diff --git a/dataflow_voice_control_ulite6_zed.yml b/dataflow_voice_control_ulite6_zed.yml
index e79867f..21386a7 100644
--- a/dataflow_voice_control_ulite6_zed.yml
+++ b/dataflow_voice_control_ulite6_zed.yml
@@ -66,8 +66,7 @@ nodes:
       CALIBRATION_FILE: "calibration_ulite6_zed.npz"
       DETECTOR_WEIGHTS: "trained_models/yolo8n.pt"
       CONFIG_FILE: "config.toml"
-      ROI_TOP_LEFT: "500,230"
-      ROI_BOTTOM_RIGHT: "775,510"
+      USE_ROI: "false"
       SIZE_THRESHOLD: "4200"
       DETECT_EVERY_N: "3"
       MIN_DEPTH_MM: "10"
@@ -107,9 +106,9 @@ nodes:
       DRY_RUN: "false"
       # Initial position (used on startup and reset command)
       INIT_ON_START: "true"
-      INIT_X: "300.0"
+      INIT_X: "250.0"
       INIT_Y: "0.0"
-      INIT_Z: "350.0"
+      INIT_Z: "400.0"
       INIT_ROLL: "180.0"
       INIT_PITCH: "0.0"
       INIT_YAW: "0.0"
diff --git a/dora_voice_control/docs/add_robot.md b/dora_voice_control/docs/add_robot.md
new file mode 100644
index 0000000..8faf312
--- /dev/null
+++ b/dora_voice_control/docs/add_robot.md
@@ -0,0 +1,100 @@
+# 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.
diff --git a/dora_voice_control/docs/voice_control_node.md b/dora_voice_control/docs/voice_control_node.md
new file mode 100644
index 0000000..e19345b
--- /dev/null
+++ b/dora_voice_control/docs/voice_control_node.md
@@ -0,0 +1,44 @@
+# Voice Control Node
+
+This node turns voice intents into robot commands and publishes them to the Dora graph.
+
+## Dataflow wiring
+
+Typical wiring (from `dataflow_voice_control_ulite6_zed.yml`):
+
+- Inputs
+  - `voice_in` (speech/commands)
+  - `tcp_pose` (current robot TCP pose)
+  - `objects` (detected objects)
+  - `status` (robot status)
+  - `image_annotated` (debug image)
+- Outputs
+  - `robot_cmd` (robot command queue)
+  - `scene_update` (scene debug)
+  - `voice_out` (debug/feedback)
+
+## Runtime flow
+
+1) Voice input is parsed into an intent (action + optional object/color/size).
+2) The scene is queried for a target object if the action requires it.
+3) `RobotBehavior.execute()` validates preconditions and dispatches to a handler.
+4) The handler queues `RobotStep` commands via the adapter.
+5) `CommandQueueService` sends commands on `robot_cmd`.
+
+## Key files
+
+- `dora_voice_control/dora_voice_control/main.py`
+  - Node wiring, intent processing, and dispatch loop.
+- `dora_voice_control/dora_voice_control/core/behavior.py`
+  - Base behavior, action validation, handler dispatch.
+- `dora_voice_control/dora_voice_control/robots/`
+  - Robot-specific adapters and behaviors.
+
+## Environment variables (common)
+
+- `ROBOT_TYPE`: robot selector (e.g., `vacuum`, `littlehand`)
+- `COMMAND_OUTPUT`: output port name for robot commands (default `robot_cmd`)
+- `INIT_ON_START`: queue initial reset + move to home (default `true`)
+- `INIT_X/Y/Z`, `INIT_ROLL/PITCH/YAW`: home pose
+
+See `dora_voice_control/README.md` for full configuration.
diff --git a/dora_voice_control/dora_voice_control/robots/littlehand/behavior.py b/dora_voice_control/dora_voice_control/robots/littlehand/behavior.py
index 4bc6860..50f9dcc 100644
--- a/dora_voice_control/dora_voice_control/robots/littlehand/behavior.py
+++ b/dora_voice_control/dora_voice_control/robots/littlehand/behavior.py
@@ -34,10 +34,11 @@ class LittlehandBehavior(RobotBehavior):
         return self._queue_move(ctx, ctx.pose[0], ctx.pose[1], target_z)
 
     def action_ir(self, ctx: ActionContext) -> bool:
-        """Move to object position (approach + target)."""
+        """Move to object X/Y while keeping current Z."""
+        if ctx.pose is None or ctx.target is None:
+            return False
         pos = ctx.target.position_mm
-        self._queue_approach_sequence(ctx, pos)
-        return True
+        return self._queue_move(ctx, pos[0], pos[1], ctx.pose[2])
 
     def action_tomar(self, ctx: ActionContext) -> bool:
         """Activate tool (low-level grab)."""
diff --git a/dora_yolo_object_detector/dora_yolo_object_detector/main.py b/dora_yolo_object_detector/dora_yolo_object_detector/main.py
index 1ab109d..1bfdb17 100644
--- a/dora_yolo_object_detector/dora_yolo_object_detector/main.py
+++ b/dora_yolo_object_detector/dora_yolo_object_detector/main.py
@@ -324,24 +324,25 @@ def _draw_detections(
     """Draw bounding boxes and labels on frame."""
     annotated = frame.copy()
 
-    # Draw ROI rectangle (always visible)
-    cv2.rectangle(
-        annotated,
-        cfg.roi_top_left,
-        cfg.roi_bottom_right,
-        (0, 255, 0) if cfg.use_roi else (128, 128, 128),
-        2,
-    )
-    # Label the ROI
-    cv2.putText(
-        annotated,
-        "ROI",
-        (cfg.roi_top_left[0] + 5, cfg.roi_top_left[1] + 20),
-        cv2.FONT_HERSHEY_SIMPLEX,
-        0.6,
-        (0, 255, 0) if cfg.use_roi else (128, 128, 128),
-        2,
-    )
+    if cfg.use_roi:
+        # Draw ROI rectangle
+        cv2.rectangle(
+            annotated,
+            cfg.roi_top_left,
+            cfg.roi_bottom_right,
+            (0, 255, 0),
+            2,
+        )
+        # Label the ROI
+        cv2.putText(
+            annotated,
+            "ROI",
+            (cfg.roi_top_left[0] + 5, cfg.roi_top_left[1] + 20),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.6,
+            (0, 255, 0),
+            2,
+        )
 
     # Color mapping for visualization
     color_map = {