# Add a New Robot

This project uses a simple adapter + behavior pattern.

## 1) Create a robot adapter

Implement the common command interface:

- File: `dora_voice_control/dora_voice_control/robots/<robot_name>/adapter.py`
- Base class: `RobotAdapter` (`dora_voice_control/dora_voice_control/core/robot.py`)

Example (vacuum style):

```python
from __future__ import annotations
from typing import Any, Dict, List

from ...core.robot import RobotAdapter
from ...core.state import RobotStep

NAME = "my_robot"
ALIASES = {"my_robot", "my_alias"}

class MyRobotAdapter(RobotAdapter):
    def grab(self) -> List[RobotStep]:
        return [RobotStep(action="vacuum_on", payload={})]

    def release(self) -> List[RobotStep]:
        return [RobotStep(action="vacuum_off", payload={})]

    def move(self, payload: Dict[str, Any]) -> List[RobotStep]:
        return [RobotStep(action="move_to_pose", payload=payload)]

    def reset_tool(self) -> List[RobotStep]:
        return [RobotStep(action="vacuum_off", payload={})]
```

The `action` strings must match what your robot node understands.

## 2) Create robot actions

- File: `dora_voice_control/dora_voice_control/robots/<robot_name>/actions.py`
- Use `ActionInfo` to define names, aliases, and requirements.

```python
from ...core.behavior import ActionInfo

MY_ACTIONS = {
    "tomar": ActionInfo(name="tomar", aliases=["toma"], requires_object=False),
    "soltar": ActionInfo(name="soltar", aliases=["suelta"], requires_object=False),
}
```

## 3) Create robot behavior

- File: `dora_voice_control/dora_voice_control/robots/<robot_name>/behavior.py`
- Subclass `RobotBehavior` and implement `action_handlers()`.

```python
from typing import Callable
from ...core.behavior import ActionContext, RobotBehavior
from .actions import MY_ACTIONS

class MyRobotBehavior(RobotBehavior):
    ACTIONS = MY_ACTIONS

    def action_tomar(self, ctx: ActionContext) -> bool:
        self._queue_steps(ctx, self.robot_adapter.grab())
        return True

    def action_soltar(self, ctx: ActionContext) -> bool:
        self._queue_steps(ctx, self.robot_adapter.release())
        return True

    def action_handlers(self) -> dict[str, Callable[[ActionContext], bool]]:
        return {
            "tomar": self.action_tomar,
            "soltar": self.action_soltar,
        }
```

## 4) Register the robot

- File: `dora_voice_control/dora_voice_control/robots/__init__.py`

Add a resolver entry that maps `ROBOT_TYPE` to your adapter/behavior.

## 5) Update dataflow

Set `ROBOT_TYPE` in your dataflow:

```yaml
env:
  ROBOT_TYPE: "my_robot"
```

## Safety notes

- Keep bounds checks in behavior methods (`_queue_move` already checks workspace limits).
- For real hardware, validate with a staged plan: simulation → dry-run → full run.
