# Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import abc import builtins from pathlib import Path from typing import Any import draccus from lerobot.motors import MotorCalibration from lerobot.utils.constants import HF_LEROBOT_CALIBRATION, ROBOTS from .config import RobotConfig # TODO(aliberts): action/obs typing such as Generic[ObsType, ActType] similar to gym.Env ? # https://github.com/Farama-Foundation/Gymnasium/blob/3287c869f9a48d99454306b0d4b4ec537f0f35e3/gymnasium/core.py#L23 class Robot(abc.ABC): """ The base abstract class for all LeRobot-compatible robots. This class provides a standardized interface for interacting with physical robots. Subclasses must implement all abstract methods and properties to be usable. Attributes: config_class (RobotConfig): The expected configuration class for this robot. name (str): The unique robot name used to identify this robot type. """ # Set these in ALL subclasses config_class: builtins.type[RobotConfig] name: str def __init__(self, config: RobotConfig): self.robot_type = self.name self.id = config.id self.calibration_dir = ( config.calibration_dir if config.calibration_dir else HF_LEROBOT_CALIBRATION / ROBOTS / self.name ) self.calibration_dir.mkdir(parents=True, exist_ok=True) self.calibration_fpath = self.calibration_dir / f"{self.id}.json" self.calibration: dict[str, MotorCalibration] = {} if self.calibration_fpath.is_file(): self._load_calibration() def __str__(self) -> str: return f"{self.id} {self.__class__.__name__}" # TODO(aliberts): create a proper Feature class for this that links with datasets @property @abc.abstractmethod def observation_features(self) -> dict: """ A dictionary describing the structure and types of the observations produced by the robot. Its structure (keys) should match the structure of what is returned by :pymeth:`get_observation`. Values for the dict should either be: - The type of the value if it's a simple value, e.g. `float` for single proprioceptive value (a joint's position/velocity) - A tuple representing the shape if it's an array-type value, e.g. `(height, width, channel)` for images Note: this property should be able to be called regardless of whether the robot is connected or not. """ pass @property @abc.abstractmethod def action_features(self) -> dict: """ A dictionary describing the structure and types of the actions expected by the robot. Its structure (keys) should match the structure of what is passed to :pymeth:`send_action`. Values for the dict should be the type of the value if it's a simple value, e.g. `float` for single proprioceptive value (a joint's goal position/velocity) Note: this property should be able to be called regardless of whether the robot is connected or not. """ pass @property @abc.abstractmethod def is_connected(self) -> bool: """ Whether the robot is currently connected or not. If `False`, calling :pymeth:`get_observation` or :pymeth:`send_action` should raise an error. """ pass @abc.abstractmethod def connect(self, calibrate: bool = True) -> None: """ Establish communication with the robot. Args: calibrate (bool): If True, automatically calibrate the robot after connecting if it's not calibrated or needs calibration (this is hardware-dependant). """ pass @property @abc.abstractmethod def is_calibrated(self) -> bool: """Whether the robot is currently calibrated or not. Should be always `True` if not applicable""" pass @abc.abstractmethod def calibrate(self) -> None: """ Calibrate the robot if applicable. If not, this should be a no-op. This method should collect any necessary data (e.g., motor offsets) and update the :pyattr:`calibration` dictionary accordingly. """ pass def _load_calibration(self, fpath: Path | None = None) -> None: """ Helper to load calibration data from the specified file. Args: fpath (Path | None): Optional path to the calibration file. Defaults to `self.calibration_fpath`. """ fpath = self.calibration_fpath if fpath is None else fpath with open(fpath) as f, draccus.config_type("json"): self.calibration = draccus.load(dict[str, MotorCalibration], f) def _save_calibration(self, fpath: Path | None = None) -> None: """ Helper to save calibration data to the specified file. Args: fpath (Path | None): Optional path to save the calibration file. Defaults to `self.calibration_fpath`. """ fpath = self.calibration_fpath if fpath is None else fpath with open(fpath, "w") as f, draccus.config_type("json"): draccus.dump(self.calibration, f, indent=4) @abc.abstractmethod def configure(self) -> None: """ Apply any one-time or runtime configuration to the robot. This may include setting motor parameters, control modes, or initial state. """ pass @abc.abstractmethod def get_observation(self) -> dict[str, Any]: """ Retrieve the current observation from the robot. Returns: dict[str, Any]: A flat dictionary representing the robot's current sensory state. Its structure should match :pymeth:`observation_features`. """ pass @abc.abstractmethod def send_action(self, action: dict[str, Any]) -> dict[str, Any]: """ Send an action command to the robot. Args: action (dict[str, Any]): Dictionary representing the desired action. Its structure should match :pymeth:`action_features`. Returns: dict[str, Any]: The action actually sent to the motors potentially clipped or modified, e.g. by safety limits on velocity. """ pass @abc.abstractmethod def disconnect(self) -> None: """Disconnect from the robot and perform any necessary cleanup.""" pass