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Sonic VLA data exporter for G1 -- NO ROS 2 DEPENDENCY.
All data sources use ZMQ:
1. Robot state -> ZMQ SUB on ``g1_debug`` topic (port 5557, from C++ zmq_output_handler)
2. SMPL pose -> ZMQ SUB on ``pose`` topic (port 5556, from pico_manager_thread_server)
3. Camera -> ZMQ/TCP via ComposedCameraClientSensor
Robot config (``script_config`` in info.json) is read from the ``robot_config``
ZMQ topic re-published every ~2 s by the C++ process. If the config is not
received within the timeout the exporter exits with an error.
Virtual environment setup (run from repo root):
bash install_scripts/install_data_collection.sh
source .venv_data_collection/bin/activate
Usage (from repo root):
python gear_sonic/scripts/run_data_exporter.py --task-prompt "pick up the cup"
python gear_sonic/scripts/run_data_exporter.py --task-prompt "walk forward" --dataset-name my_session
"""
from collections import deque
from dataclasses import dataclass
from datetime import datetime
import json
import time
import numpy as np
from scipy.spatial.transform import Rotation as R
import tyro
import zmq
from gear_sonic.data.exporter import Gr00tDataExporter
from gear_sonic.data.features_sonic_vla import (
get_features_sonic_vla,
get_g1_robot_model,
get_modality_config_sonic_vla,
get_wrist_camera_features,
get_wrist_camera_modality_config,
)
from gear_sonic.camera.composed_camera import ComposedCameraClientSensor
from gear_sonic.utils.data_collection.episode_state import EpisodeState
from gear_sonic.utils.data_collection.keyboard_subscriber import ZMQKeyboardSubscriber
from gear_sonic.utils.data_collection.telemetry import Telemetry
from gear_sonic.utils.data_collection.text_to_speech import TextToSpeech
from gear_sonic.utils.data_collection.transforms import compute_projected_gravity, quat_to_rot6d
from gear_sonic.utils.data_collection.zmq_state_subscriber import (
ZMQStateSubscriber,
poll_robot_config_zmq,
)
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
@dataclass
class SonicDataExporterConfig:
"""CLI config for the ROS-free Sonic data exporter."""
# Dataset
dataset_name: str | None = None
"""Dataset name (auto-generated if creating new)."""
task_prompt: str = "demo"
"""Language task prompt."""
root_output_dir: str = "outputs"
"""Root output directory."""
data_collection_frequency: int = 50
"""Data collection frequency (Hz)."""
# Camera
camera_host: str = "localhost"
"""Camera server host."""
camera_port: int = 5555
"""Camera server port."""
# ZMQ: Sonic / SMPL pose (from pico_manager_thread_server)
sonic_zmq_host: str = "localhost"
"""ZMQ host for Sonic SMPL pose messages."""
sonic_zmq_port: int = 5556
"""ZMQ port for Sonic SMPL pose messages."""
# ZMQ: Robot state (from C++ zmq_output_handler, g1_debug topic)
state_zmq_host: str = "localhost"
"""ZMQ host for robot state (g1_debug topic from C++ deploy)."""
state_zmq_port: int = 5557
"""ZMQ port for robot state (same socket as robot_config topic)."""
# Robot config
robot_config_timeout: float = 0
"""Seconds to wait for the ZMQ robot_config message at startup (0 = wait forever)."""
record_wrist_cameras: bool = False
"""Record wrist camera streams (left_wrist, right_wrist). Requires cameras to be available."""
text_to_speech: bool = True
"""Use text-to-speech voice feedback."""
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
class TimeDeltaException(Exception):
def __init__(self, failure_count: int, reset_timeout_sec: float):
self.failure_count = failure_count
self.reset_timeout_sec = reset_timeout_sec
self.message = f"{self.failure_count} failures in {self.reset_timeout_sec} seconds"
super().__init__(self.message)
def unpack_pose_message(packed_data: bytes, topic: str = "pose") -> dict:
"""Unpack a single-frame packed message from pico_manager_thread_server.
Wire format: [topic_prefix][1280-byte JSON header][concatenated binary fields]
"""
HEADER_SIZE = 1280
topic_bytes = topic.encode("utf-8")
if not packed_data.startswith(topic_bytes):
raise ValueError(f"Message does not start with expected topic '{topic}'")
offset = len(topic_bytes)
if len(packed_data) < offset + HEADER_SIZE:
raise ValueError(f"Packed data too small: {len(packed_data)} < {offset + HEADER_SIZE}")
header_bytes = packed_data[offset : offset + HEADER_SIZE]
null_idx = header_bytes.find(b"\x00")
if null_idx > 0:
header_bytes = header_bytes[:null_idx]
header = json.loads(header_bytes.decode("utf-8"))
fields = header.get("fields", [])
result = {"version": header.get("v", 0), "endian": header.get("endian", "le")}
current_offset = offset + HEADER_SIZE
dtype_map = {
"f32": np.float32,
"f64": np.float64,
"i32": np.int32,
"i64": np.int64,
"bool": bool,
}
for field in fields:
dtype = dtype_map.get(field["dtype"], np.float32)
shape = tuple(field["shape"])
n_bytes = int(np.prod(shape)) * np.dtype(dtype).itemsize
result[field["name"]] = (
np.frombuffer(packed_data[current_offset : current_offset + n_bytes], dtype=dtype)
.reshape(shape)
.copy()
)
current_offset += n_bytes
return result
class TimingThresholdMonitor:
def __init__(self, max_failures=3, reset_timeout_sec=5, time_delta=0.2, raise_exception=False):
self.max_failures = max_failures
self.reset_timeout_sec = reset_timeout_sec
self.failure_count = 0
self.last_failure_time = 0
self.time_delta = time_delta
self.raise_exception = raise_exception
def reset(self):
self.failure_count = 0
self.last_failure_time = 0
def log_time_delta(self, time_delta_sec: float):
time_delta = abs(time_delta_sec)
if time_delta > self.time_delta:
self.failure_count += 1
self.last_failure_time = time.monotonic()
if self.is_threshold_exceeded():
print(
f"Time delta exception: {self.failure_count} failures in "
f"{self.reset_timeout_sec} seconds, time delta: {time_delta}"
)
if self.raise_exception:
raise TimeDeltaException(self.failure_count, self.reset_timeout_sec)
def is_threshold_exceeded(self):
if self.failure_count >= self.max_failures:
return True
if time.monotonic() - self.last_failure_time > self.reset_timeout_sec:
self.reset()
return False
# ---------------------------------------------------------------------------
# Data Collector
# ---------------------------------------------------------------------------
class GrootDataCollector:
"""Collects data from G1 robot in Sonic CPP + SMPL mode -- no ROS 2.
Data sources (all ZMQ):
- ``g1_debug`` topic -> proprio (body_q, hand_q, actions, base_quat, ...)
- ``pose`` topic -> SMPL pose (smpl_joints, body_quat_w, hand_joints, ...)
- ``planner`` topic -> planner commands (vr_position, vr_orientation, ...)
- ``manager_state`` topic -> current stream mode + toggle flags
- Camera client -> ego-view images
"""
def __init__(
self,
camera_host: str,
camera_port: int,
data_exporter: Gr00tDataExporter,
robot_model,
text_to_speech=None,
frequency: int = 20,
sonic_data_zmq_host: str = "localhost",
sonic_data_zmq_port: int = 5556,
state_zmq_host: str = "localhost",
state_zmq_port: int = 5557,
):
self.text_to_speech = text_to_speech
self.frequency = frequency
self.loop_period = 1.0 / frequency
self.data_exporter = data_exporter
self.robot_model = robot_model
self._episode_state = EpisodeState()
self._keyboard_listener = ZMQKeyboardSubscriber()
self._image_subscriber = ComposedCameraClientSensor(server_ip=camera_host, port=camera_port)
self.obs_act_buffer = deque(maxlen=100)
self.latest_image_msg = None
self.latest_proprio_msg = None
self.latest_sonic_msg = None
self.latest_planner_msg = None
self.current_stream_mode = 0
self._manager_toggle_dc = False
self._manager_toggle_da = False
self._state_subscriber = ZMQStateSubscriber(
host=state_zmq_host,
port=state_zmq_port,
)
self._sonic_zmq_ctx = None
self._sonic_zmq_socket = None
try:
self._sonic_zmq_ctx = zmq.Context()
self._sonic_zmq_socket = self._sonic_zmq_ctx.socket(zmq.SUB)
self._sonic_zmq_socket.connect(f"tcp://{sonic_data_zmq_host}:{sonic_data_zmq_port}")
self._sonic_zmq_socket.setsockopt(zmq.RCVTIMEO, 100)
self._sonic_zmq_socket.setsockopt(zmq.CONFLATE, 0)
self._sonic_zmq_socket.setsockopt(zmq.RCVHWM, 20)
self._sonic_zmq_socket.setsockopt_string(zmq.SUBSCRIBE, "pose")
self._sonic_zmq_socket.setsockopt_string(zmq.SUBSCRIBE, "planner")
self._sonic_zmq_socket.setsockopt_string(zmq.SUBSCRIBE, "manager_state")
time.sleep(0.5)
print(f"[Sonic] Connected to ZMQ at {sonic_data_zmq_host}:{sonic_data_zmq_port}")
print("[Sonic] Subscribed to: pose, planner, manager_state")
except Exception as e:
print(f"[Sonic] Warning: Failed to initialize ZMQ subscriber: {e}")
self._sonic_zmq_socket = None
self.telemetry = Telemetry(window_size=100)
self.sonic_timing_monitor = TimingThresholdMonitor(
max_failures=3, reset_timeout_sec=5, time_delta=0.1
)
self._last_latency_log_time = 0.0
self._initial_yaw = None
print(f"Recording to {self.data_exporter.meta.root}")
@property
def current_episode_index(self):
return self.data_exporter.episode_buffer["episode_index"]
def _print_and_say(self, message: str, say: bool = True, blocking: bool = False):
if self.text_to_speech is not None:
self.text_to_speech.print_and_say(message, say, blocking=blocking)
else:
print(message)
def _poll_state_zmq(self):
"""Poll the ``g1_debug`` ZMQ topic for robot state (non-blocking)."""
msg = self._state_subscriber.get_msg(clear=True)
if msg is None:
return
if msg.get("ros_timestamp", 0.0) == 0.0:
msg["ros_timestamp"] = time.time()
self.latest_proprio_msg = msg
def _check_recording_commands(self):
"""Check keyboard + ZMQ toggle flags for recording commands."""
key = self._keyboard_listener.read_msg()
if self._manager_toggle_da:
key = "x"
self._manager_toggle_da = False
elif self._manager_toggle_dc:
key = "c"
self._manager_toggle_dc = False
if key == "c":
self._episode_state.change_state()
if self._episode_state.get_state() == self._episode_state.RECORDING:
self._initial_yaw = None
self._print_and_say(
f"Started recording {self.current_episode_index}", blocking=False
)
elif self._episode_state.get_state() == self._episode_state.NEED_TO_SAVE:
self._print_and_say("Stopping recording, preparing to save", blocking=False)
elif self._episode_state.get_state() == self._episode_state.IDLE:
self._print_and_say("Saved episode and back to idle state", blocking=False)
elif key == "x":
if self._episode_state.get_state() == self._episode_state.RECORDING:
self.data_exporter.save_episode_as_discarded()
self._episode_state.reset_state()
self._initial_yaw = None
self._print_and_say("Discarded episode", blocking=False)
def _poll_sonic_zmq_messages(self):
"""Poll ZMQ for pose, planner, and manager_state messages (non-blocking)."""
if self._sonic_zmq_socket is None:
return
max_polls = 20
for _ in range(max_polls):
try:
raw = self._sonic_zmq_socket.recv(zmq.NOBLOCK)
except zmq.Again:
break
if raw.startswith(b"manager_state"):
self._handle_manager_state(raw)
elif raw.startswith(b"planner"):
self._handle_planner_message(raw)
elif raw.startswith(b"pose"):
self._handle_pose_message(raw)
def _handle_manager_state(self, raw: bytes) -> None:
try:
data = unpack_pose_message(raw, topic="manager_state")
except Exception:
return
if "stream_mode" in data:
self.current_stream_mode = int(data["stream_mode"].flat[0])
if self._extract_bool(data, "toggle_data_collection"):
self._manager_toggle_dc = True
if self._extract_bool(data, "toggle_data_abort"):
self._manager_toggle_da = True
def _handle_planner_message(self, raw: bytes) -> None:
try:
data = unpack_pose_message(raw, topic="planner")
except Exception:
return
planner_mode = int(data["mode"].flat[0]) if "mode" in data else 0
planner_movement = (
data["movement"].flatten().astype(np.float32)
if "movement" in data and data["movement"].size == 3
else np.zeros(3, dtype=np.float32)
)
planner_facing = (
data["facing"].flatten().astype(np.float32)
if "facing" in data and data["facing"].size == 3
else np.array([1.0, 0.0, 0.0], dtype=np.float32)
)
planner_speed = float(data["speed"].flat[0]) if "speed" in data else -1.0
planner_height = float(data["height"].flat[0]) if "height" in data else -1.0
vr_3pt_position = None
if "vr_position" in data and data["vr_position"].size == 9:
vr_3pt_position = data["vr_position"].flatten().astype(np.float32)
vr_3pt_orientation = None
if "vr_orientation" in data and data["vr_orientation"].size == 12:
vr_3pt_orientation = data["vr_orientation"].flatten().astype(np.float32)
self.latest_planner_msg = {
"planner_mode": planner_mode,
"planner_movement": planner_movement,
"planner_facing": planner_facing,
"planner_speed": planner_speed,
"planner_height": planner_height,
"vr_3pt_position": vr_3pt_position,
"vr_3pt_orientation": vr_3pt_orientation,
"left_hand_joints": self._extract_hand_joints(data, "left_hand_joints"),
"right_hand_joints": self._extract_hand_joints(data, "right_hand_joints"),
"receive_timestamp": time.time(),
}
def _handle_pose_message(self, raw: bytes) -> None:
G1_L_WRIST_ROLL_IDX = 23
G1_L_WRIST_PITCH_IDX = 25
G1_L_WRIST_YAW_IDX = 27
G1_R_WRIST_ROLL_IDX = 24
G1_R_WRIST_PITCH_IDX = 26
G1_R_WRIST_YAW_IDX = 28
try:
pose_data = unpack_pose_message(raw, topic="pose")
except Exception as e:
print(f"[Sonic] Error unpacking pose message: {e}")
return
try:
if "smpl_joints" not in pose_data or len(pose_data["smpl_joints"].shape) != 3:
return
left_wrist_joints = None
right_wrist_joints = None
if "joint_pos" in pose_data and len(pose_data["joint_pos"].shape) == 2:
joint_pos = pose_data["joint_pos"][0]
left_wrist_joints = np.array(
[
joint_pos[G1_L_WRIST_ROLL_IDX],
joint_pos[G1_L_WRIST_PITCH_IDX],
joint_pos[G1_L_WRIST_YAW_IDX],
],
dtype=np.float32,
)
right_wrist_joints = np.array(
[
joint_pos[G1_R_WRIST_ROLL_IDX],
joint_pos[G1_R_WRIST_PITCH_IDX],
joint_pos[G1_R_WRIST_YAW_IDX],
],
dtype=np.float32,
)
frame_index = None
if "frame_index" in pose_data:
frame_index = np.array([pose_data["frame_index"].flat[0]], dtype=np.int64)
smpl_pose = np.zeros(63, dtype=np.float32)
if "smpl_pose" in pose_data:
raw_pose = pose_data["smpl_pose"]
if raw_pose.ndim == 3:
smpl_pose = raw_pose[0].flatten().astype(np.float32)
elif raw_pose.ndim == 2:
smpl_pose = raw_pose.flatten().astype(np.float32)
elif raw_pose.ndim == 1 and raw_pose.size == 63:
smpl_pose = raw_pose.astype(np.float32)
left_hand_joints = self._extract_hand_joints(pose_data, "left_hand_joints")
right_hand_joints = self._extract_hand_joints(pose_data, "right_hand_joints")
vr_3pt_position = None
if "vr_position" in pose_data and pose_data["vr_position"].size == 9:
vr_3pt_position = pose_data["vr_position"].flatten().astype(np.float32)
vr_3pt_orientation = None
if "vr_orientation" in pose_data and pose_data["vr_orientation"].size == 12:
vr_3pt_orientation = pose_data["vr_orientation"].flatten().astype(np.float32)
self.latest_sonic_msg = {
"smpl_joints": pose_data["smpl_joints"][0],
"smpl_pose": smpl_pose,
"body_quat_w": (
pose_data["body_quat_w"][0] if "body_quat_w" in pose_data else None
),
"left_hand_joints": left_hand_joints,
"right_hand_joints": right_hand_joints,
"left_wrist_joints": left_wrist_joints,
"right_wrist_joints": right_wrist_joints,
"vr_3pt_position": vr_3pt_position,
"vr_3pt_orientation": vr_3pt_orientation,
"frame_index": frame_index,
"receive_timestamp": time.time(),
}
except Exception as e:
if not hasattr(self, "_sonic_error_count"):
self._sonic_error_count = 0
self._sonic_error_count += 1
if self._sonic_error_count == 1 or self._sonic_error_count % 100 == 0:
print(f"[Sonic] Error processing pose message: {e}")
@staticmethod
def _extract_hand_joints(pose_data: dict, key: str) -> np.ndarray:
arr = pose_data.get(key)
if arr is not None:
if arr.ndim > 1:
arr = arr[0]
return arr.astype(np.float32)
return np.zeros(7, dtype=np.float32)
@staticmethod
def _extract_bool(pose_data: dict, key: str) -> bool:
val = pose_data.get(key)
if val is None:
return False
if isinstance(val, np.ndarray):
return bool(val.flat[0])
return bool(val)
def _log_latency_periodic(
self,
sonic_latency_ms: float | None = None,
):
current_time = time.time()
if current_time - self._last_latency_log_time >= 1.0:
self._last_latency_log_time = current_time
parts = []
if sonic_latency_ms is not None:
parts.append(f"Sonic Pose: {sonic_latency_ms:.1f}ms")
if parts:
print(f"[Latency] {', '.join(parts)}")
def _add_images_to_frame_data(self, frame_data: dict) -> None:
if self.latest_image_msg is None:
return
images = self.latest_image_msg["images"]
for feature_name, feature_info in self.data_exporter.features.items():
if feature_info.get("dtype") in ["image", "video"]:
image_key = feature_name.split(".")[-1]
if image_key not in images:
raise ValueError(
f"Required image '{image_key}' for feature '{feature_name}' "
f"not found in image message. Available: {list(images.keys())}"
)
frame_data[feature_name] = images[image_key]
def _finalize_frame(self, t_start: float) -> bool:
t_end = time.monotonic()
if t_end - t_start > (1 / self.frequency):
print(f"DataExporter Missed: {t_end - t_start} sec")
if self._episode_state.get_state() == self._episode_state.NEED_TO_SAVE:
buffer_size = self.data_exporter.episode_buffer.get("size", 0)
if buffer_size > 0:
self.data_exporter.save_episode()
self.sonic_timing_monitor.reset()
self._initial_yaw = None
self._print_and_say("Finished saving episode")
else:
self._print_and_say("Skipping save: no frames collected", say=False)
self._episode_state.change_state()
return True
def _add_data_frame(self):
t_start = time.monotonic()
if self.latest_proprio_msg is None or self.latest_image_msg is None:
self._print_and_say(
f"Waiting for message. "
f"Avail msg: proprio {self.latest_proprio_msg is not None} | "
f"image {self.latest_image_msg is not None}",
say=False,
)
return False
if self._episode_state.get_state() != self._episode_state.RECORDING:
return self._finalize_frame(t_start)
return self._add_data_frame_sonic(t_start)
def _add_data_frame_sonic(self, t_start: float) -> bool:
"""Build one data frame in Sonic CPP + SMPL mode."""
assert self.latest_proprio_msg is not None
proprio = self.latest_proprio_msg
whole_q = self.robot_model.get_configuration_from_actuated_joints(
body_actuated_joint_values=proprio["body_q"],
left_hand_actuated_joint_values=proprio["left_hand_q"],
right_hand_actuated_joint_values=proprio["right_hand_q"],
)
whole_action_wbc = self.robot_model.get_configuration_from_actuated_joints(
body_actuated_joint_values=proprio["last_action"],
left_hand_actuated_joint_values=proprio["last_left_hand_action"],
right_hand_actuated_joint_values=proprio["last_right_hand_action"],
)
self.robot_model.cache_forward_kinematics(whole_q)
eef_parts = []
for side in ["left", "right"]:
placement = self.robot_model.frame_placement(
self.robot_model.supplemental_info.hand_frame_names[side]
)
pos = placement.translation[:3]
quat = R.from_matrix(placement.rotation).as_quat(scalar_first=True)
eef_parts.append(np.concatenate([pos, quat]))
observation_eef_state = np.concatenate(eef_parts)
frame_data: dict = {
"observation.state": whole_q,
"observation.eef_state": observation_eef_state,
"action.wbc": whole_action_wbc,
}
self._add_cpp_state_features(frame_data, proprio)
sonic_latency_ms = self._add_sonic_pose_features(frame_data)
self._add_images_to_frame_data(frame_data)
self._log_latency_periodic(sonic_latency_ms)
self.data_exporter.add_frame(frame_data)
return self._finalize_frame(t_start)
def _add_cpp_state_features(self, frame_data: dict, proprio: dict) -> None:
if "base_quat" in proprio:
base_quat = np.asarray(proprio["base_quat"], dtype=np.float64)
frame_data["observation.root_orientation"] = base_quat
frame_data["observation.projected_gravity"] = compute_projected_gravity(
base_quat
).astype(np.float64)
if "init_ref_data_root_rot_array" in proprio:
frame_data["observation.cpp_rotation_offset"] = np.asarray(
proprio["init_ref_data_root_rot_array"], dtype=np.float64
)
else:
frame_data["observation.cpp_rotation_offset"] = np.array(
[1.0, 0.0, 0.0, 0.0], dtype=np.float64
)
else:
frame_data["observation.root_orientation"] = np.array(
[1.0, 0.0, 0.0, 0.0], dtype=np.float64
)
frame_data["observation.projected_gravity"] = np.array(
[0.0, 0.0, -1.0], dtype=np.float64
)
frame_data["observation.cpp_rotation_offset"] = np.array(
[1.0, 0.0, 0.0, 0.0], dtype=np.float64
)
if "init_base_quat" in proprio:
frame_data["observation.init_base_quat"] = np.asarray(
proprio["init_base_quat"], dtype=np.float64
)
else:
frame_data["observation.init_base_quat"] = np.array(
[1.0, 0.0, 0.0, 0.0], dtype=np.float64
)
if "delta_heading" in proprio:
dh = proprio["delta_heading"]
if isinstance(dh, np.ndarray):
dh = dh.item() if dh.size == 1 else dh[0]
frame_data["teleop.delta_heading"] = np.array([float(dh)], dtype=np.float64)
else:
frame_data["teleop.delta_heading"] = np.zeros(1, dtype=np.float64)
if "token_state" in proprio:
frame_data["action.motion_token"] = np.asarray(proprio["token_state"], dtype=np.float64)
else:
frame_data["action.motion_token"] = np.zeros(64, dtype=np.float64)
def _add_sonic_pose_features(self, frame_data: dict) -> float | None:
"""Add teleop features based on current stream mode."""
sonic_latency_ms = None
frame_data["teleop.stream_mode"] = np.array([self.current_stream_mode], dtype=np.int32)
smpl_msg = self.latest_sonic_msg
use_smpl = False
if self.current_stream_mode in (1, 4) and smpl_msg is not None:
receive_ts = smpl_msg.get("receive_timestamp")
if receive_ts is not None:
age_sec = time.time() - receive_ts
sonic_latency_ms = age_sec * 1000
self.sonic_timing_monitor.log_time_delta(age_sec)
if sonic_latency_ms <= 100.0:
use_smpl = True
elif (self.sonic_timing_monitor.failure_count + 1) % 10 == 0:
self._print_and_say(
f"Sonic pose stale ({sonic_latency_ms:.1f}ms old), using zeros",
say=False,
)
else:
use_smpl = True
planner_msg = self.latest_planner_msg
use_planner = False
if self.current_stream_mode == 5 and planner_msg is not None:
receive_ts = planner_msg.get("receive_timestamp")
if receive_ts is not None:
age_sec = time.time() - receive_ts
planner_latency_ms = age_sec * 1000
if sonic_latency_ms is None:
sonic_latency_ms = planner_latency_ms
if planner_latency_ms <= 200.0:
use_planner = True
else:
use_planner = True
# SMPL features
if use_smpl and smpl_msg.get("smpl_joints") is not None:
joints = np.asarray(smpl_msg["smpl_joints"], dtype=np.float32)
if joints.ndim == 2:
joints = joints.flatten()
frame_data["teleop.smpl_joints"] = np.ascontiguousarray(joints, dtype=np.float32)
else:
frame_data["teleop.smpl_joints"] = np.zeros(72, dtype=np.float32)
if use_smpl and smpl_msg.get("smpl_pose") is not None:
pose = np.asarray(smpl_msg["smpl_pose"], dtype=np.float32)
if pose.ndim > 1:
pose = pose.flatten()
frame_data["teleop.smpl_pose"] = np.ascontiguousarray(pose, dtype=np.float32)
else:
frame_data["teleop.smpl_pose"] = np.zeros(63, dtype=np.float32)
if use_smpl and smpl_msg.get("body_quat_w") is not None:
body_quat_w = smpl_msg["body_quat_w"].astype(np.float32)
frame_data["teleop.body_quat_w"] = body_quat_w
frame_data["teleop.target_body_orientation"] = self._compute_target_body_orientation(
body_quat_w, frame_data
)
else:
frame_data["teleop.body_quat_w"] = np.array([1.0, 0.0, 0.0, 0.0], dtype=np.float32)
frame_data["teleop.target_body_orientation"] = quat_to_rot6d(
np.array([1.0, 0.0, 0.0, 0.0], dtype=np.float32)
)
frame_data["teleop.left_wrist_joints"] = (
smpl_msg["left_wrist_joints"].astype(np.float32)
if use_smpl and smpl_msg.get("left_wrist_joints") is not None
else np.zeros(3, dtype=np.float32)
)
frame_data["teleop.right_wrist_joints"] = (
smpl_msg["right_wrist_joints"].astype(np.float32)
if use_smpl and smpl_msg.get("right_wrist_joints") is not None
else np.zeros(3, dtype=np.float32)
)
frame_data["teleop.smpl_frame_index"] = (
smpl_msg["frame_index"].astype(np.int64)
if use_smpl and smpl_msg is not None and smpl_msg.get("frame_index") is not None
else np.array([0], dtype=np.int64)
)
hand_msg = (
smpl_msg if self.current_stream_mode in (1, 4) and smpl_msg is not None
else planner_msg if planner_msg is not None
else smpl_msg
)
frame_data["teleop.left_hand_joints"] = (
hand_msg["left_hand_joints"].astype(np.float32)
if hand_msg is not None
and hand_msg.get("left_hand_joints") is not None
else np.zeros(7, dtype=np.float32)
)
frame_data["teleop.right_hand_joints"] = (
hand_msg["right_hand_joints"].astype(np.float32)
if hand_msg is not None
and hand_msg.get("right_hand_joints") is not None
else np.zeros(7, dtype=np.float32)
)
# Planner command fields
frame_data["teleop.planner_mode"] = np.array(
[planner_msg["planner_mode"]] if use_planner else [0],
dtype=np.int32,
)
frame_data["teleop.planner_movement"] = (
planner_msg["planner_movement"].copy()
if use_planner and planner_msg.get("planner_movement") is not None
else np.zeros(3, dtype=np.float32)
)
frame_data["teleop.planner_facing"] = (
planner_msg["planner_facing"].copy()
if use_planner and planner_msg.get("planner_facing") is not None
else np.array([1.0, 0.0, 0.0], dtype=np.float32)
)
frame_data["teleop.planner_speed"] = np.array(
[planner_msg["planner_speed"]] if use_planner else [-1.0],
dtype=np.float32,
)
frame_data["teleop.planner_height"] = np.array(
[planner_msg["planner_height"]] if use_planner else [-1.0],
dtype=np.float32,
)
# VR 3-point pose
frame_data["teleop.vr_3pt_position"] = (
planner_msg["vr_3pt_position"].astype(np.float32)
if use_planner and planner_msg.get("vr_3pt_position") is not None
else np.zeros(9, dtype=np.float32)
)
if use_planner and planner_msg.get("vr_3pt_orientation") is not None:
frame_data["teleop.vr_3pt_orientation"] = quat_to_rot6d(
planner_msg["vr_3pt_orientation"].astype(np.float32)
)
else:
frame_data["teleop.vr_3pt_orientation"] = np.zeros(18, dtype=np.float32)
return sonic_latency_ms
def _compute_target_body_orientation(
self, body_quat_w: np.ndarray, frame_data: dict
) -> np.ndarray:
"""Compute yaw-normalised target body orientation as rot6d (6-dim)."""
delta_heading = float(frame_data.get("teleop.delta_heading", [0.0])[0])
body_rot = R.from_quat(body_quat_w, scalar_first=True)
target_rot = R.from_euler("z", delta_heading, degrees=False) * body_rot
euler = target_rot.as_euler("ZYX", degrees=False)
current_yaw = euler[0]
if self._initial_yaw is None:
self._initial_yaw = current_yaw
normalised_euler = np.array([current_yaw - self._initial_yaw, euler[1], euler[2]])
target_quat = (
R.from_euler("ZYX", normalised_euler, degrees=False)
.as_quat(scalar_first=True)
.astype(np.float32)
)
return quat_to_rot6d(target_quat)
def save_and_cleanup(self):
try:
self._print_and_say("saving episode done", blocking=False)
buffer_size = self.data_exporter.episode_buffer.get("size", 0)
if buffer_size > 0:
self.data_exporter.save_episode()
self._print_and_say(
f"Recording complete: {self.data_exporter.meta.root}", say=False, blocking=True
)
except Exception as e:
self._print_and_say(f"Error saving episode: {e}", blocking=True)
try:
self._state_subscriber.close()
except Exception:
pass
for sock in [self._sonic_zmq_socket]:
if sock is not None:
try:
sock.close()
except Exception:
pass
for ctx in [self._sonic_zmq_ctx]:
if ctx is not None:
try:
ctx.term()
except Exception:
pass
self._print_and_say("Shutting down data exporter...", say=False)
def run(self):
try:
while True:
t_start = time.monotonic()
with self.telemetry.timer("total_loop"):
with self.telemetry.timer("poll_state"):
self._poll_state_zmq()
with self.telemetry.timer("poll_sonic"):
self._poll_sonic_zmq_messages()
with self.telemetry.timer("poll_image"):
img_msg = self._image_subscriber.read()
if img_msg is not None:
self.latest_image_msg = img_msg
with self.telemetry.timer("add_frame"):
self._add_data_frame()
with self.telemetry.timer("check_recording_commands"):
self._check_recording_commands()
end_time = time.monotonic()
elapsed = time.monotonic() - t_start
sleep_time = self.loop_period - elapsed
if sleep_time > 0:
time.sleep(sleep_time)
if (end_time - t_start) > self.loop_period:
self.telemetry.log_timing_info(
context="Data Exporter Loop Missed", threshold=0.001
)
except KeyboardInterrupt:
print("Data exporter terminated by user")
buffer_size = self.data_exporter.episode_buffer.get("size", 0)
if buffer_size > 0:
self.data_exporter.save_episode_as_discarded()
finally:
self.save_and_cleanup()
# ---------------------------------------------------------------------------
# Entry point
# ---------------------------------------------------------------------------
def main(config: SonicDataExporterConfig):
g1_rm = get_g1_robot_model()
dataset_features = get_features_sonic_vla(g1_rm)
modality_config = get_modality_config_sonic_vla(g1_rm)
if config.record_wrist_cameras:
print("[Camera] Wrist cameras enabled — adding to dataset schema")
dataset_features.update(get_wrist_camera_features())
wrist_modality = get_wrist_camera_modality_config()
for key, value in wrist_modality.items():
if key in modality_config:
modality_config[key].update(value)
else:
modality_config[key] = value
text_to_speech = TextToSpeech() if config.text_to_speech else None
robot_config = poll_robot_config_zmq(
config.state_zmq_host, config.state_zmq_port, config.robot_config_timeout
)
data_exporter = Gr00tDataExporter.create(
save_root=f"{config.root_output_dir}/{config.dataset_name}",
fps=config.data_collection_frequency,
features=dataset_features,
modality_config=modality_config,
task=config.task_prompt,
script_config={**robot_config, "record_wrist_cameras": config.record_wrist_cameras},
)
data_collector = GrootDataCollector(
frequency=config.data_collection_frequency,
data_exporter=data_exporter,
robot_model=g1_rm,
camera_host=config.camera_host,
camera_port=config.camera_port,
text_to_speech=text_to_speech,
sonic_data_zmq_host=config.sonic_zmq_host,
sonic_data_zmq_port=config.sonic_zmq_port,
state_zmq_host=config.state_zmq_host,
state_zmq_port=config.state_zmq_port,
)
data_collector.run()
if __name__ == "__main__":
config = tyro.cli(SonicDataExporterConfig)
if config.dataset_name is None:
config.dataset_name = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
main(config)
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