| """Pack SONIC v1.1 encoder / decoder vectors.""" |
|
|
| from __future__ import annotations |
|
|
| from collections import deque |
|
|
| import numpy as np |
|
|
| from .constants import ( |
| DECODER_DIM, |
| DEFAULT_ANGLES, |
| ENCODER_DIM, |
| ENCODER_OFF, |
| FUTURE_FRAMES, |
| G1_STEP, |
| HIST_FRAMES, |
| LOWER_BODY_ISAAC_IDX, |
| MODE_IDS, |
| NUM_JOINTS, |
| TOKEN_DIM, |
| WRIST_ISAAC_IDX, |
| ) |
| from .math_np import heading_rel_6d |
|
|
|
|
| class History: |
| """Oldest-first proprio history at control rate (10 frames, step 1).""" |
|
|
| def __init__(self) -> None: |
| self.ang_vel = deque(maxlen=HIST_FRAMES) |
| self.q_rel = deque(maxlen=HIST_FRAMES) |
| self.dq = deque(maxlen=HIST_FRAMES) |
| self.action = deque(maxlen=HIST_FRAMES) |
| self.gravity = deque(maxlen=HIST_FRAMES) |
|
|
| def push( |
| self, |
| ang_vel: np.ndarray, |
| q_rel: np.ndarray, |
| dq: np.ndarray, |
| action: np.ndarray, |
| gravity: np.ndarray, |
| ) -> None: |
| self.ang_vel.append(np.asarray(ang_vel, dtype=np.float32).reshape(3)) |
| self.q_rel.append(np.asarray(q_rel, dtype=np.float32).reshape(NUM_JOINTS)) |
| self.dq.append(np.asarray(dq, dtype=np.float32).reshape(NUM_JOINTS)) |
| self.action.append(np.asarray(action, dtype=np.float32).reshape(NUM_JOINTS)) |
| self.gravity.append(np.asarray(gravity, dtype=np.float32).reshape(3)) |
|
|
| def fill(self, **kwargs) -> None: |
| for _ in range(HIST_FRAMES): |
| self.push(**kwargs) |
|
|
| def stack(self, buf: deque) -> np.ndarray: |
| while len(buf) < HIST_FRAMES: |
| buf.appendleft(np.zeros_like(buf[0]) if buf else np.zeros(1, dtype=np.float32)) |
| return np.concatenate(list(buf), axis=0) |
|
|
|
|
| def _future_idx(t: int, n: int, n_frames: int, step: int) -> np.ndarray: |
| idx = t + np.arange(n_frames) * step |
| return np.clip(idx, 0, n - 1) |
|
|
|
|
| def pack_encoder( |
| *, |
| mode: str, |
| t: int, |
| joint_pos: np.ndarray, |
| joint_vel: np.ndarray, |
| ref_quat_wxyz: np.ndarray, |
| robot_quat_wxyz: np.ndarray, |
| vr_local_pos: np.ndarray | None, |
| vr_local_quat: np.ndarray | None, |
| ) -> np.ndarray: |
| """Build the 1751-D encoder input. |
| |
| ``joint_pos`` / ``joint_vel`` are (T, 29) in **Isaac Lab** joint order at |
| 50 Hz. ``vr_local_pos`` (T, 3, 3) and ``vr_local_quat`` (T, 3, 4 wxyz) are |
| already expressed in the **reference motion pelvis** frame, matching |
| ``vr_3point_local_target``: "local here means relative to the reference |
| motion root, not the robot root". |
| |
| Teleop only fills ``encoder_modes.teleop.required_observations``; other |
| encoder slots stay zero (GEAR-SONIC deploy). |
| """ |
| enc = np.zeros(ENCODER_DIM, dtype=np.float32) |
| mode_id = MODE_IDS[mode] |
| s, _e = ENCODER_OFF["encoder_mode_4"] |
| enc[s] = float(mode_id) |
|
|
| n = joint_pos.shape[0] |
| g1_idx = _future_idx(t, n, FUTURE_FRAMES, G1_STEP) |
| smpl_idx = _future_idx(t, n, FUTURE_FRAMES, 1) |
| fill_g1 = mode == "g1" |
| fill_teleop = mode == "teleop" |
| fill_smpl = mode == "smpl" |
|
|
| if fill_g1: |
| a, b = ENCODER_OFF["motion_joint_positions_10frame_step5"] |
| enc[a:b] = joint_pos[g1_idx].reshape(-1) |
| a, b = ENCODER_OFF["motion_joint_velocities_10frame_step5"] |
| enc[a:b] = joint_vel[g1_idx].reshape(-1) |
| ori_mf = np.stack( |
| [heading_rel_6d(robot_quat_wxyz, ref_quat_wxyz[i]) for i in g1_idx], |
| axis=0, |
| ).reshape(-1) |
| a, b = ENCODER_OFF["motion_anchor_orientation_heading_10frame_step5"] |
| enc[a:b] = ori_mf |
|
|
| if fill_teleop: |
| a, b = ENCODER_OFF["motion_anchor_orientation_heading"] |
| enc[a:b] = heading_rel_6d(robot_quat_wxyz, ref_quat_wxyz[t]) |
|
|
| a, b = ENCODER_OFF["motion_joint_positions_lowerbody_10frame_step5"] |
| enc[a:b] = joint_pos[g1_idx][:, LOWER_BODY_ISAAC_IDX].reshape(-1) |
| a, b = ENCODER_OFF["motion_joint_velocities_lowerbody_10frame_step5"] |
| enc[a:b] = joint_vel[g1_idx][:, LOWER_BODY_ISAAC_IDX].reshape(-1) |
|
|
| if fill_smpl: |
| a, b = ENCODER_OFF["motion_joint_positions_wrists_10frame_step1"] |
| enc[a:b] = joint_pos[smpl_idx][:, WRIST_ISAAC_IDX].reshape(-1) |
|
|
| if fill_teleop and vr_local_pos is not None: |
| a, b = ENCODER_OFF["vr_3point_local_target"] |
| enc[a:b] = np.asarray(vr_local_pos[t], dtype=np.float64).reshape(-1) |
| if fill_teleop and vr_local_quat is not None: |
| a, b = ENCODER_OFF["vr_3point_local_orn_target"] |
| enc[a:b] = np.asarray(vr_local_quat[t], dtype=np.float64).reshape(-1) |
|
|
| return enc |
|
|
|
|
| def pack_decoder(token: np.ndarray, hist: History) -> np.ndarray: |
| dec = np.zeros(DECODER_DIM, dtype=np.float32) |
| dec[:TOKEN_DIM] = np.asarray(token, dtype=np.float32).reshape(TOKEN_DIM) |
| |
| i = TOKEN_DIM |
| for buf in (hist.ang_vel, hist.q_rel, hist.dq, hist.action, hist.gravity): |
| stacked = hist.stack(buf) |
| dec[i : i + stacked.size] = stacked |
| i += stacked.size |
| if i != DECODER_DIM: |
| raise RuntimeError(f"decoder pack {i} != {DECODER_DIM}") |
| return dec |
|
|
|
|
| def default_q() -> np.ndarray: |
| return np.asarray(DEFAULT_ANGLES, dtype=np.float64) |
|
|
