agents.components.vla

Module Contents

Classes

VLA	Vision-Language-Agent (VLA) Component.

API

class agents.components.vla.VLA(*, inputs: List[agents.ros.Topic], outputs: List[agents.ros.Topic], model_client: agents.clients.lerobot.LeRobotClient, config: agents.config.VLAConfig, component_name: str, **kwargs)

Bases: agents.components.model_component.ModelComponent

Vision-Language-Agent (VLA) Component.

custom_on_activate()

Custom activation

custom_on_deactivate()

Custom deactivation

set_termination_trigger(mode: Literal[timesteps, pynput.keyboard, event] = 'timesteps', max_timesteps: int = 100, stop_key: str = 'q', stop_event: Optional[agents.ros.Event] = None)

Set the condition used to determine when an action is done.

Parameters:

• mode – One of ‘timesteps’, ‘keyboard’, ‘event’.

• max_timesteps – The number of timesteps after which to stop (used if mode=‘timesteps’ or ‘event’).

• stop_key – The key to press to stop the action (used if mode=‘keyboard’).

signal_done()

Signals that the action is complete. Can be used as an action for signaled events

set_aggregation_function(agg_fn: Callable[[numpy.ndarray, numpy.ndarray], numpy.ndarray])

Set the aggregation function to be used for aggregating generated actions from the robot policy model

Parameters:

agg_fn (Callable[[np.ndarray, np.ndarray], np.ndarray]) – A callable that takes two numpy arrays as input and returns a single numpy array.

Raises:

TypeError – If agg_fn is not a callable or does not match the expected signature.

main_action_callback(goal_handle: agents.ros.VisionLanguageAction.Goal)

Callback for the VLA main action server

Parameters:

goal_handle (VisionLanguageAction.Goal) – Incoming action goal

Returns:

Action result

Return type:

VisionLanguageAction.Result