iterate on review:

src/lerobot/processor/observation_processor.py

@@ -243,22 +243,21 @@ class LiberoProcessorStep(ObservationProcessorStep):
             robot_state = processed_obs.pop("observation.robot_state")
 
             # Extract components
-            eef_pos = robot_state["eef"]["pos"]  # (3,)
-            eef_quat = robot_state["eef"]["quat"]  # (4,)
-            gripper_qpos = robot_state["gripper"]["qpos"]  # (2,)
+            eef_pos = robot_state["eef"]["pos"]  # (B, 3,)
+            eef_quat = robot_state["eef"]["quat"]  # (B, 4,)
+            gripper_qpos = robot_state["gripper"]["qpos"]  # (B, 2,)
 
             # Convert quaternion to axis-angle
             eef_axisangle = self._quat2axisangle(eef_quat)  # (B, 3)
-
             # Concatenate into a single state vector
-            state = np.concatenate((eef_pos, eef_axisangle, gripper_qpos), axis=-1)
+            state = torch.cat((eef_pos, eef_axisangle, gripper_qpos), dim=-1)
 
-            # Convert to tensor
-            state_tensor = torch.from_numpy(state).float()
-            if state_tensor.dim() == 1:
-                state_tensor = state_tensor.unsqueeze(0)
+            # ensure float32
+            state = state.float()
+            if state.dim() == 1:
+                state = state.unsqueeze(0)
 
-            processed_obs[OBS_STATE] = state_tensor
+            processed_obs[OBS_STATE] = state
         return processed_obs
 
     def transform_features(
@@ -267,7 +266,26 @@ class LiberoProcessorStep(ObservationProcessorStep):
         """
         Transforms feature keys from the LIBERO format to the LeRobot standard.
         """
-        new_features: dict[PipelineFeatureType, dict[str, PolicyFeature]] = {ft: {} for ft in features}
+        new_features: dict[PipelineFeatureType, dict[str, PolicyFeature]] = {}
+
+        # copy over non-STATE features
+        for ft, feats in features.items():
+            if ft != PipelineFeatureType.STATE:
+                new_features[ft] = feats.copy()
+
+        # rebuild STATE features
+        state_feats = {}
+
+        # add our new flattened state
+        state_feats["observation.state"] = PolicyFeature(
+            key="observation.state",
+            shape=(8,),  # [eef_pos(3), axis_angle(3), gripper(2)]
+            dtype="float32",
+            description=("Concatenated end-effector position (3), axis-angle (3), and gripper qpos (2)."),
+        )
+
+        new_features[PipelineFeatureType.STATE] = state_feats
+
         return new_features
 
     def observation(self, observation):