refactor(processor): clarify action types, distinguish PolicyAction, RobotAction, and EnvAction (#1908)

* refactor(processor): split action from policy, robots and environment

- Updated function names to robot_action_to_transition and robot_transition_to_action across multiple files to better reflect their purpose in processing robot actions.
- Adjusted references in the RobotProcessorPipeline and related components to ensure compatibility with the new naming convention.
- Enhanced type annotations for action parameters to improve code readability and maintainability.

* refactor(converters): rename robot_transition_to_action to transition_to_robot_action

- Updated function names across multiple files to improve clarity and consistency in processing robot actions.
- Adjusted references in RobotProcessorPipeline and related components to align with the new naming convention.
- Simplified action handling in the AddBatchDimensionProcessorStep by removing unnecessary checks for action presence.

* refactor(converters): update references to transition_to_robot_action

- Renamed all instances of robot_transition_to_action to transition_to_robot_action across multiple files for consistency and clarity in the processing of robot actions.
- Adjusted the RobotProcessorPipeline configurations to reflect the new naming convention, enhancing code readability.

* refactor(processor): update Torch2NumpyActionProcessorStep to extend ActionProcessorStep

- Changed the base class of Torch2NumpyActionProcessorStep from PolicyActionProcessorStep to ActionProcessorStep, aligning it with the current architecture of action processing.
- This modification enhances the clarity of the class's role in the processing pipeline.

* fix(processor): main action processor can take also EnvAction

---------

Co-authored-by: Steven Palma <steven.palma@huggingface.co>

src/lerobot/processor/batch_processor.py

@@ -27,11 +27,11 @@ from torch import Tensor
 from lerobot.configs.types import PipelineFeatureType, PolicyFeature
 from lerobot.constants import OBS_ENV_STATE, OBS_IMAGE, OBS_IMAGES, OBS_STATE
 
-from .core import EnvTransition
+from .core import EnvTransition, PolicyAction
 from .pipeline import (
-    ActionProcessorStep,
     ComplementaryDataProcessorStep,
     ObservationProcessorStep,
+    PolicyActionProcessorStep,
     ProcessorStep,
     ProcessorStepRegistry,
 )
@@ -39,14 +39,14 @@ from .pipeline import (
 
 @dataclass
 @ProcessorStepRegistry.register(name="to_batch_processor_action")
-class AddBatchDimensionActionStep(ActionProcessorStep):
+class AddBatchDimensionActionStep(PolicyActionProcessorStep):
     """
     Processor step to add a batch dimension to a 1D tensor action.
 
     This is useful for creating a batch of size 1 from a single action sample.
     """
 
-    def action(self, action: Tensor) -> Tensor:
+    def action(self, action: PolicyAction) -> PolicyAction:
         """
         Adds a batch dimension to the action if it's a 1D tensor.
 
@@ -56,7 +56,7 @@ class AddBatchDimensionActionStep(ActionProcessorStep):
         Returns:
             The action tensor with an added batch dimension.
         """
-        if not isinstance(action, Tensor) or action.dim() != 1:
+        if action.dim() != 1:
             return action
         return action.unsqueeze(0)