for error checking:

  response=$(curl ...); if [ $? -ne 0 ]; then echo "API error: $response"; fi
  

Always wrap API calls in try-catch blocks in scripts, e.g., in Python: try: requests.post(url) except Exception as e: log_error(e).

Concrete Usage Examples

1. Design a simple AR overlay for a mobile app: First, run arvr-cli init --project ar-overlay --type ar. Then, upload a 3D model with curl -X POST -d '{"model": "overlay.glb"}' https://api.openclaw.com/api/vr/models. Optimize for mobile: arvr-cli optimize --input overlay.glb --device android. Finally, integrate the output into an Android app using Unity's AR Foundation.

2. Create a VR simulation for training: Initialize with arvr-cli init --project vr-training --type vr. Add spatial mapping: curl https://api.openclaw.com/api/ar/spatial-map?roomSize=10x10. Build interactions: Use the API to simulate gestures, then test with arvr-cli simulate --project vr-training. Export and import into Unreal Engine for full deployment.

Graph Relationships

• Related to cluster: ar-vr (e.g., shares tags with skills like ar-vr-development).
• Connected via tags: ["ar-vr"] links to other AR/VR skills; ["design"] connects to ui-design and 3d-modeling skills.
• Dependencies: Requires outputs from 3d-modeling skills as inputs.