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# !/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 RobotAction, RobotObservation, RobotProcessorPipeline
from lerobot.processor.converters import (
robot_action_observation_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 (
InverseKinematicsEEToJoints,
)
from lerobot.robots.so100_follower.so100_follower import SO100Follower
from lerobot.utils.constants import ACTION
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>"
# Initialize the robot config
robot_config = SO100FollowerConfig(
port="/dev/tty.usbmodem5A460814411", id="my_awesome_follower_arm", use_degrees=True
)
# Initialize the robot
robot = SO100Follower(robot_config)
# 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="./SO101/so101_new_calib.urdf",
target_frame_name="gripper_frame_link",
joint_names=list(robot.bus.motors.keys()),
)
# Build pipeline to convert EE action to joints action
robot_ee_to_joints_processor = RobotProcessorPipeline[tuple[RobotAction, RobotObservation], RobotAction](
steps=[
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_observation_to_transition,
to_output=transition_to_robot_action,
)
# Fetch the dataset to replay
dataset = LeRobotDataset(HF_REPO_ID, episodes=[EPISODE_IDX])
# Filter dataset to only include frames from the specified episode since episodes are chunked in dataset V3.0
episode_frames = dataset.hf_dataset.filter(lambda x: x["episode_index"] == EPISODE_IDX)
actions = episode_frames.select_columns(ACTION)
# Connect to the robot
robot.connect()
if not robot.is_connected:
raise ValueError("Robot is not connected!")
print("Starting replay loop...")
log_say(f"Replaying episode {EPISODE_IDX}")
for idx in range(len(episode_frames)):
t0 = time.perf_counter()
# Get recorded action from dataset
ee_action = {
name: float(actions[idx][ACTION][i]) for i, name in enumerate(dataset.features[ACTION]["names"])
}
# Get robot observation
robot_obs = robot.get_observation()
# Dataset EE -> robot joints
joint_action = robot_ee_to_joints_processor((ee_action, robot_obs))
# Send action to robot
_ = robot.send_action(joint_action)
busy_wait(1.0 / dataset.fps - (time.perf_counter() - t0))
# Clean up
robot.disconnect()
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