136 lines
4.5 KiB
Python
136 lines
4.5 KiB
Python
#!/usr/bin/env python
|
|
|
|
# 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 json
|
|
import logging
|
|
import time
|
|
|
|
import numpy as np
|
|
|
|
from lerobot.common.errors import DeviceAlreadyConnectedError, DeviceNotConnectedError
|
|
from lerobot.common.motors import TorqueMode
|
|
from lerobot.common.motors.feetech import (
|
|
FeetechMotorsBus,
|
|
apply_feetech_offsets_from_calibration,
|
|
run_full_arm_calibration,
|
|
)
|
|
|
|
from ..teleoperator import Teleoperator
|
|
from .configuration_so100 import SO100TeleopConfig
|
|
|
|
|
|
class SO100Teleop(Teleoperator):
|
|
"""
|
|
[SO-100 Leader Arm](https://github.com/TheRobotStudio/SO-ARM100) designed by TheRobotStudio
|
|
"""
|
|
|
|
config_class = SO100TeleopConfig
|
|
name = "so100"
|
|
|
|
def __init__(self, config: SO100TeleopConfig):
|
|
super().__init__(config)
|
|
self.config = config
|
|
self.robot_type = config.type
|
|
|
|
self.arm = FeetechMotorsBus(
|
|
port=self.config.port,
|
|
motors={
|
|
"shoulder_pan": (1, "sts3215"),
|
|
"shoulder_lift": (2, "sts3215"),
|
|
"elbow_flex": (3, "sts3215"),
|
|
"wrist_flex": (4, "sts3215"),
|
|
"wrist_roll": (5, "sts3215"),
|
|
"gripper": (6, "sts3215"),
|
|
},
|
|
)
|
|
|
|
self.is_connected = False
|
|
self.logs = {}
|
|
|
|
@property
|
|
def action_feature(self) -> dict:
|
|
return {
|
|
"dtype": "float32",
|
|
"shape": (len(self.arm),),
|
|
"names": {"motors": list(self.arm.motors)},
|
|
}
|
|
|
|
@property
|
|
def feedback_feature(self) -> dict:
|
|
return {}
|
|
|
|
def connect(self) -> None:
|
|
if self.is_connected:
|
|
raise DeviceAlreadyConnectedError(
|
|
"ManipulatorRobot is already connected. Do not run `robot.connect()` twice."
|
|
)
|
|
|
|
logging.info("Connecting arm.")
|
|
self.arm.connect()
|
|
|
|
# We assume that at connection time, arm is in a rest position,
|
|
# and torque can be safely disabled to run calibration.
|
|
self.arm.write("Torque_Enable", TorqueMode.DISABLED.value)
|
|
self.calibrate()
|
|
|
|
# Check arm can be read
|
|
self.arm.read("Present_Position")
|
|
|
|
self.is_connected = True
|
|
|
|
def calibrate(self) -> None:
|
|
"""After calibration all motors function in human interpretable ranges.
|
|
Rotations are expressed in degrees in nominal range of [-180, 180],
|
|
and linear motions (like gripper of Aloha) in nominal range of [0, 100].
|
|
"""
|
|
if self.calibration_fpath.exists():
|
|
with open(self.calibration_fpath) as f:
|
|
calibration = json.load(f)
|
|
else:
|
|
# TODO(rcadene): display a warning in __init__ if calibration file not available
|
|
logging.info(f"Missing calibration file '{self.calibration_fpath}'")
|
|
calibration = run_full_arm_calibration(self.arm, self.robot_type, self.name, "leader")
|
|
|
|
logging.info(f"Calibration is done! Saving calibration file '{self.calibration_fpath}'")
|
|
self.calibration_fpath.parent.mkdir(parents=True, exist_ok=True)
|
|
with open(self.calibration_fpath, "w") as f:
|
|
json.dump(calibration, f)
|
|
|
|
self.arm.set_calibration(calibration)
|
|
apply_feetech_offsets_from_calibration(self.arm, calibration)
|
|
|
|
def get_action(self) -> np.ndarray:
|
|
"""The returned action does not have a batch dimension."""
|
|
# Read arm position
|
|
before_read_t = time.perf_counter()
|
|
action = self.arm.read("Present_Position")
|
|
self.logs["read_pos_dt_s"] = time.perf_counter() - before_read_t
|
|
|
|
return action
|
|
|
|
def send_feedback(self, feedback: np.ndarray) -> None:
|
|
# TODO(rcadene, aliberts): Implement force feedback
|
|
pass
|
|
|
|
def disconnect(self) -> None:
|
|
if not self.is_connected:
|
|
raise DeviceNotConnectedError(
|
|
"ManipulatorRobot is not connected. You need to run `robot.connect()` before disconnecting."
|
|
)
|
|
|
|
self.arm.disconnect()
|
|
self.is_connected = False
|