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Steven Palma
2026-04-14 15:42:04 +02:00
parent cff4bcf4a0
commit 05a2604d6e
27 changed files with 2822 additions and 2751 deletions
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examples/so100_to_so100_EE/record.py
+19 -88
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@@ -17,25 +17,13 @@
from lerobot.cameras.opencv import OpenCVCameraConfig
from lerobot.common.control_utils import init_keyboard_listener
from lerobot.datasets import LeRobotDataset, aggregate_pipeline_dataset_features, create_initial_features
from lerobot.model.kinematics import RobotKinematics
from lerobot.processor import (
RobotProcessorPipeline,
observation_to_transition,
robot_action_observation_to_transition,
transition_to_observation,
transition_to_robot_action,
)
from lerobot.datasets import LeRobotDataset
from lerobot.processor import make_default_processors
from lerobot.robots.so_follower import SO100Follower, SO100FollowerConfig
from lerobot.robots.so_follower.robot_kinematic_processor import (
EEBoundsAndSafety,
ForwardKinematicsJointsToEE,
InverseKinematicsEEToJoints,
)
from lerobot.scripts.lerobot_record import record_loop
from lerobot.teleoperators.so_leader import SO100Leader, SO100LeaderConfig
from lerobot.types import RobotAction, RobotObservation
from lerobot.utils.feature_utils import combine_feature_dicts
from lerobot.utils.constants import ACTION, OBS_STR
from lerobot.utils.feature_utils import hw_to_dataset_features
from lerobot.utils.utils import log_say
from lerobot.utils.visualization_utils import init_rerun
@@ -62,77 +50,16 @@ def main():
follower = SO100Follower(follower_config)
leader = SO100Leader(leader_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
follower_kinematics_solver = RobotKinematics(
urdf_path="./SO101/so101_new_calib.urdf",
target_frame_name="gripper_frame_link",
joint_names=list(follower.bus.motors.keys()),
)
# 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
leader_kinematics_solver = RobotKinematics(
urdf_path="./SO101/so101_new_calib.urdf",
target_frame_name="gripper_frame_link",
joint_names=list(leader.bus.motors.keys()),
)
# Build pipeline to convert follower joints to EE observation
follower_joints_to_ee = RobotProcessorPipeline[RobotObservation, RobotObservation](
steps=[
ForwardKinematicsJointsToEE(
kinematics=follower_kinematics_solver, motor_names=list(follower.bus.motors.keys())
),
],
to_transition=observation_to_transition,
to_output=transition_to_observation,
)
# Build pipeline to convert leader joints to EE action
leader_joints_to_ee = RobotProcessorPipeline[tuple[RobotAction, RobotObservation], RobotAction](
steps=[
ForwardKinematicsJointsToEE(
kinematics=leader_kinematics_solver, motor_names=list(leader.bus.motors.keys())
),
],
to_transition=robot_action_observation_to_transition,
to_output=transition_to_robot_action,
)
# Build pipeline to convert EE action to follower joints
ee_to_follower_joints = RobotProcessorPipeline[tuple[RobotAction, RobotObservation], RobotAction](
[
EEBoundsAndSafety(
end_effector_bounds={"min": [-1.0, -1.0, -1.0], "max": [1.0, 1.0, 1.0]},
max_ee_step_m=0.10,
),
InverseKinematicsEEToJoints(
kinematics=follower_kinematics_solver,
motor_names=list(follower.bus.motors.keys()),
initial_guess_current_joints=True,
),
],
to_transition=robot_action_observation_to_transition,
to_output=transition_to_robot_action,
)
# Configure the dataset features
action_features = hw_to_dataset_features(follower.action_features, ACTION)
obs_features = hw_to_dataset_features(follower.observation_features, OBS_STR)
dataset_features = {**action_features, **obs_features}
# Create the dataset
dataset = LeRobotDataset.create(
repo_id=HF_REPO_ID,
fps=FPS,
features=combine_feature_dicts(
# Run the feature contract of the pipelines
# This tells you how the features would look like after the pipeline steps
aggregate_pipeline_dataset_features(
pipeline=leader_joints_to_ee,
initial_features=create_initial_features(action=leader.action_features),
use_videos=True,
),
aggregate_pipeline_dataset_features(
pipeline=follower_joints_to_ee,
initial_features=create_initial_features(observation=follower.observation_features),
use_videos=True,
),
),
features=dataset_features,
robot_type=follower.name,
use_videos=True,
image_writer_threads=4,
@@ -150,6 +77,10 @@ def main():
if not leader.is_connected or not follower.is_connected:
raise ValueError("Robot or teleop is not connected!")
teleop_action_processor, robot_action_processor, robot_observation_processor = (
make_default_processors()
)
print("Starting record loop...")
episode_idx = 0
while episode_idx < NUM_EPISODES and not events["stop_recording"]:
@@ -160,14 +91,14 @@ def main():
robot=follower,
events=events,
fps=FPS,
teleop_action_processor=teleop_action_processor,
robot_action_processor=robot_action_processor,
robot_observation_processor=robot_observation_processor,
teleop=leader,
dataset=dataset,
control_time_s=EPISODE_TIME_SEC,
single_task=TASK_DESCRIPTION,
display_data=True,
teleop_action_processor=leader_joints_to_ee,
robot_action_processor=ee_to_follower_joints,
robot_observation_processor=follower_joints_to_ee,
)
# Reset the environment if not stopping or re-recording
@@ -179,13 +110,13 @@ def main():
robot=follower,
events=events,
fps=FPS,
teleop_action_processor=teleop_action_processor,
robot_action_processor=robot_action_processor,
robot_observation_processor=robot_observation_processor,
teleop=leader,
control_time_s=RESET_TIME_SEC,
single_task=TASK_DESCRIPTION,
display_data=True,
teleop_action_processor=leader_joints_to_ee,
robot_action_processor=ee_to_follower_joints,
robot_observation_processor=follower_joints_to_ee,
)
if events["rerecord_episode"]: