Add SO-100 robot
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from .configuration_so100 import So100RobotConfig
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from .robot_so100 import So100Robot
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__all__ = ["So100RobotConfig", "So100Robot"]
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from dataclasses import dataclass, field
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from lerobot.common.cameras import CameraConfig
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from ..config import RobotConfig
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@RobotConfig.register_subclass("so100")
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@dataclass
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class So100RobotConfig(RobotConfig):
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# Port to connect to the robot
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port: str
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# `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
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# Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
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# the number of motors in your follower arms.
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max_relative_target: int | None = None
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mock: bool = False
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# motors
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shoulder_pan: tuple = (1, "sts3215")
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shoulder_lift: tuple = (2, "sts3215")
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elbow_flex: tuple = (3, "sts3215")
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wrist_flex: tuple = (4, "sts3215")
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wrist_roll: tuple = (5, "sts3215")
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gripper: tuple = (6, "sts3215")
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# cameras
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cameras: dict[str, CameraConfig] = field(default_factory=dict)
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#!/usr/bin/env python
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# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import logging
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import time
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import numpy as np
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from lerobot.common.cameras.utils import make_cameras_from_configs
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from lerobot.common.constants import OBS_IMAGES, OBS_STATE
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from lerobot.common.errors import DeviceAlreadyConnectedError, DeviceNotConnectedError
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from lerobot.common.motors.feetech import (
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FeetechMotorsBus,
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TorqueMode,
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run_arm_manual_calibration,
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)
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from ..robot import Robot
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from ..utils import ensure_safe_goal_position
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from .configuration_so100 import So100RobotConfig
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class So100Robot(Robot):
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"""
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[SO-100 Arm](https://github.com/TheRobotStudio/SO-ARM100) designed by TheRobotStudio
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"""
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config_class = So100RobotConfig
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name = "koch"
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def __init__(self, config: So100RobotConfig):
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super().__init__(config)
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self.config = config
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self.robot_type = config.type
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self.id = config.id
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self.arm = FeetechMotorsBus(
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port=self.config.port,
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motors={
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"shoulder_pan": config.shoulder_pan,
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"shoulder_lift": config.shoulder_lift,
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"elbow_flex": config.elbow_flex,
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"wrist_flex": config.wrist_flex,
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"wrist_roll": config.wrist_roll,
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"gripper": config.gripper,
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},
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)
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self.cameras = make_cameras_from_configs(config.cameras)
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self.is_connected = False
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self.logs = {}
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@property
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def state_feature(self) -> dict:
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return {
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"dtype": "float32",
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"shape": (len(self.arm),),
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"names": {"motors": list(self.arm.motors)},
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}
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@property
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def action_feature(self) -> dict:
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return self.state_feature
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@property
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def camera_features(self) -> dict[str, dict]:
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cam_ft = {}
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for cam_key, cam in self.cameras.items():
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cam_ft[cam_key] = {
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"shape": (cam.height, cam.width, cam.channels),
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"names": ["height", "width", "channels"],
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"info": None,
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}
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return cam_ft
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def connect(self) -> None:
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if self.is_connected:
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raise DeviceAlreadyConnectedError(
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"ManipulatorRobot is already connected. Do not run `robot.connect()` twice."
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)
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logging.info("Connecting arm.")
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self.arm.connect()
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# We assume that at connection time, arm is in a rest position,
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# and torque can be safely disabled to run calibration.
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self.arm.write("Torque_Enable", TorqueMode.DISABLED.value)
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self.calibrate()
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# Mode=0 for Position Control
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self.arm.write("Mode", 0)
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# Set P_Coefficient to lower value to avoid shakiness (Default is 32)
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self.arm.write("P_Coefficient", 16)
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# Set I_Coefficient and D_Coefficient to default value 0 and 32
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self.arm.write("I_Coefficient", 0)
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self.arm.write("D_Coefficient", 32)
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# Close the write lock so that Maximum_Acceleration gets written to EPROM address,
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# which is mandatory for Maximum_Acceleration to take effect after rebooting.
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self.arm.write("Lock", 0)
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# Set Maximum_Acceleration to 254 to speedup acceleration and deceleration of
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# the motors. Note: this configuration is not in the official STS3215 Memory Table
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self.arm.write("Maximum_Acceleration", 254)
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self.arm.write("Acceleration", 254)
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logging.info("Activating torque.")
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self.arm.write("Torque_Enable", TorqueMode.ENABLED.value)
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# Check arm can be read
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self.arm.read("Present_Position")
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# Connect the cameras
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for cam in self.cameras.values():
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cam.connect()
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self.is_connected = True
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def calibrate(self) -> None:
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"""After calibration all motors function in human interpretable ranges.
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Rotations are expressed in degrees in nominal range of [-180, 180],
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and linear motions (like gripper of Aloha) in nominal range of [0, 100].
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"""
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arm_calib_path = self.calibration_dir / f"{self.config.id}.json"
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if arm_calib_path.exists():
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with open(arm_calib_path) as f:
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calibration = json.load(f)
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else:
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# TODO(rcadene): display a warning in __init__ if calibration file not available
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logging.info(f"Missing calibration file '{arm_calib_path}'")
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calibration = run_arm_manual_calibration(self.arm, self.robot_type, self.name, "follower")
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logging.info(f"Calibration is done! Saving calibration file '{arm_calib_path}'")
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arm_calib_path.parent.mkdir(parents=True, exist_ok=True)
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with open(arm_calib_path, "w") as f:
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json.dump(calibration, f)
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self.arm.set_calibration(calibration)
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def get_observation(self) -> dict[str, np.ndarray]:
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"""The returned observations do not have a batch dimension."""
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if not self.is_connected:
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raise DeviceNotConnectedError(
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"ManipulatorRobot is not connected. You need to run `robot.connect()`."
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)
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obs_dict = {}
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# Read arm position
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before_read_t = time.perf_counter()
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obs_dict[OBS_STATE] = self.arm.read("Present_Position")
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self.logs["read_pos_dt_s"] = time.perf_counter() - before_read_t
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# Capture images from cameras
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for cam_key, cam in self.cameras.items():
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before_camread_t = time.perf_counter()
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obs_dict[f"{OBS_IMAGES}.{cam_key}"] = cam.async_read()
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self.logs[f"read_camera_{cam_key}_dt_s"] = cam.logs["delta_timestamp_s"]
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self.logs[f"async_read_camera_{cam_key}_dt_s"] = time.perf_counter() - before_camread_t
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return obs_dict
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def send_action(self, action: np.ndarray) -> np.ndarray:
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"""Command arm to move to a target joint configuration.
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The relative action magnitude may be clipped depending on the configuration parameter
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`max_relative_target`. In this case, the action sent differs from original action.
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Thus, this function always returns the action actually sent.
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Args:
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action (np.ndarray): array containing the goal positions for the motors.
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Raises:
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RobotDeviceNotConnectedError: if robot is not connected.
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Returns:
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np.ndarray: the action sent to the motors, potentially clipped.
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"""
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if not self.is_connected:
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raise DeviceNotConnectedError(
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"ManipulatorRobot is not connected. You need to run `robot.connect()`."
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)
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goal_pos = action
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# Cap goal position when too far away from present position.
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# /!\ Slower fps expected due to reading from the follower.
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if self.config.max_relative_target is not None:
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present_pos = self.arm.read("Present_Position")
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goal_pos = ensure_safe_goal_position(goal_pos, present_pos, self.config.max_relative_target)
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# Send goal position to the arm
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self.arm.write("Goal_Position", goal_pos.astype(np.int32))
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return goal_pos
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def print_logs(self):
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# TODO(aliberts): move robot-specific logs logic here
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pass
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def disconnect(self):
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if not self.is_connected:
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raise DeviceNotConnectedError(
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"ManipulatorRobot is not connected. You need to run `robot.connect()` before disconnecting."
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)
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self.arm.disconnect()
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for cam in self.cameras.values():
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cam.disconnect()
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self.is_connected = False
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from dataclasses import dataclass, field
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from lerobot.common.cameras.configs import CameraConfig, OpenCVCameraConfig
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from lerobot.common.motors.configs import FeetechMotorsBusConfig, MotorsBusConfig
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from lerobot.common.robots.config_abc import ManipulatorRobotConfig, RobotConfig
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@RobotConfig.register_subclass("so100")
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@dataclass
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class So100RobotConfig(ManipulatorRobotConfig):
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calibration_dir: str = ".cache/calibration/so100"
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# `max_relative_target` limits the magnitude of the relative positional target vector for safety purposes.
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# Set this to a positive scalar to have the same value for all motors, or a list that is the same length as
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# the number of motors in your follower arms.
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max_relative_target: int | None = None
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leader_arms: dict[str, MotorsBusConfig] = field(
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default_factory=lambda: {
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"main": FeetechMotorsBusConfig(
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port="/dev/tty.usbmodem58760431091",
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motors={
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# name: (index, model)
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"shoulder_pan": [1, "sts3215"],
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"shoulder_lift": [2, "sts3215"],
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"elbow_flex": [3, "sts3215"],
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"wrist_flex": [4, "sts3215"],
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"wrist_roll": [5, "sts3215"],
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"gripper": [6, "sts3215"],
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},
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),
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}
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)
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follower_arms: dict[str, MotorsBusConfig] = field(
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default_factory=lambda: {
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"main": FeetechMotorsBusConfig(
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port="/dev/tty.usbmodem585A0076891",
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motors={
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# name: (index, model)
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"shoulder_pan": [1, "sts3215"],
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"shoulder_lift": [2, "sts3215"],
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"elbow_flex": [3, "sts3215"],
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"wrist_flex": [4, "sts3215"],
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"wrist_roll": [5, "sts3215"],
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"gripper": [6, "sts3215"],
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},
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),
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}
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)
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cameras: dict[str, CameraConfig] = field(
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default_factory=lambda: {
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"laptop": OpenCVCameraConfig(
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camera_index=0,
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fps=30,
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width=640,
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height=480,
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),
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"phone": OpenCVCameraConfig(
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camera_index=1,
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fps=30,
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width=640,
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height=480,
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),
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}
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)
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mock: bool = False
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