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e0803b8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 | """Shared definitions and utilities for BONES-SEED G1 converters."""
from __future__ import annotations
from functools import lru_cache
from pathlib import Path
import mujoco
import numpy as np
from scipy.spatial.transform import Rotation as R
MT_JOINT_NAMES = [
"left_hip_pitch_joint",
"left_hip_roll_joint",
"left_hip_yaw_joint",
"left_knee_joint",
"left_ankle_pitch_joint",
"left_ankle_roll_joint",
"right_hip_pitch_joint",
"right_hip_roll_joint",
"right_hip_yaw_joint",
"right_knee_joint",
"right_ankle_pitch_joint",
"right_ankle_roll_joint",
"waist_yaw_joint",
"waist_roll_joint",
"waist_pitch_joint",
"left_shoulder_pitch_joint",
"left_shoulder_roll_joint",
"left_shoulder_yaw_joint",
"left_elbow_joint",
"left_wrist_roll_joint",
"left_wrist_pitch_joint",
"left_wrist_yaw_joint",
"right_shoulder_pitch_joint",
"right_shoulder_roll_joint",
"right_shoulder_yaw_joint",
"right_elbow_joint",
"right_wrist_roll_joint",
"right_wrist_pitch_joint",
"right_wrist_yaw_joint",
]
ISAAC_JOINT_NAMES = [
"left_hip_pitch_joint",
"right_hip_pitch_joint",
"waist_yaw_joint",
"left_hip_roll_joint",
"right_hip_roll_joint",
"waist_roll_joint",
"left_hip_yaw_joint",
"right_hip_yaw_joint",
"waist_pitch_joint",
"left_knee_joint",
"right_knee_joint",
"left_shoulder_pitch_joint",
"right_shoulder_pitch_joint",
"left_ankle_pitch_joint",
"right_ankle_pitch_joint",
"left_shoulder_roll_joint",
"right_shoulder_roll_joint",
"left_ankle_roll_joint",
"right_ankle_roll_joint",
"left_shoulder_yaw_joint",
"right_shoulder_yaw_joint",
"left_elbow_joint",
"right_elbow_joint",
"left_wrist_roll_joint",
"right_wrist_roll_joint",
"left_wrist_pitch_joint",
"right_wrist_pitch_joint",
"left_wrist_yaw_joint",
"right_wrist_yaw_joint",
]
MT_BODY_NAMES = [
"pelvis",
"left_hip_pitch_link",
"left_hip_roll_link",
"left_hip_yaw_link",
"left_knee_link",
"left_ankle_pitch_link",
"left_ankle_roll_link",
"right_hip_pitch_link",
"right_hip_roll_link",
"right_hip_yaw_link",
"right_knee_link",
"right_ankle_pitch_link",
"right_ankle_roll_link",
"torso_link",
"left_shoulder_pitch_link",
"left_shoulder_roll_link",
"left_shoulder_yaw_link",
"left_elbow_link",
"left_wrist_roll_link",
"right_shoulder_pitch_link",
"right_shoulder_roll_link",
"right_shoulder_yaw_link",
"right_elbow_link",
"right_wrist_roll_link",
"head_mimic",
"left_hand_mimic",
"right_hand_mimic",
]
ISAAC_BODY_NAMES = [
"pelvis",
"left_hip_pitch_link",
"right_hip_pitch_link",
"pelvis_contour_link",
"left_hip_roll_link",
"right_hip_roll_link",
"waist_roll_link",
"left_hip_yaw_link",
"right_hip_yaw_link",
"torso_link",
"left_knee_link",
"right_knee_link",
"left_shoulder_pitch_link",
"right_shoulder_pitch_link",
"left_ankle_pitch_link",
"right_ankle_pitch_link",
"left_shoulder_roll_link",
"right_shoulder_roll_link",
"left_ankle_roll_link",
"right_ankle_roll_link",
"left_shoulder_yaw_link",
"right_shoulder_yaw_link",
"left_elbow_link",
"right_elbow_link",
"left_wrist_roll_link",
"right_wrist_roll_link",
"left_wrist_pitch_link",
"right_wrist_pitch_link",
"left_wrist_yaw_link",
"right_wrist_yaw_link",
]
ROOT_TRANSLATION_COLUMNS = [
"root_translateX",
"root_translateY",
"root_translateZ",
]
ROOT_ROTATION_COLUMNS = [
"root_rotateX",
"root_rotateY",
"root_rotateZ",
]
def validate_fps(source_fps: int, target_fps: int) -> None:
if source_fps <= 0 or target_fps <= 0:
raise ValueError("source_fps and target_fps must both be positive")
def load_csv_motion(csv_path: str | Path) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
"""Load root position, root quaternion (xyzw), and MT-order DOF positions."""
csv_path = Path(csv_path)
if not csv_path.is_file():
raise FileNotFoundError(f"CSV file not found: {csv_path}")
data = np.genfromtxt(csv_path, delimiter=",", names=True)
data = np.atleast_1d(data)
if data.size == 0 or data.dtype.names is None:
raise ValueError(f"CSV contains no motion frames: {csv_path}")
required_columns = (
ROOT_TRANSLATION_COLUMNS
+ ROOT_ROTATION_COLUMNS
+ [f"{name}_dof" for name in MT_JOINT_NAMES]
)
missing = [name for name in required_columns if name not in data.dtype.names]
if missing:
raise ValueError(
f"CSV is missing {len(missing)} required column(s): {', '.join(missing)}"
)
root_pos = np.column_stack([data[name] for name in ROOT_TRANSLATION_COLUMNS])
root_pos = root_pos.astype(np.float32) / 100.0
root_euler_xyz_deg = np.column_stack(
[data[name] for name in ROOT_ROTATION_COLUMNS]
)
root_rot_xyzw = R.from_euler(
"xyz", root_euler_xyz_deg, degrees=True
).as_quat().astype(np.float32)
dof_pos_deg = np.column_stack(
[data[f"{name}_dof"] for name in MT_JOINT_NAMES]
).astype(np.float32)
dof_pos = np.deg2rad(dof_pos_deg).astype(np.float32)
for name, value in (
("root_pos", root_pos),
("root_rot_xyzw", root_rot_xyzw),
("dof_pos", dof_pos),
):
if not np.isfinite(value).all():
raise ValueError(f"{name} contains NaN or Inf: {csv_path}")
return root_pos, root_rot_xyzw, dof_pos
@lru_cache(maxsize=8)
def load_g1_model(g1_xml: str) -> mujoco.MjModel:
"""Load and validate a G1 MJCF model, cached once per worker process."""
xml_path = Path(g1_xml).expanduser().resolve()
if not xml_path.is_file():
raise FileNotFoundError(f"G1 MJCF file not found: {xml_path}")
model = mujoco.MjModel.from_xml_path(str(xml_path))
expected_nq = 7 + len(MT_JOINT_NAMES)
if model.nq != expected_nq:
raise ValueError(
f"Expected G1 model nq={expected_nq}, but {xml_path} has nq={model.nq}"
)
model_joint_names = []
for joint_id in range(model.njnt):
if model.jnt_type[joint_id] == mujoco.mjtJoint.mjJNT_FREE:
continue
name = mujoco.mj_id2name(
model, mujoco.mjtObj.mjOBJ_JOINT, joint_id
)
if name:
model_joint_names.append(name)
if model_joint_names != MT_JOINT_NAMES:
raise ValueError(
"G1 MJCF joint order does not match the expected MT order.\n"
f"Expected: {MT_JOINT_NAMES}\n"
f"Found: {model_joint_names}"
)
return model
def require_body_id(model: mujoco.MjModel, body_name: str) -> int:
body_id = mujoco.mj_name2id(
model, mujoco.mjtObj.mjOBJ_BODY, body_name
)
if body_id < 0:
raise ValueError(f"G1 MJCF is missing required body: {body_name}")
return body_id
def output_frame_count(frame_count: int, source_fps: int, target_fps: int) -> int:
return max(1, int(round(frame_count * target_fps / source_fps)))
def interpolate_linear(array: np.ndarray, new_frame_count: int) -> np.ndarray:
"""Linearly resample an array along its first dimension."""
old_frame_count = len(array)
if new_frame_count == old_frame_count:
return array.copy()
if old_frame_count == 1:
return np.repeat(array, new_frame_count, axis=0)
new_times = np.linspace(0, old_frame_count - 1, new_frame_count)
result = np.empty(
(new_frame_count,) + array.shape[1:], dtype=np.float32
)
for index, time in enumerate(new_times):
lower = int(np.floor(time))
upper = min(lower + 1, old_frame_count - 1)
fraction = time - lower
result[index] = array[lower] + fraction * (
array[upper] - array[lower]
)
return result
def interpolate_quaternions(
quaternions: np.ndarray, new_frame_count: int
) -> np.ndarray:
"""SLERP quaternion arrays along the first dimension."""
old_frame_count = len(quaternions)
if new_frame_count == old_frame_count:
result = quaternions.copy()
elif old_frame_count == 1:
result = np.repeat(quaternions, new_frame_count, axis=0)
else:
result = np.empty(
(new_frame_count,) + quaternions.shape[1:], dtype=np.float32
)
new_times = np.linspace(0, old_frame_count - 1, new_frame_count)
for index, time in enumerate(new_times):
lower = int(np.floor(time))
upper = min(lower + 1, old_frame_count - 1)
fraction = time - lower
q0 = quaternions[lower]
q1 = quaternions[upper]
dot = np.sum(q0 * q1, axis=-1, keepdims=True)
q1 = np.where(dot < 0.0, -q1, q1)
dot = np.clip(np.abs(dot), 0.0, 1.0)
theta = np.arccos(dot)
sin_theta = np.sin(theta)
small = sin_theta < 1e-6
denominator = np.maximum(sin_theta, 1e-6)
weight0 = np.where(
small,
1.0 - fraction,
np.sin((1.0 - fraction) * theta) / denominator,
)
weight1 = np.where(
small,
fraction,
np.sin(fraction * theta) / denominator,
)
result[index] = weight0 * q0 + weight1 * q1
norms = np.linalg.norm(result, axis=-1, keepdims=True)
if np.any(norms < 1e-8):
raise ValueError("Encountered a zero-length quaternion during resampling")
return (result / norms).astype(np.float32)
def finite_difference(array: np.ndarray, fps: int) -> np.ndarray:
"""Compute a time derivative using forward/backward and central differences."""
derivative = np.zeros_like(array, dtype=np.float32)
if len(array) == 1:
return derivative
dt = 1.0 / fps
derivative[0] = (array[1] - array[0]) / dt
derivative[-1] = (array[-1] - array[-2]) / dt
if len(array) > 2:
derivative[1:-1] = (array[2:] - array[:-2]) / (2.0 * dt)
return derivative
def body_angular_velocity_wxyz(
body_quat_wxyz: np.ndarray, fps: int
) -> np.ndarray:
"""Compute world-frame body angular velocity from wxyz quaternions."""
angular_velocity = np.zeros(
body_quat_wxyz.shape[:-1] + (3,), dtype=np.float32
)
if len(body_quat_wxyz) == 1:
return angular_velocity
dt = 1.0 / fps
for frame in range(len(body_quat_wxyz) - 1):
q0_xyzw = body_quat_wxyz[frame][:, [1, 2, 3, 0]]
q1_xyzw = body_quat_wxyz[frame + 1][:, [1, 2, 3, 0]]
rotation0 = R.from_quat(q0_xyzw)
rotation1 = R.from_quat(q1_xyzw)
delta = rotation1 * rotation0.inv()
angular_velocity[frame] = delta.as_rotvec() / dt
angular_velocity[-1] = angular_velocity[-2]
return angular_velocity
def ensure_output_parent(output_path: str | Path) -> Path:
output_path = Path(output_path)
output_path.parent.mkdir(parents=True, exist_ok=True)
return output_path
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