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import abc
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import builtins
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from pathlib import Path
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from typing import Any
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import draccus
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from lerobot.motors import MotorCalibration
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from lerobot.utils.constants import HF_LEROBOT_CALIBRATION, ROBOTS
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from .config import RobotConfig
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class Robot(abc.ABC):
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"""
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The base abstract class for all LeRobot-compatible robots.
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This class provides a standardized interface for interacting with physical robots.
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Subclasses must implement all abstract methods and properties to be usable.
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Attributes:
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config_class (RobotConfig): The expected configuration class for this robot.
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name (str): The unique robot name used to identify this robot type.
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"""
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config_class: builtins.type[RobotConfig]
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name: str
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def __init__(self, config: RobotConfig):
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self.robot_type = self.name
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self.id = config.id
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self.calibration_dir = (
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config.calibration_dir if config.calibration_dir else HF_LEROBOT_CALIBRATION / ROBOTS / self.name
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)
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self.calibration_dir.mkdir(parents=True, exist_ok=True)
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self.calibration_fpath = self.calibration_dir / f"{self.id}.json"
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self.calibration: dict[str, MotorCalibration] = {}
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if self.calibration_fpath.is_file():
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self._load_calibration()
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def __str__(self) -> str:
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return f"{self.id} {self.__class__.__name__}"
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@property
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@abc.abstractmethod
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def observation_features(self) -> dict:
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"""
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A dictionary describing the structure and types of the observations produced by the robot.
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Its structure (keys) should match the structure of what is returned by :pymeth:`get_observation`.
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Values for the dict should either be:
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- The type of the value if it's a simple value, e.g. `float` for single proprioceptive value (a joint's position/velocity)
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- A tuple representing the shape if it's an array-type value, e.g. `(height, width, channel)` for images
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Note: this property should be able to be called regardless of whether the robot is connected or not.
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"""
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pass
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@property
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@abc.abstractmethod
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def action_features(self) -> dict:
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"""
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A dictionary describing the structure and types of the actions expected by the robot. Its structure
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(keys) should match the structure of what is passed to :pymeth:`send_action`. Values for the dict
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should be the type of the value if it's a simple value, e.g. `float` for single proprioceptive value
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(a joint's goal position/velocity)
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Note: this property should be able to be called regardless of whether the robot is connected or not.
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"""
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pass
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@property
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@abc.abstractmethod
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def is_connected(self) -> bool:
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"""
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Whether the robot is currently connected or not. If `False`, calling :pymeth:`get_observation` or
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:pymeth:`send_action` should raise an error.
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"""
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pass
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@abc.abstractmethod
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def connect(self, calibrate: bool = True) -> None:
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"""
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Establish communication with the robot.
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Args:
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calibrate (bool): If True, automatically calibrate the robot after connecting if it's not
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calibrated or needs calibration (this is hardware-dependant).
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"""
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pass
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@property
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@abc.abstractmethod
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def is_calibrated(self) -> bool:
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"""Whether the robot is currently calibrated or not. Should be always `True` if not applicable"""
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pass
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@abc.abstractmethod
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def calibrate(self) -> None:
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"""
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Calibrate the robot if applicable. If not, this should be a no-op.
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This method should collect any necessary data (e.g., motor offsets) and update the
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:pyattr:`calibration` dictionary accordingly.
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"""
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pass
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def _load_calibration(self, fpath: Path | None = None) -> None:
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"""
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Helper to load calibration data from the specified file.
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Args:
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fpath (Path | None): Optional path to the calibration file. Defaults to `self.calibration_fpath`.
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"""
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fpath = self.calibration_fpath if fpath is None else fpath
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with open(fpath) as f, draccus.config_type("json"):
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self.calibration = draccus.load(dict[str, MotorCalibration], f)
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def _save_calibration(self, fpath: Path | None = None) -> None:
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"""
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Helper to save calibration data to the specified file.
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Args:
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fpath (Path | None): Optional path to save the calibration file. Defaults to `self.calibration_fpath`.
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"""
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fpath = self.calibration_fpath if fpath is None else fpath
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with open(fpath, "w") as f, draccus.config_type("json"):
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draccus.dump(self.calibration, f, indent=4)
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@abc.abstractmethod
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def configure(self) -> None:
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"""
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Apply any one-time or runtime configuration to the robot.
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This may include setting motor parameters, control modes, or initial state.
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"""
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pass
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@abc.abstractmethod
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def get_observation(self) -> dict[str, Any]:
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"""
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Retrieve the current observation from the robot.
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Returns:
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dict[str, Any]: A flat dictionary representing the robot's current sensory state. Its structure
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should match :pymeth:`observation_features`.
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"""
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pass
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@abc.abstractmethod
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def send_action(self, action: dict[str, Any]) -> dict[str, Any]:
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"""
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Send an action command to the robot.
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Args:
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action (dict[str, Any]): Dictionary representing the desired action. Its structure should match
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:pymeth:`action_features`.
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Returns:
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dict[str, Any]: The action actually sent to the motors potentially clipped or modified, e.g. by
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safety limits on velocity.
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"""
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pass
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@abc.abstractmethod
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def disconnect(self) -> None:
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"""Disconnect from the robot and perform any necessary cleanup."""
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pass
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