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import argparse
import threading
import time
from collections import deque
import sys
import termios
import tty
import select
import cv2
import numpy as np
import rospy
import torch
from cv_bridge import CvBridge
from geometry_msgs.msg import Twist
from nav_msgs.msg import Odometry
from openpi_client import image_tools, websocket_client_policy
from piper_msgs.msg import PosCmd
from sensor_msgs.msg import Image, JointState
from std_msgs.msg import Header
import os
import dm_env
import collections
from deploy.data_collection.collect_data import save_data
CAMERA_NAMES = ["cam_high", "cam_right_wrist", "cam_left_wrist"]
observation_window = None
stream_buffer = None
# inference data collection control
inference_collection_active = False
inference_collection_lock = threading.Lock()
# save-data control
save_data_requested = False
save_data_lock = threading.Lock()
lang_embeddings = "Pick and sort bricks on the conveyor."
RIGHT_OFFSET = 0.003
class InferenceDataCollector:
"""Inference-mode data collector that saves episodes classified as success or failure."""
def __init__(self, camera_names, dataset_dir="./data", task_name=None):
self.camera_names = camera_names
self.dataset_dir = dataset_dir
self.task_name = task_name
self.is_collecting = False
self.timesteps = []
self.actions = []
self.frame_count = 0
self.episode_idx_success = 0
self.episode_idx_fail = 0
self.full_dataset_dir = None
def _find_next_episode_idx(self, subdir_name):
"""Find next available episode index in the given subdirectory."""
if self.full_dataset_dir is None:
return 0
subdir_path = os.path.join(self.full_dataset_dir, subdir_name)
if not os.path.exists(subdir_path):
os.makedirs(subdir_path, exist_ok=True)
print(f"Created directory: {subdir_path}")
return 0
existing = [
f for f in os.listdir(subdir_path)
if f.startswith('episode_') and f.endswith('.hdf5')
]
if existing:
indices = [int(f.split('_')[1].split('.')[0]) for f in existing]
return max(indices) + 1
return 0
def update_episode_indices(self):
"""Update episode indices for success and fail subdirectories."""
self.episode_idx_success = self._find_next_episode_idx('aloha_mobile_success')
self.episode_idx_fail = self._find_next_episode_idx('aloha_mobile_fail')
print(f"Next success episode: {self.episode_idx_success}")
print(f"Next fail episode: {self.episode_idx_fail}")
def start_collection(self):
"""Start collecting frames and actions."""
self.is_collecting = True
self.timesteps = []
self.actions = []
self.frame_count = 0
print(f"\n{'='*70}")
print("Data collection started!")
print(f" Save dir: {self.full_dataset_dir}")
print(f" Success idx: {self.episode_idx_success} | Fail idx: {self.episode_idx_fail}")
print(f" Press 's' to stop and save")
print(f"{'='*70}\n")
def add_frame(self, observation, action):
"""Add one frame of observation and action data."""
if not self.is_collecting:
return
self.frame_count += 1
step_type = dm_env.StepType.FIRST if self.frame_count == 1 else dm_env.StepType.MID
self.timesteps.append(dm_env.TimeStep(
step_type=step_type, reward=None, discount=None, observation=observation
))
self.actions.append(action)
if self.frame_count % 50 == 0:
print(f"Collected {self.frame_count} frames")
def save_current_episode(self, export_video=True, video_fps=30,
video_codec='libx264', video_quality=23):
"""Stop collection and save episode after asking user for success/fail classification."""
if len(self.actions) == 0:
print("\033[31m❌ No data collected, cannot save\033[0m")
return False
print(f"\n{'='*70}")
print("❓ Was this episode a success or failure?")
print(" Press '1' → Success (save to aloha_mobile_success)")
print(" Press '0' → Failure (save to aloha_mobile_fail)")
print(f"{'='*70}")
local_settings = termios.tcgetattr(sys.stdin)
try:
tty.setcbreak(sys.stdin.fileno())
is_success = None
subdir_name = None
episode_idx = None
while True:
if select.select([sys.stdin], [], [], 0.1)[0]:
char = sys.stdin.read(1)
if char == '1':
is_success = True
subdir_name = 'aloha_mobile_success'
episode_idx = self.episode_idx_success
print("\n✅ Marked as [Success]")
break
elif char == '0':
is_success = False
subdir_name = 'aloha_mobile_fail'
episode_idx = self.episode_idx_fail
print("\n❌ Marked as [Failure]")
break
else:
print(f"⚠️ Invalid input '{char}', press '1' or '0'")
finally:
termios.tcsetattr(sys.stdin, termios.TCSADRAIN, local_settings)
if is_success is None:
print("\n❌ No valid input, cancelling save")
return False
save_dir = os.path.join(self.full_dataset_dir, subdir_name)
os.makedirs(save_dir, exist_ok=True)
dataset_path = os.path.join(save_dir, f"episode_{episode_idx}")
print(f"\n💾 Saving Episode {episode_idx} to {subdir_name}...")
print(f" Frames: {len(self.actions)}")
class _Args:
def __init__(self, camera_names, export_video, video_fps, video_codec, video_quality):
self.camera_names = camera_names
self.export_video = export_video
self.video_fps = video_fps
self.video_codec = video_codec
self.video_quality = video_quality
self.use_robot_base = False
_args = _Args(self.camera_names, export_video, video_fps, video_codec, video_quality)
try:
save_data(_args, self.timesteps, self.actions, dataset_path)
print(f"\n\033[32m✅ Episode {episode_idx} saved!\033[0m")
print(f" Path: {dataset_path}.hdf5")
if is_success:
self.episode_idx_success += 1
else:
self.episode_idx_fail += 1
self.timesteps = []
self.actions = []
self.frame_count = 0
self.is_collecting = False
print(f"\n{'='*70}")
print("✅ Save complete")
print(f" Next success episode: {self.episode_idx_success}")
print(f" Next fail episode: {self.episode_idx_fail}")
print(f"{'='*70}\n")
return True
except Exception as e:
print(f"\033[31m❌ Save failed: {e}\033[0m")
import traceback
traceback.print_exc()
return False
def get_frame_count(self):
return self.frame_count
def has_data(self):
return len(self.actions) > 0
def keyboard_monitor_thread():
"""Background thread: press 's' to trigger data save and exit."""
global save_data_requested
original_settings = None
try:
original_settings = termios.tcgetattr(sys.stdin)
tty.setcbreak(sys.stdin.fileno())
while not rospy.is_shutdown():
if select.select([sys.stdin], [], [], 0.1)[0]:
char = sys.stdin.read(1)
if char.lower() == 's':
with save_data_lock:
save_data_requested = True
print("\n" + "💾" * 35)
print("💾 Save requested, stopping collection...")
print("💾" * 35 + "\n")
finally:
if original_settings is not None:
try:
termios.tcsetattr(sys.stdin, termios.TCSADRAIN, original_settings)
except Exception:
pass
class StreamActionBuffer:
"""
Maintains a chunk queue for actions and the current smoothed execution sequence.
integrate_new_chunk supports latency trimming and linear overlap blending.
"""
def __init__(self, max_chunks=10, decay_alpha=0.25, state_dim=14, smooth_method="temporal"):
self.chunks = deque()
self.max_chunks = max_chunks
self.lock = threading.Lock()
self.decay_alpha = float(decay_alpha)
self.state_dim = state_dim
self.smooth_method = smooth_method
self.cur_chunk = deque()
self.k = 0
self.last_action = None
def integrate_new_chunk(self, actions_chunk: np.ndarray, max_k: int, min_m: int = 8):
with self.lock:
if actions_chunk is None or len(actions_chunk) == 0:
return
max_k = max(0, int(max_k))
min_m = max(1, int(min_m))
drop_n = min(self.k, max_k)
if drop_n >= len(actions_chunk):
return
new_chunk = [a.copy() for a in actions_chunk[drop_n:]]
if len(self.cur_chunk) == 0 and self.last_action is not None:
old_list = [np.asarray(self.last_action, dtype=float).copy() for _ in range(min_m)]
self.last_action = None
else:
old_list = list(self.cur_chunk)
if len(old_list) > 0 and len(old_list) < min_m:
tail = np.asarray(old_list[-1], dtype=float).copy()
old_list.extend([tail.copy() for _ in range(min_m - len(old_list))])
elif len(old_list) == 0:
self.cur_chunk = deque(new_chunk, maxlen=None)
self.k = 0
return
new_list = list(new_chunk)
overlap_len = min(len(old_list), len(new_list))
if overlap_len <= 0:
self.cur_chunk = deque(new_list, maxlen=None)
self.k = 0
return
if len(old_list) > len(new_list):
old_list = old_list[:len(new_list)]
overlap_len = len(new_list)
w_old = np.array([1.0], dtype=float) if overlap_len == 1 else np.linspace(1.0, 0.0, overlap_len, dtype=float)
w_new = 1.0 - w_old
smoothed = [
(w_old[i] * np.asarray(old_list[i], dtype=float) +
w_new[i] * np.asarray(new_list[i], dtype=float))
for i in range(overlap_len)
]
self.cur_chunk = deque([a.copy() for a in smoothed + new_list[overlap_len:]], maxlen=None)
self.k = 0
def pop_next_action(self) -> np.ndarray | None:
with self.lock:
if len(self.cur_chunk) == 0:
return None
if len(self.cur_chunk) == 1:
self.last_action = np.asarray(self.cur_chunk[0], dtype=float).copy()
act = np.asarray(self.cur_chunk.popleft(), dtype=float)
self.k += 1
return act
def start_inference_thread(args, config, policy, ros_operator):
th = threading.Thread(target=inference_fn_non_blocking_fast, args=(args, config, policy, ros_operator))
th.daemon = True
th.start()
def inference_fn_non_blocking_fast(args, config, policy, ros_operator):
global stream_buffer
rate = rospy.Rate(getattr(args, "inference_rate", 4))
while not rospy.is_shutdown():
try:
update_observation_window(args, config, ros_operator)
latest_obs = observation_window[-1]
imgs = [
latest_obs["images"][config["camera_names"][0]],
latest_obs["images"][config["camera_names"][1]],
latest_obs["images"][config["camera_names"][2]],
]
imgs = [cv2.cvtColor(im, cv2.COLOR_BGR2RGB) for im in imgs]
imgs = image_tools.resize_with_pad(np.array(imgs), 224, 224)
proprio = latest_obs["qpos"]
payload = {
"state": proprio,
"images": {
"top_head": imgs[0].transpose(2, 0, 1),
"hand_right": imgs[1].transpose(2, 0, 1),
"hand_left": imgs[2].transpose(2, 0, 1),
},
"prompt": lang_embeddings,
}
actions = policy.infer(payload)["actions"]
if actions is not None and len(actions) > 0:
max_k = int(getattr(args, "latency_k", 0))
min_m = int(getattr(args, "min_smooth_steps", 8))
stream_buffer.integrate_new_chunk(actions, max_k=max_k, min_m=min_m)
try:
rate.sleep()
except Exception:
pass
except Exception:
try:
rate.sleep()
except Exception:
time.sleep(0.005)
continue
def set_seed(seed):
torch.manual_seed(seed)
np.random.seed(seed)
class SimpleKalmanFilter:
def __init__(self, process_variance=1e-6, measurement_variance=1e-7, initial_value=None):
self.process_variance = process_variance
self.measurement_variance = measurement_variance
self.estimate = initial_value
self.error_estimate = 1.0
def update(self, measurement):
if self.estimate is None:
self.estimate = measurement.copy()
return self.estimate
# Compute Kalman gain
kalman_gain = self.error_estimate / (self.error_estimate + self.measurement_variance)
# Update estimate
self.estimate = self.estimate + kalman_gain * (measurement - self.estimate)
# Update error estimate
self.error_estimate = (1 - kalman_gain) * self.error_estimate + abs(self.estimate - measurement) * self.process_variance
return self.estimate
def interpolate_action(args, prev_action, cur_action):
steps = np.concatenate((np.array(args.arm_steps_length), np.array(args.arm_steps_length)), axis=0)
diff = np.abs(cur_action - prev_action)
step = np.ceil(diff / steps).astype(int)
step = np.max(step)
if step <= 1:
return cur_action[np.newaxis, :]
new_actions = np.linspace(prev_action, cur_action, step + 1)
return new_actions[1:]
def minimum_jerk_interpolation(args, prev_action, cur_action):
num_steps = args.jerk_num_steps
t_normalized = np.linspace(0, 1, num_steps + 1)[1:]
trajectory = []
for tau in t_normalized:
factor = 10 * (tau ** 3) - 15 * (tau ** 4) + 6 * (tau ** 5)
trajectory.append(prev_action + factor * (cur_action - prev_action))
return np.array(trajectory)
def get_config(args):
return {
"episode_len": args.max_publish_step,
"state_dim": 14,
"chunk_size": args.chunk_size,
"camera_names": CAMERA_NAMES,
}
def get_ros_observation(args, ros_operator):
rate = rospy.Rate(args.publish_rate)
print_flag = True
# max wait time; fall back to cached frame to avoid blocking upstream
max_wait_s = 0.6
start_t = time.time()
while True and not rospy.is_shutdown():
# non-destructive peek to avoid competing with other consumers
result = ros_operator.get_frame_peek()
if not result:
# timeout exceeded; use cached frame if available
if (time.time() - start_t) > max_wait_s and ros_operator.last_frame_cache is not None:
if print_flag:
print("syn timeout, using last cached frame in get_ros_observation")
print_flag = False
(img_front, img_left, img_right, _, _, _, puppet_arm_left, puppet_arm_right, _) = \
ros_operator.last_frame_cache
return (img_front, img_left, img_right, puppet_arm_left, puppet_arm_right)
if print_flag:
print("syn fail when get_ros_observation")
print_flag = False
rate.sleep()
continue
print_flag = True
(img_front, img_left, img_right, _, _, _, puppet_arm_left, puppet_arm_right, _) = result
return (img_front, img_left, img_right, puppet_arm_left, puppet_arm_right)
def update_observation_window(args, config, ros_operator):
# JPEG transformation — align with training
def jpeg_mapping(img):
img = cv2.imencode(".jpg", img)[1].tobytes()
img = cv2.imdecode(np.frombuffer(img, np.uint8), cv2.IMREAD_COLOR)
return img
global observation_window
if observation_window is None:
observation_window = deque(maxlen=2)
# Append the first dummy image
observation_window.append({
"qpos": None,
"images": {
config["camera_names"][0]: None,
config["camera_names"][1]: None,
config["camera_names"][2]: None,
},
})
img_front, img_left, img_right, puppet_arm_left, puppet_arm_right = \
get_ros_observation(args, ros_operator)
img_front = jpeg_mapping(img_front)
img_left = jpeg_mapping(img_left)
img_right = jpeg_mapping(img_right)
qpos = np.concatenate(
(np.array(puppet_arm_left.position), np.array(puppet_arm_right.position)), axis=0
)
observation_window.append({
"qpos": qpos,
"images": {
config["camera_names"][0]: img_front,
config["camera_names"][1]: img_right,
config["camera_names"][2]: img_left,
},
})
def inference_fn(args, config, policy):
global observation_window
global lang_embeddings
while True and not rospy.is_shutdown():
time1 = time.time()
# fetch images in sequence [front, right, left]
image_arrs = [
observation_window[-1]["images"][config["camera_names"][0]],
observation_window[-1]["images"][config["camera_names"][1]],
observation_window[-1]["images"][config["camera_names"][2]],
]
# convert BGR to RGB
image_arrs = [cv2.cvtColor(img, cv2.COLOR_BGR2RGB) for img in image_arrs]
image_arrs = image_tools.resize_with_pad(np.array(image_arrs), 224, 224)
# get last qpos in shape [14,]
proprio = observation_window[-1]["qpos"]
payload = {
"state": proprio,
"images": {
"top_head": image_arrs[0].transpose(2, 0, 1),
"hand_right": image_arrs[1].transpose(2, 0, 1),
"hand_left": image_arrs[2].transpose(2, 0, 1),
},
"prompt": lang_embeddings,
}
# actions shaped as [chunk, 14] in format [left, right]
actions = policy.infer(payload)["actions"]
print(f"Model inference time: {(time.time() - time1)*1000:.3f} ms")
return actions
def model_inference(args, config, ros_operator):
global lang_embeddings
global save_data_requested
global inference_collection_active
global stream_buffer
policy = websocket_client_policy.WebsocketClientPolicy(args.host, args.port)
kalman_filters = [SimpleKalmanFilter() for _ in range(config["state_dim"])]
print(f"Server metadata: {policy.get_server_metadata()}")
max_publish_step = config["episode_len"]
chunk_size = config["chunk_size"]
# Initialize puppet arm position
left0 = [0, 0.32, -0.36, 0, 0.24, 0, 0.07]
right0 = [0, 0.32, -0.36, 0, 0.24, 0, 0.07]
ros_operator.puppet_arm_publish_continuous(left0, right0)
# Initialize inference data collector
data_collector = InferenceDataCollector(
camera_names=['cam_high', 'cam_left_wrist', 'cam_right_wrist'],
dataset_dir=args.dataset_dir,
task_name="inference_collect",
)
data_collector.full_dataset_dir = os.path.join(args.dataset_dir, "aloha_mobile")
os.makedirs(data_collector.full_dataset_dir, exist_ok=True)
data_collector.update_episode_indices()
# Start keyboard monitor thread
keyboard_thread = threading.Thread(target=keyboard_monitor_thread, daemon=True)
keyboard_thread.start()
print("\n" + "="*70)
print("✅ Keyboard monitor started")
print(" Press 's' → Stop and save episode")
print("="*70 + "\n")
time.sleep(0.3)
print("\n" + "="*70)
print("🤖 Robot arms reset to initial position")
print("="*70)
input("Press [Enter] to start inference and data collection...")
print("\n" + "="*70)
print("🚀 Starting inference and data collection...")
print(" Press 's' to stop and save")
print("="*70 + "\n")
# Start collection
data_collector.start_collection()
with inference_collection_lock:
inference_collection_active = True
pre_action = np.zeros(config["state_dim"])
action = None
with torch.inference_mode():
while True and not rospy.is_shutdown():
t = 0
rate = rospy.Rate(args.publish_rate)
action_buffer = np.zeros([chunk_size, config["state_dim"]])
last_stream_act = None
while t < max_publish_step and not rospy.is_shutdown():
# check if save was requested
with save_data_lock:
if save_data_requested:
with inference_collection_lock:
if inference_collection_active and data_collector.has_data():
print("\n" + "💾" * 35)
print("💾 Stopping and saving data...")
print("💾" * 35 + "\n")
ros_operator.open_grippers()
time.sleep(1.0)
print("✅ Grippers opened\n")
data_collector.save_current_episode(
export_video=getattr(args, 'export_video', True),
video_fps=getattr(args, 'video_fps', 30),
video_codec=getattr(args, 'video_codec', 'libx264'),
video_quality=getattr(args, 'video_quality', 23),
)
print("\n" + "✅" * 35)
print("✅ Data saved, exiting...")
print("✅" * 35 + "\n")
rospy.signal_shutdown("Data saved, exiting...")
return
else:
print("\n⚠️ No data to save\n")
save_data_requested = False
# ── temporal smoothing execution path ──────────────────────
if args.use_temporal_smoothing:
if stream_buffer is None:
stream_buffer = StreamActionBuffer(
max_chunks=args.buffer_max_chunks,
decay_alpha=args.exp_decay_alpha,
state_dim=config["state_dim"],
smooth_method="temporal",
)
start_inference_thread(args, config, policy, ros_operator)
act = stream_buffer.pop_next_action()
if act is not None:
if args.ctrl_type == "joint":
left_action = act[:7].copy()
right_action = act[7:14].copy()
left_action[6] = max(0.0, left_action[6] - RIGHT_OFFSET)
right_action[6] = max(0.0, right_action[6] - RIGHT_OFFSET)
ros_operator.puppet_arm_publish(left_action, right_action)
# collect inference data
with inference_collection_lock:
is_collecting = inference_collection_active and data_collector.is_collecting
if is_collecting:
try:
result = ros_operator.get_frame_peek()
if result:
(img_front, img_left, img_right, _, _, _,
puppet_arm_left, puppet_arm_right, _) = result
observation = collections.OrderedDict()
observation['images'] = {
'cam_high': img_front.copy(),
'cam_left_wrist': img_left.copy(),
'cam_right_wrist': img_right.copy(),
}
observation['qpos'] = np.concatenate(
(puppet_arm_left.position, puppet_arm_right.position)
).copy()
observation['qvel'] = np.zeros(14)
observation['effort'] = np.zeros(14)
observation['base_vel'] = [0.0, 0.0]
action_to_save = np.concatenate([left_action, right_action]).copy()
data_collector.add_frame(observation, action_to_save)
except Exception as e:
rospy.logwarn(f"[inference collect] frame error: {e}")
elif args.ctrl_type == "eef":
ros_operator.endpose_publish(act[:7], act[7:14])
last_stream_act = act.copy()
else:
if last_stream_act is not None:
if args.ctrl_type == "joint":
ros_operator.puppet_arm_publish(last_stream_act[:7], last_stream_act[7:14])
elif args.ctrl_type == "eef":
ros_operator.endpose_publish(last_stream_act[:7], last_stream_act[7:14])
rate.sleep()
t += 1
if t % 50 == 0:
print(f"Step {t} | Recording: {data_collector.get_frame_count()} frames | Press 's' to save")
continue
# ── non-temporal-smoothing path (blocking chunk mode) ──────
update_observation_window(args, config, ros_operator)
if t % chunk_size == 0:
action_buffer = inference_fn(args, config, policy).copy()
raw_action = action_buffer[t % chunk_size]
if args.use_kalman_filter:
action = np.array([kf.update(raw_action[i]) for i, kf in enumerate(kalman_filters)])
else:
action = raw_action
if args.use_actions_interpolation:
if args.interpolate_method == "linear":
interp_actions = interpolate_action(args, pre_action, action)
elif args.interpolate_method == "minimum_jerk":
interp_actions = minimum_jerk_interpolation(args, pre_action, action)
else:
raise NotImplementedError
else:
interp_actions = action[np.newaxis, :]
for act in interp_actions:
if args.ctrl_type == "joint":
left_action = act[:7]
right_action = act[7:14]
if args.gripper_threshold:
if left_action[-1] < 0.03: left_action[-1] = 0
if right_action[-1] < 0.03: right_action[-1] = 0
ros_operator.puppet_arm_publish(left_action, right_action)
elif args.ctrl_type == "eef":
ros_operator.endpose_publish(act[:7], act[7:14])
if args.use_robot_base:
ros_operator.robot_base_publish(act[14:16])
rate.sleep()
t += 1
if t % 50 == 0:
print(f"Published Step {t}")
pre_action = action.copy()
class RosOperator:
def __init__(self, args):
self.robot_base_deque = None
self.puppet_arm_right_deque = None
self.puppet_arm_left_deque = None
self.img_front_deque = None
self.img_right_deque = None
self.img_left_deque = None
self.img_front_depth_deque = None
self.img_right_depth_deque = None
self.img_left_depth_deque = None
self.bridge = None
self.puppet_arm_left_publisher = None
self.puppet_arm_right_publisher = None
self.endpose_left_publisher = None
self.endpose_right_publisher = None
self.robot_base_publisher = None
self.puppet_arm_publish_thread = None
self.puppet_arm_publish_lock = None
self.args = args
self.last_frame_cache = None
self.init()
self.init_ros()
def init(self):
self.bridge = CvBridge()
self.img_left_deque = deque()
self.img_right_deque = deque()
self.img_front_deque = deque()
self.img_left_depth_deque = deque()
self.img_right_depth_deque = deque()
self.img_front_depth_deque = deque()
self.puppet_arm_left_deque = deque()
self.puppet_arm_right_deque = deque()
self.robot_base_deque = deque()
self.puppet_arm_publish_lock = threading.Lock()
self.puppet_arm_publish_lock.acquire()
def open_grippers(self):
left_arm = list(self.puppet_arm_left_deque[-1].position)
right_arm = list(self.puppet_arm_right_deque[-1].position)
left_arm[6] = 1.0
right_arm[6] = 1.0
self.puppet_arm_publish(left_arm, right_arm)
print("Grippers opened.")
def puppet_arm_publish(self, left, right):
joint_state_msg = JointState()
joint_state_msg.header = Header()
joint_state_msg.header.stamp = rospy.Time.now()
joint_state_msg.name = ["joint0", "joint1", "joint2", "joint3", "joint4", "joint5", "joint6"]
joint_state_msg.position = left
self.puppet_arm_left_publisher.publish(joint_state_msg)
joint_state_msg.position = right
self.puppet_arm_right_publisher.publish(joint_state_msg)
def endpose_publish(self, left, right):
endpose_msg = PosCmd()
endpose_msg.x, endpose_msg.y, endpose_msg.z = left[:3]
endpose_msg.roll, endpose_msg.pitch, endpose_msg.yaw = left[3:6]
endpose_msg.gripper = left[6]
self.endpose_left_publisher.publish(endpose_msg)
endpose_msg.x, endpose_msg.y, endpose_msg.z = right[:3]
endpose_msg.roll, endpose_msg.pitch, endpose_msg.yaw = right[3:6]
endpose_msg.gripper = right[6]
self.endpose_right_publisher.publish(endpose_msg)
def robot_base_publish(self, vel):
vel_msg = Twist()
vel_msg.linear.x = vel[0]
vel_msg.linear.y = 0
vel_msg.linear.z = 0
vel_msg.angular.x = 0
vel_msg.angular.y = 0
vel_msg.angular.z = vel[1]
self.robot_base_publisher.publish(vel_msg)
def puppet_arm_publish_continuous(self, left, right):
rate = rospy.Rate(self.args.publish_rate)
left_arm = right_arm = None
while True and not rospy.is_shutdown():
if len(self.puppet_arm_left_deque) != 0: left_arm = list(self.puppet_arm_left_deque[-1].position)
if len(self.puppet_arm_right_deque) != 0: right_arm = list(self.puppet_arm_right_deque[-1].position)
if left_arm is None or right_arm is None:
rate.sleep()
continue
else:
break
left_symbol = [1 if left[i] - left_arm[i] > 0 else -1 for i in range(len(left))]
right_symbol = [1 if right[i] - right_arm[i] > 0 else -1 for i in range(len(right))]
flag = True
step = 0
while flag and not rospy.is_shutdown():
if self.puppet_arm_publish_lock.acquire(False):
return
left_diff = [abs(left[i] - left_arm[i]) for i in range(len(left))]
right_diff = [abs(right[i] - right_arm[i]) for i in range(len(right))]
flag = False
for i in range(len(left)):
if left_diff[i] < self.args.arm_steps_length[i]:
left_arm[i] = left[i]
else:
left_arm[i] += left_symbol[i] * self.args.arm_steps_length[i]
flag = True
for i in range(len(right)):
if right_diff[i] < self.args.arm_steps_length[i]:
right_arm[i] = right[i]
else:
right_arm[i] += right_symbol[i] * self.args.arm_steps_length[i]
flag = True
joint_state_msg = JointState()
joint_state_msg.header = Header()
joint_state_msg.header.stamp = rospy.Time.now()
joint_state_msg.name = ["joint0", "joint1", "joint2", "joint3", "joint4", "joint5", "joint6"]
joint_state_msg.position = left_arm
self.puppet_arm_left_publisher.publish(joint_state_msg)
joint_state_msg.position = right_arm
self.puppet_arm_right_publisher.publish(joint_state_msg)
step += 1
print("puppet_arm_publish_continuous:", step)
rate.sleep()
def puppet_arm_publish_linear(self, left, right):
num_step = 100
rate = rospy.Rate(200)
left_arm = right_arm = None
while True and not rospy.is_shutdown():
if len(self.puppet_arm_left_deque) != 0: left_arm = list(self.puppet_arm_left_deque[-1].position)
if len(self.puppet_arm_right_deque) != 0: right_arm = list(self.puppet_arm_right_deque[-1].position)
if left_arm is None or right_arm is None:
rate.sleep()
continue
else:
break
traj_left_list = np.linspace(left_arm, left, num_step)
traj_right_list = np.linspace(right_arm, right, num_step)
for i in range(len(traj_left_list)):
traj_left = traj_left_list[i]
traj_right = traj_right_list[i]
traj_left[-1] = left[-1]
traj_right[-1] = right[-1]
joint_state_msg = JointState()
joint_state_msg.header = Header()
joint_state_msg.header.stamp = rospy.Time.now()
joint_state_msg.name = ["joint0", "joint1", "joint2", "joint3", "joint4", "joint5", "joint6"]
joint_state_msg.position = traj_left
self.puppet_arm_left_publisher.publish(joint_state_msg)
joint_state_msg.position = traj_right
self.puppet_arm_right_publisher.publish(joint_state_msg)
rate.sleep()
def puppet_arm_publish_continuous_thread(self, left, right):
if self.puppet_arm_publish_thread is not None:
self.puppet_arm_publish_lock.release()
self.puppet_arm_publish_thread.join()
self.puppet_arm_publish_lock.acquire(False)
self.puppet_arm_publish_thread = None
self.puppet_arm_publish_thread = threading.Thread(
target=self.puppet_arm_publish_continuous, args=(left, right)
)
self.puppet_arm_publish_thread.start()
def get_frame(self):
if (
len(self.img_left_deque) == 0
or len(self.img_right_deque) == 0
or len(self.img_front_deque) == 0
or (self.args.use_depth_image and (
len(self.img_left_depth_deque) == 0
or len(self.img_right_depth_deque) == 0
or len(self.img_front_depth_deque) == 0
))
):
return False
if self.args.use_depth_image:
frame_time = min([
self.img_left_deque[-1].header.stamp.to_sec(),
self.img_right_deque[-1].header.stamp.to_sec(),
self.img_front_deque[-1].header.stamp.to_sec(),
self.img_left_depth_deque[-1].header.stamp.to_sec(),
self.img_right_depth_deque[-1].header.stamp.to_sec(),
self.img_front_depth_deque[-1].header.stamp.to_sec(),
])
else:
frame_time = min([
self.img_left_deque[-1].header.stamp.to_sec(),
self.img_right_deque[-1].header.stamp.to_sec(),
self.img_front_deque[-1].header.stamp.to_sec(),
])
if len(self.img_left_deque) == 0 or self.img_left_deque[-1].header.stamp.to_sec() < frame_time: return False
if len(self.img_right_deque) == 0 or self.img_right_deque[-1].header.stamp.to_sec() < frame_time: return False
if len(self.img_front_deque) == 0 or self.img_front_deque[-1].header.stamp.to_sec() < frame_time: return False
if len(self.puppet_arm_left_deque) == 0 or self.puppet_arm_left_deque[-1].header.stamp.to_sec() < frame_time: return False
if len(self.puppet_arm_right_deque) == 0 or self.puppet_arm_right_deque[-1].header.stamp.to_sec() < frame_time: return False
if self.args.use_depth_image and (len(self.img_left_depth_deque) == 0 or self.img_left_depth_deque[-1].header.stamp.to_sec() < frame_time): return False
if self.args.use_depth_image and (len(self.img_right_depth_deque) == 0 or self.img_right_depth_deque[-1].header.stamp.to_sec() < frame_time): return False
if self.args.use_depth_image and (len(self.img_front_depth_deque) == 0 or self.img_front_depth_deque[-1].header.stamp.to_sec() < frame_time): return False
if self.args.use_robot_base and (len(self.robot_base_deque) == 0 or self.robot_base_deque[-1].header.stamp.to_sec() < frame_time): return False
while self.img_left_deque[0].header.stamp.to_sec() < frame_time: self.img_left_deque.popleft()
img_left = self.bridge.imgmsg_to_cv2(self.img_left_deque.popleft(), "passthrough")
while self.img_right_deque[0].header.stamp.to_sec() < frame_time: self.img_right_deque.popleft()
img_right = self.bridge.imgmsg_to_cv2(self.img_right_deque.popleft(), "passthrough")
while self.img_front_deque[0].header.stamp.to_sec() < frame_time: self.img_front_deque.popleft()
img_front = self.bridge.imgmsg_to_cv2(self.img_front_deque.popleft(), "passthrough")
while self.puppet_arm_left_deque[0].header.stamp.to_sec() < frame_time: self.puppet_arm_left_deque.popleft()
puppet_arm_left = self.puppet_arm_left_deque.popleft()
while self.puppet_arm_right_deque[0].header.stamp.to_sec() < frame_time: self.puppet_arm_right_deque.popleft()
puppet_arm_right = self.puppet_arm_right_deque.popleft()
img_left_depth = img_right_depth = img_front_depth = None
if self.args.use_depth_image:
while self.img_left_depth_deque[0].header.stamp.to_sec() < frame_time: self.img_left_depth_deque.popleft()
img_left_depth = self.bridge.imgmsg_to_cv2(self.img_left_depth_deque.popleft(), "passthrough")
while self.img_right_depth_deque[0].header.stamp.to_sec() < frame_time: self.img_right_depth_deque.popleft()
img_right_depth = self.bridge.imgmsg_to_cv2(self.img_right_depth_deque.popleft(), "passthrough")
while self.img_front_depth_deque[0].header.stamp.to_sec() < frame_time: self.img_front_depth_deque.popleft()
img_front_depth = self.bridge.imgmsg_to_cv2(self.img_front_depth_deque.popleft(), "passthrough")
robot_base = None
if self.args.use_robot_base:
while self.robot_base_deque[0].header.stamp.to_sec() < frame_time: self.robot_base_deque.popleft()
robot_base = self.robot_base_deque.popleft()
result_tuple = (img_front, img_left, img_right,
img_front_depth, img_left_depth, img_right_depth,
puppet_arm_left, puppet_arm_right, robot_base)
self.last_frame_cache = result_tuple
return result_tuple
def get_frame_peek(self):
"""Thread-safe version that snapshots all deques to avoid concurrent modification."""
if (
len(self.img_left_deque) == 0
or len(self.img_right_deque) == 0
or len(self.img_front_deque) == 0
or (self.args.use_depth_image and (
len(self.img_left_depth_deque) == 0
or len(self.img_right_depth_deque) == 0
or len(self.img_front_depth_deque) == 0
))
):
return False
# snapshot all deques to avoid mutation during iteration
try:
img_left_snapshot = list(self.img_left_deque)
img_right_snapshot = list(self.img_right_deque)
img_front_snapshot = list(self.img_front_deque)
puppet_left_snapshot = list(self.puppet_arm_left_deque)
puppet_right_snapshot = list(self.puppet_arm_right_deque)
if self.args.use_depth_image:
img_left_depth_snapshot = list(self.img_left_depth_deque)
img_right_depth_snapshot = list(self.img_right_depth_deque)
img_front_depth_snapshot = list(self.img_front_depth_deque)
if self.args.use_robot_base:
robot_base_snapshot = list(self.robot_base_deque)
except Exception:
# deque modified during snapshot, abort
return False
# compute earliest frame timestamp
if self.args.use_depth_image:
frame_time = min([
img_left_snapshot[-1].header.stamp.to_sec(),
img_right_snapshot[-1].header.stamp.to_sec(),
img_front_snapshot[-1].header.stamp.to_sec(),
img_left_depth_snapshot[-1].header.stamp.to_sec(),
img_right_depth_snapshot[-1].header.stamp.to_sec(),
img_front_depth_snapshot[-1].header.stamp.to_sec(),
])
else:
frame_time = min([
img_left_snapshot[-1].header.stamp.to_sec(),
img_right_snapshot[-1].header.stamp.to_sec(),
img_front_snapshot[-1].header.stamp.to_sec(),
])
# verify all snapshots have reached this timestamp
for snapshot in [img_left_snapshot, img_right_snapshot, img_front_snapshot,
puppet_left_snapshot, puppet_right_snapshot]:
if len(snapshot) == 0 or snapshot[-1].header.stamp.to_sec() < frame_time:
return False
if self.args.use_depth_image:
for snapshot in [img_left_depth_snapshot, img_right_depth_snapshot, img_front_depth_snapshot]:
if len(snapshot) == 0 or snapshot[-1].header.stamp.to_sec() < frame_time:
return False
if self.args.use_robot_base:
if len(robot_base_snapshot) == 0 or robot_base_snapshot[-1].header.stamp.to_sec() < frame_time:
return False
def first_ge(snapshot_list, t):
"""Find first item in snapshot_list with timestamp >= t."""
for item in snapshot_list:
if item.header.stamp.to_sec() >= t:
return item
return snapshot_list[-1] if snapshot_list else None
# find timestamp-matching messages
img_left_msg = first_ge(img_left_snapshot, frame_time)
img_right_msg = first_ge(img_right_snapshot, frame_time)
img_front_msg = first_ge(img_front_snapshot, frame_time)
puppet_arm_left = first_ge(puppet_left_snapshot, frame_time)
puppet_arm_right = first_ge(puppet_right_snapshot, frame_time)
# decode image messages
img_left = self.bridge.imgmsg_to_cv2(img_left_msg, "passthrough")
img_right = self.bridge.imgmsg_to_cv2(img_right_msg, "passthrough")
img_front = self.bridge.imgmsg_to_cv2(img_front_msg, "passthrough")
# depth images (if enabled)
img_left_depth = img_right_depth = img_front_depth = None
if self.args.use_depth_image:
img_left_depth = self.bridge.imgmsg_to_cv2(first_ge(img_left_depth_snapshot, frame_time), "passthrough")
img_right_depth = self.bridge.imgmsg_to_cv2(first_ge(img_right_depth_snapshot, frame_time), "passthrough")
img_front_depth = self.bridge.imgmsg_to_cv2(first_ge(img_front_depth_snapshot, frame_time), "passthrough")
# robot base data (if enabled)
robot_base = None
if self.args.use_robot_base:
robot_base = first_ge(robot_base_snapshot, frame_time)
return (img_front, img_left, img_right,
img_front_depth, img_left_depth, img_right_depth,
puppet_arm_left, puppet_arm_right, robot_base)
def img_left_callback(self, msg):
if len(self.img_left_deque) >= 2000: self.img_left_deque.popleft()
self.img_left_deque.append(msg)
def img_right_callback(self, msg):
if len(self.img_right_deque) >= 2000: self.img_right_deque.popleft()
self.img_right_deque.append(msg)
def img_front_callback(self, msg):
if len(self.img_front_deque) >= 2000: self.img_front_deque.popleft()
self.img_front_deque.append(msg)
def img_left_depth_callback(self, msg):
if len(self.img_left_depth_deque) >= 2000: self.img_left_depth_deque.popleft()
self.img_left_depth_deque.append(msg)
def img_right_depth_callback(self, msg):
if len(self.img_right_depth_deque) >= 2000: self.img_right_depth_deque.popleft()
self.img_right_depth_deque.append(msg)
def img_front_depth_callback(self, msg):
if len(self.img_front_depth_deque) >= 2000: self.img_front_depth_deque.popleft()
self.img_front_depth_deque.append(msg)
def puppet_arm_left_callback(self, msg):
if len(self.puppet_arm_left_deque) >= 2000: self.puppet_arm_left_deque.popleft()
self.puppet_arm_left_deque.append(msg)
def puppet_arm_right_callback(self, msg):
if len(self.puppet_arm_right_deque) >= 2000: self.puppet_arm_right_deque.popleft()
self.puppet_arm_right_deque.append(msg)
def robot_base_callback(self, msg):
if len(self.robot_base_deque) >= 2000: self.robot_base_deque.popleft()
self.robot_base_deque.append(msg)
def init_ros(self):
rospy.init_node("joint_state_publisher", anonymous=True)
rospy.Subscriber(self.args.img_left_topic, Image, self.img_left_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.img_right_topic, Image, self.img_right_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.img_front_topic, Image, self.img_front_callback, queue_size=1000, tcp_nodelay=True)
if self.args.use_depth_image:
rospy.Subscriber(self.args.img_left_depth_topic, Image, self.img_left_depth_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.img_right_depth_topic, Image, self.img_right_depth_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.img_front_depth_topic, Image, self.img_front_depth_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.puppet_arm_left_topic, JointState, self.puppet_arm_left_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.puppet_arm_right_topic, JointState, self.puppet_arm_right_callback, queue_size=1000, tcp_nodelay=True)
rospy.Subscriber(self.args.robot_base_topic, Odometry, self.robot_base_callback, queue_size=1000, tcp_nodelay=True)
self.puppet_arm_left_publisher = rospy.Publisher(self.args.puppet_arm_left_cmd_topic, JointState, queue_size=10)
self.puppet_arm_right_publisher = rospy.Publisher(self.args.puppet_arm_right_cmd_topic, JointState, queue_size=10)
self.endpose_left_publisher = rospy.Publisher(self.args.endpose_left_cmd_topic, PosCmd, queue_size=10)
self.endpose_right_publisher = rospy.Publisher(self.args.endpose_right_cmd_topic, PosCmd, queue_size=10)
self.robot_base_publisher = rospy.Publisher(self.args.robot_base_cmd_topic, Twist, queue_size=10)
def get_arguments():
parser = argparse.ArgumentParser()
parser.add_argument("--max_publish_step", type=int, default=10000)
parser.add_argument("--seed", type=int, default=None)
parser.add_argument("--img_front_topic", type=str, default="/camera_f/color/image_raw")
parser.add_argument("--img_left_topic", type=str, default="/camera_l/color/image_raw")
parser.add_argument("--img_right_topic", type=str, default="/camera_r/color/image_raw")
parser.add_argument("--img_front_depth_topic", type=str, default="/camera_f/depth/image_raw")
parser.add_argument("--img_left_depth_topic", type=str, default="/camera_l/depth/image_raw")
parser.add_argument("--img_right_depth_topic", type=str, default="/camera_r/depth/image_raw")
parser.add_argument("--puppet_arm_left_cmd_topic", type=str, default="/master/joint_left")
parser.add_argument("--puppet_arm_right_cmd_topic", type=str, default="/master/joint_right")
parser.add_argument("--puppet_arm_left_topic", type=str, default="/puppet/joint_left")
parser.add_argument("--puppet_arm_right_topic", type=str, default="/puppet/joint_right")
parser.add_argument("--endpose_left_cmd_topic", type=str, default="/pos_cmd_left")
parser.add_argument("--endpose_right_cmd_topic", type=str, default="/pos_cmd_right")
parser.add_argument("--robot_base_topic", type=str, default="/odom_raw")
parser.add_argument("--robot_base_cmd_topic", type=str, default="/cmd_vel")
parser.add_argument("--use_robot_base", action="store_true", default=False)
parser.add_argument("--publish_rate", type=int, default=30)
# smoothing
parser.add_argument("--use_temporal_smoothing", action="store_true", default=False)
parser.add_argument("--latency_k", type=int, default=8)
parser.add_argument("--inference_rate", type=float, default=3.0)
parser.add_argument("--min_smooth_steps", type=int, default=8)
parser.add_argument("--buffer_max_chunks", type=int, default=10)
parser.add_argument("--exp_decay_alpha", type=float, default=0.25)
parser.add_argument("--gripper_threshold", action="store_true", default=True)
parser.add_argument("--chunk_size", type=int, default=50)
parser.add_argument("--arm_steps_length", type=float, default=[0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.2])
parser.add_argument("--use_actions_interpolation", action="store_true", default=False)
parser.add_argument("--use_kalman_filter", action="store_true", default=True)
parser.add_argument("--interpolate_method", type=str, choices=["linear", "minimum_jerk"], default="linear")
parser.add_argument("--jerk_num_steps", type=int, default=10)
parser.add_argument("--use_depth_image", action="store_true", default=False)
# video export
parser.add_argument("--export_video", action="store_true", default=True)
parser.add_argument("--video_fps", type=int, default=30)
parser.add_argument("--video_codec", type=str, choices=["libx264", "libx265", "libsvtav1"], default="libx264")
parser.add_argument("--video_quality", type=int, default=23, help="CRF value; lower = higher quality")
# server
parser.add_argument("--host", type=str, default="localhost")
parser.add_argument("--port", type=int, default=8000)
parser.add_argument("--ctrl_type", type=str, choices=["joint", "eef"], default="joint")
# dataset
parser.add_argument("--dataset_dir", type=str, default="/home/agilex/data")
parser.add_argument("--task_name", type=str, default="aloha_inference")
parser.add_argument("--episode_idx", type=int, default=0)
parser.add_argument("--max_timesteps", type=int, default=100000000)
parser.add_argument("--frame_rate", type=int, default=30)
parser.add_argument("--camera_names", nargs="+", default=["cam_high", "cam_left_wrist", "cam_right_wrist"])
return parser.parse_args()
def main():
args = get_arguments()
try:
ros_operator = RosOperator(args)
if args.seed is not None:
set_seed(args.seed)
config = get_config(args)
model_inference(args, config, ros_operator)
except KeyboardInterrupt:
print("\n⚠️ Interrupted, exiting...")
except Exception as e:
print(f"\n❌ Error: {e}")
import traceback
traceback.print_exc()
finally:
print("Program exited")
if __name__ == "__main__":
main()
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