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feat(scripts): lerobot-rollout
This commit is contained in:
Steven Palma
committed by
Steven Palma
Steven Palma
parent
5c43fa1cce
commit
bc06cb44ca
@@ -14,13 +14,17 @@
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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 logging
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import time
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from lerobot.cameras.opencv import OpenCVCameraConfig
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from lerobot.common.control_utils import init_keyboard_listener
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from lerobot.common.control_utils import init_keyboard_listener, predict_action
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from lerobot.configs import FeatureType, PolicyFeature
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from lerobot.datasets import LeRobotDataset, aggregate_pipeline_dataset_features, create_initial_features
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from lerobot.model.kinematics import RobotKinematics
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from lerobot.policies import make_pre_post_processors
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from lerobot.policies.act import ACTPolicy
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from lerobot.policies.utils import make_robot_action
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from lerobot.processor import (
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RobotProcessorPipeline,
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make_default_teleop_action_processor,
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@@ -34,11 +38,12 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
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ForwardKinematicsJointsToEE,
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InverseKinematicsEEToJoints,
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)
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from lerobot.scripts.lerobot_record import record_loop
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from lerobot.types import RobotAction, RobotObservation
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from lerobot.utils.feature_utils import combine_feature_dicts
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from lerobot.utils.constants import ACTION, OBS_STR
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from lerobot.utils.feature_utils import build_dataset_frame, combine_feature_dicts
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from lerobot.utils.robot_utils import precise_sleep
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from lerobot.utils.utils import log_say
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from lerobot.utils.visualization_utils import init_rerun
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from lerobot.utils.visualization_utils import init_rerun, log_rerun_data
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NUM_EPISODES = 5
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FPS = 30
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@@ -49,6 +54,9 @@ HF_DATASET_ID = "<hf_username>/<dataset_repo_id>"
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def main():
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# NOTE: For production policy deployment, use `lerobot-rollout` CLI instead.
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# This script provides a self-contained example for educational purposes.
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# Create the robot configuration & robot
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camera_config = {"front": OpenCVCameraConfig(index_or_path=0, width=640, height=480, fps=FPS)}
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robot_config = SO100FollowerConfig(
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@@ -143,43 +151,67 @@ def main():
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raise ValueError("Robot is not connected!")
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print("Starting evaluate loop...")
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control_interval = 1 / FPS
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episode_idx = 0
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for episode_idx in range(NUM_EPISODES):
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log_say(f"Running inference, recording eval episode {episode_idx + 1} of {NUM_EPISODES}")
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# Main record loop
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record_loop(
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robot=robot,
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events=events,
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fps=FPS,
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policy=policy,
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preprocessor=preprocessor, # Pass the pre and post policy processors
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postprocessor=postprocessor,
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dataset=dataset,
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control_time_s=EPISODE_TIME_SEC,
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single_task=TASK_DESCRIPTION,
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display_data=True,
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teleop_action_processor=make_default_teleop_action_processor(),
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robot_action_processor=robot_ee_to_joints_processor,
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robot_observation_processor=robot_joints_to_ee_pose_processor,
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)
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# Inline evaluation loop: predict actions and send to robot
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timestamp = 0
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start_episode_t = time.perf_counter()
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while timestamp < EPISODE_TIME_SEC:
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start_loop_t = time.perf_counter()
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if events["exit_early"]:
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events["exit_early"] = False
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break
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# Get robot observation
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obs = robot.get_observation()
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obs_processed = robot_joints_to_ee_pose_processor(obs)
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observation_frame = build_dataset_frame(dataset.features, obs_processed, prefix=OBS_STR)
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# Predict action using the policy
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action_tensor = predict_action(
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observation=observation_frame,
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policy=policy,
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device=policy.config.device,
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preprocessor=preprocessor,
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postprocessor=postprocessor,
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use_amp=policy.config.device.type == "cuda",
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task=TASK_DESCRIPTION,
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robot_type=robot.name,
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)
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# Convert policy output to robot action dict
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action_values = make_robot_action(action_tensor, dataset.features)
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# Process and send action to robot (EE -> joints via IK)
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robot_action_to_send = robot_ee_to_joints_processor((action_values, obs))
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robot.send_action(robot_action_to_send)
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# Write to dataset
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action_frame = build_dataset_frame(dataset.features, action_values, prefix=ACTION)
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frame = {**observation_frame, **action_frame, "task": TASK_DESCRIPTION}
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dataset.add_frame(frame)
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log_rerun_data(observation=obs_processed, action=action_values)
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dt_s = time.perf_counter() - start_loop_t
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sleep_time_s = control_interval - dt_s
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if sleep_time_s < 0:
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logging.warning(
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f"Evaluate loop is running slower ({1 / dt_s:.1f} Hz) than the target FPS ({FPS} Hz)."
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)
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precise_sleep(max(sleep_time_s, 0.0))
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timestamp = time.perf_counter() - start_episode_t
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# Reset the environment if not stopping or re-recording
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if not events["stop_recording"] and (
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(episode_idx < NUM_EPISODES - 1) or events["rerecord_episode"]
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):
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log_say("Reset the environment")
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record_loop(
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robot=robot,
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events=events,
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fps=FPS,
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control_time_s=EPISODE_TIME_SEC,
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single_task=TASK_DESCRIPTION,
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display_data=True,
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teleop_action_processor=make_default_teleop_action_processor(),
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robot_action_processor=robot_ee_to_joints_processor,
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robot_observation_processor=robot_joints_to_ee_pose_processor,
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)
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log_say("Waiting for environment reset, press right arrow key when ready...")
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if events["rerecord_episode"]:
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log_say("Re-record episode")
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@@ -190,7 +222,6 @@ def main():
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# Save episode
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dataset.save_episode()
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episode_idx += 1
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finally:
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# Clean up
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log_say("Stop recording")
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