mirror of
https://github.com/huggingface/lerobot.git
synced 2026-05-20 02:59:50 +00:00
9183083e75
* refactor(processor): split action from policy, robots and environment - Updated function names to robot_action_to_transition and robot_transition_to_action across multiple files to better reflect their purpose in processing robot actions. - Adjusted references in the RobotProcessorPipeline and related components to ensure compatibility with the new naming convention. - Enhanced type annotations for action parameters to improve code readability and maintainability. * refactor(converters): rename robot_transition_to_action to transition_to_robot_action - Updated function names across multiple files to improve clarity and consistency in processing robot actions. - Adjusted references in RobotProcessorPipeline and related components to align with the new naming convention. - Simplified action handling in the AddBatchDimensionProcessorStep by removing unnecessary checks for action presence. * refactor(converters): update references to transition_to_robot_action - Renamed all instances of robot_transition_to_action to transition_to_robot_action across multiple files for consistency and clarity in the processing of robot actions. - Adjusted the RobotProcessorPipeline configurations to reflect the new naming convention, enhancing code readability. * refactor(processor): update Torch2NumpyActionProcessorStep to extend ActionProcessorStep - Changed the base class of Torch2NumpyActionProcessorStep from PolicyActionProcessorStep to ActionProcessorStep, aligning it with the current architecture of action processing. - This modification enhances the clarity of the class's role in the processing pipeline. * fix(processor): main action processor can take also EnvAction --------- Co-authored-by: Steven Palma <steven.palma@huggingface.co>
82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
# !/usr/bin/env python
|
|
|
|
# Copyright 2025 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 time
|
|
|
|
from lerobot.datasets.lerobot_dataset import LeRobotDataset
|
|
from lerobot.model.kinematics import RobotKinematics
|
|
from lerobot.processor import RobotProcessorPipeline
|
|
from lerobot.processor.converters import robot_action_to_transition, transition_to_robot_action
|
|
from lerobot.robots.so100_follower.config_so100_follower import SO100FollowerConfig
|
|
from lerobot.robots.so100_follower.robot_kinematic_processor import (
|
|
AddRobotObservationAsComplimentaryData,
|
|
InverseKinematicsEEToJoints,
|
|
)
|
|
from lerobot.robots.so100_follower.so100_follower import SO100Follower
|
|
from lerobot.utils.robot_utils import busy_wait
|
|
from lerobot.utils.utils import log_say
|
|
|
|
EPISODE_IDX = 0
|
|
HF_REPO_ID = "<hf_username>/<dataset_repo_id>"
|
|
|
|
robot_config = SO100FollowerConfig(
|
|
port="/dev/tty.usbmodem58760434471", id="my_awesome_follower_arm", use_degrees=True
|
|
)
|
|
robot = SO100Follower(robot_config)
|
|
robot.connect()
|
|
|
|
dataset = LeRobotDataset(HF_REPO_ID, episodes=[EPISODE_IDX])
|
|
actions = dataset.hf_dataset.select_columns("action")
|
|
|
|
# NOTE: It is highly recommended to use the urdf in the SO-ARM100 repo: https://github.com/TheRobotStudio/SO-ARM100/blob/main/Simulation/SO101/so101_new_calib.urdf
|
|
kinematics_solver = RobotKinematics(
|
|
urdf_path="./src/lerobot/teleoperators/sim/so101_new_calib.urdf",
|
|
target_frame_name="gripper_frame_link",
|
|
joint_names=list(robot.bus.motors.keys()),
|
|
)
|
|
|
|
# Build pipeline to convert ee pose action to joint action
|
|
robot_ee_to_joints_processor = RobotProcessorPipeline(
|
|
steps=[
|
|
AddRobotObservationAsComplimentaryData(robot=robot),
|
|
InverseKinematicsEEToJoints(
|
|
kinematics=kinematics_solver,
|
|
motor_names=list(robot.bus.motors.keys()),
|
|
initial_guess_current_joints=False, # Because replay is open loop
|
|
),
|
|
],
|
|
to_transition=robot_action_to_transition,
|
|
to_output=transition_to_robot_action,
|
|
)
|
|
|
|
robot_ee_to_joints_processor.reset()
|
|
|
|
log_say(f"Replaying episode {EPISODE_IDX}")
|
|
for idx in range(dataset.num_frames):
|
|
t0 = time.perf_counter()
|
|
|
|
ee_action = {
|
|
name: float(actions[idx]["action"][i]) for i, name in enumerate(dataset.features["action"]["names"])
|
|
}
|
|
|
|
joint_action = robot_ee_to_joints_processor(ee_action)
|
|
action_sent = robot.send_action(joint_action)
|
|
|
|
busy_wait(1.0 / dataset.fps - (time.perf_counter() - t0))
|
|
|
|
robot.disconnect()
|