Add voice control, working but need more work
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dora_voice_control/README.md
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dora_voice_control/README.md
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# Dora Voice Control Node
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A Dora node that processes Spanish voice commands from children and translates them into robot actions (movement, grasping, releasing objects). Includes a web debug interface.
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## Features
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- Spanish voice command parsing (rule-based or Gemini LLM)
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- Real-time web debug interface
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- Command queue management
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- Workspace bounds validation
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- Object detection integration
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## File Structure
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```
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dora_voice_control/
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├── __init__.py
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├── main.py # Main Dora node entry point
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├── api.py # FastAPI web server
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├── config.py # Configuration management
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├── models.py # Pydantic request/response models
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├── parser.py # Voice command parsing logic
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├── state.py # Shared state management
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└── templates.py # HTML template for web interface
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```
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## Web Debug Interface
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Access the debug interface at `http://localhost:8080` (default).
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Features:
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- Real-time status monitoring (pose, objects, queue)
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- Send manual voice commands
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- Quick command buttons
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- View parse results
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- Command history
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- Clear queue
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## Inputs/Outputs
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| Input | Type | Description |
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|---------------|--------|------------------------------------------|
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| `voice_in` | string | Text transcription of voice command |
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| `tcp_pose` | array | Current robot pose [x, y, z, roll, pitch, yaw] |
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| `objects` | JSON | Detected objects from vision system |
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| `status` | JSON | Command execution status from robot |
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| Output | Type | Description |
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|---------------|--------|------------------------------------------|
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| `robot_cmd` | JSON | Robot command with action and payload |
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| `voice_out` | JSON | Response confirmation to user |
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| `scene_update`| JSON | Updated scene with all visible objects |
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## Supported Commands (Spanish)
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| Command | Action | Example |
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|---------------|----------------|--------------------------------|
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| `subir` | Move up | "sube" |
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| `bajar` | Move down | "baja" |
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| `tomar` | Grab object | "agarra el cubo rojo" |
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| `soltar` | Release object | "suelta en la caja azul" |
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| `ir` | Go to object | "ve al cilindro" |
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| `reiniciar` | Reset | "reinicia" |
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## Environment Variables
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```bash
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# Web API Server
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API_ENABLED=true # Enable/disable web interface
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API_HOST=0.0.0.0 # Bind address
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API_PORT=8080 # Listen port
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# TCP Parameters
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TCP_OFFSET_MM=63.0 # Z-offset to object surface
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APPROACH_OFFSET_MM=50.0 # Safe approach distance above object
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STEP_MM=20.0 # Distance for up/down increments
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# LLM Configuration (optional)
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LLM_PROVIDER=rules # "rules" or "gemini"
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GOOGLE_API_KEY=your_key # Required if using gemini
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GEMINI_MODEL=gemini-2.0-flash
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# Workspace Safety (optional)
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WORKSPACE_MIN_X=-300
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WORKSPACE_MAX_X=300
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WORKSPACE_MIN_Y=-300
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WORKSPACE_MAX_Y=300
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WORKSPACE_MIN_Z=0
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WORKSPACE_MAX_Z=500
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# Misc
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DRY_RUN=false # Skip sending robot commands
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```
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## Installation
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```bash
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cd dora_voice_control
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pip install -e .
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# With LLM support
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pip install -e ".[llm]"
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```
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## Testing
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### Web Interface
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```bash
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# Start the node (standalone for testing)
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python -m dora_voice_control.main
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# Open in browser
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open http://localhost:8080
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```
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### API Endpoints
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```bash
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# Get status
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curl http://localhost:8080/api/status
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# Get objects
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curl http://localhost:8080/api/objects
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# Get queue
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curl http://localhost:8080/api/queue
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# Send command
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curl -X POST http://localhost:8080/api/command \
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-H "Content-Type: application/json" \
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-d '{"text": "sube"}'
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# Clear queue
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curl -X POST http://localhost:8080/api/queue/clear
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```
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### Python Test
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```python
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from dora_voice_control.parser import rule_parse, normalize
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# Test command parsing
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text = "agarra el cubo rojo grande"
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result = rule_parse(normalize(text))
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print(result)
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# {'resultado': 'ok', 'accion': 'tomar', 'objeto': 'cubo', 'color': 'rojo', 'tamano': 'grande'}
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```
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## Dora Dataflow Configuration
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```yaml
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nodes:
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- id: voice_control
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build: pip install -e ./dora_voice_control
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path: dora_voice_control
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inputs:
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voice_in: iobridge/voice_in
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tcp_pose: robot/tcp_pose
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objects: detector/objects
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status: robot/status
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outputs:
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- robot_cmd
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- voice_out
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- scene_update
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env:
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API_ENABLED: "true"
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API_PORT: "8080"
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DRY_RUN: "false"
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```
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## Message Examples
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### Input: voice_in
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```
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"sube"
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"agarra el cubo rojo"
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"suelta en la caja azul"
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```
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### Output: robot_cmd
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```json
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{
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"id": "550e8400-e29b-41d4-a716-446655440000",
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"action": "move_to_pose",
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"payload": {
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"x": 150.0,
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"y": 200.0,
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"z": 280.0,
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"roll": 180.0,
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"pitch": 0.0,
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"yaw": 0.0
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}
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}
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```
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### Output: voice_out
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```json
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{"text": "Ok, voy a subir", "status": "ok"}
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{"text": "No entendi el comando", "status": "error"}
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```
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## Dependencies
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- dora-rs >= 0.3.9
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- numpy < 2.0.0
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- pyarrow >= 12.0.0
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- fastapi >= 0.109.0
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- uvicorn >= 0.27.0
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- pydantic >= 2.0.0
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- google-genai (optional, for Gemini mode)
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