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850 lines
34 KiB
850 lines
34 KiB
#!/usr/bin/env python3
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"""
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Retargeting bridge v4: Quest 3 full body tracking -> G1 robot joints via DIRECT mapping + DDS.
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Maps ALL tracked body joints directly to robot joint angles (no IK solver):
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- Waist (3 DOF): hips->chest relative rotation -> ZXY Euler
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- Shoulders (3 DOF x 2): chest->upper_arm -> YXZ Euler
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- Elbows (1 DOF x 2): upper_arm->lower_arm -> Y rotation
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- Wrists (3 DOF x 2): lower_arm->hand -> XYZ Euler
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- Hands (12 DOF): dex-retargeting for Inspire hands
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- Legs: zeroed (not tracked)
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Calibration:
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On first tracking frame, captures the user's neutral pose as reference.
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All subsequent angles are deltas from this reference, ensuring:
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- User arms at sides -> robot arms at sides (zero angles)
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- User arm movements -> proportional robot joint movements
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Architecture:
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Quest 3 -> WebSocket -> TeleopServer (shared memory)
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retarget_bridge.py
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- Direct joint retargeting (17 DOF)
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- Inspire hand retargeting (12 DOF)
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CycloneDDS -> Isaac Sim
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Usage:
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python retarget_bridge.py [--port 8765] [--dds-domain 1] [--hz 50] [--verbose]
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"""
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import sys
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import os
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import time
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import argparse
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import logging
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import signal
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import numpy as np
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from scipy.spatial.transform import Rotation
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# Add xr_teleoperate to Python path for hand retargeting
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XR_TELEOP_DIR = "/home/sparky/git/xr_teleoperate"
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sys.path.insert(0, XR_TELEOP_DIR)
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# Monkey-patch logging_mp API compatibility
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import logging_mp
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if not hasattr(logging_mp, 'getLogger'):
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logging_mp.getLogger = logging_mp.get_logger
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# Monkey-patch dex_retargeting
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import dex_retargeting
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if not hasattr(dex_retargeting, 'RetargetingConfig'):
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from dex_retargeting.retargeting_config import RetargetingConfig
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dex_retargeting.RetargetingConfig = RetargetingConfig
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# Local imports
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from teleop_server import TeleopServer
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from native_tv_wrapper import (T_ROBOT_OPENXR, T_OPENXR_ROBOT,
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T_TO_UNITREE_HAND,
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NativeTeleWrapper)
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logger = logging.getLogger("retarget_bridge")
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# ---------------------------------------------------------------------------
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# G1 joint constants
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# ---------------------------------------------------------------------------
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NUM_JOINTS = 29
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# Joint index ranges in LowCmd
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WAIST_START = 12 # indices 12-14: waist yaw, roll, pitch
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LEFT_ARM_START = 15 # indices 15-21: 7 left arm joints
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RIGHT_ARM_START = 22 # indices 22-28: 7 right arm joints
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# Joint limits from URDF with 90% safety factor
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JOINT_LIMITS = {
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12: (-2.356, 2.356), # waist_yaw
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13: (-0.468, 0.468), # waist_roll
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14: (-0.468, 0.468), # waist_pitch
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15: (-2.780, 2.403), # L shoulder_pitch
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16: (-1.429, 2.026), # L shoulder_roll
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17: (-2.356, 2.356), # L shoulder_yaw
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18: (-0.942, 1.885), # L elbow
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19: (-1.775, 1.775), # L wrist_roll
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20: (-1.453, 1.453), # L wrist_pitch
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21: (-1.453, 1.453), # L wrist_yaw
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22: (-2.780, 2.403), # R shoulder_pitch
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23: (-2.026, 1.429), # R shoulder_roll (mirrored)
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24: (-2.356, 2.356), # R shoulder_yaw
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25: (-0.942, 1.885), # R elbow
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26: (-1.775, 1.775), # R wrist_roll
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27: (-1.453, 1.453), # R wrist_pitch
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28: (-1.453, 1.453), # R wrist_yaw
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}
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# Default Kp/Kd gains
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KP = [
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60, 60, 60, 100, 40, 40, # Left leg (0-5)
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60, 60, 60, 100, 40, 40, # Right leg (6-11)
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60, 40, 40, # Waist (12-14)
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40, 40, 40, 40, 40, 40, 40, # Left arm (15-21)
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40, 40, 40, 40, 40, 40, 40, # Right arm (22-28)
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]
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KD = [
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1, 1, 1, 2, 1, 1,
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1, 1, 1, 2, 1, 1,
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1, 1, 1,
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1, 1, 1, 1, 1, 1, 1,
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1, 1, 1, 1, 1, 1, 1,
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]
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# Inspire hand normalization ranges
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INSPIRE_RANGES = [
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(0.0, 1.7), # finger flexion
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(0.0, 1.7),
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(0.0, 1.7),
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(0.0, 1.7),
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(0.0, 0.5), # thumb pitch
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(-0.1, 1.3), # thumb yaw
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]
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# Body joint indices in shared memory (8 joints x 7 floats = 56)
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BJ_HIPS = 0
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BJ_CHEST = 1
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BJ_L_UPPER = 2
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BJ_L_LOWER = 3
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BJ_L_WRIST = 4
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BJ_R_UPPER = 5
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BJ_R_LOWER = 6
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BJ_R_WRIST = 7
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# 3x3 rotation submatrices of the basis change
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R3_ROBOT_OPENXR = T_ROBOT_OPENXR[:3, :3]
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R3_OPENXR_ROBOT = T_OPENXR_ROBOT[:3, :3]
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# Signs are now baked into the axis mapping in compute_all_angles().
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# Determined empirically via joint_calibrate.py (see calibration_log.md).
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# Per-joint linear mapping: robot_angle = scale * xr_angle + offset
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# Determined empirically by comparing robot animation range with XR tracking range.
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# Indices 0-16 map to joints 12-28 (waist 0-2, L arm 3-9, R arm 10-16)
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# Default: scale=1.0, offset=0.0 (passthrough)
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JOINT_SCALE = np.ones(17)
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JOINT_OFFSET = np.zeros(17)
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# l_shoulder_pitch (index 3): XR range [-0.4, +2.3] -> robot range [-2.4, +0.8]
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JOINT_SCALE[3] = 1.2
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JOINT_OFFSET[3] = -1.95
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# l_shoulder_roll (index 4): XR Z range [+0.06, +1.05] -> robot range [0, +1.57]
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JOINT_SCALE[4] = 1.6
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JOINT_OFFSET[4] = -0.1
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# l_shoulder_yaw (index 5): XR -X range [-0.24, +0.93] -> robot range [-1.14, +1.14]
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JOINT_SCALE[5] = 2.0
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JOINT_OFFSET[5] = -0.7
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# l_elbow (index 6): XR Z range [-0.67, +0.97] -> robot range [-0.78, +1.31]
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JOINT_SCALE[6] = 1.3
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JOINT_OFFSET[6] = 0.0
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# TODO: calibrate remaining joints (wrist, right arm)
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# Smoothing parameters
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EMA_ALPHA = 0.4 # Exponential moving average (0=no update, 1=no smoothing)
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MAX_RATE = 3.0 # Max joint velocity in rad/s
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# ---------------------------------------------------------------------------
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# Body joint utilities
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# ---------------------------------------------------------------------------
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def pose7_to_mat4(pose7):
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"""Convert [x,y,z,qx,qy,qz,qw] to 4x4 SE(3) matrix."""
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mat = np.eye(4)
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r = Rotation.from_quat(pose7[3:7]) # scipy uses [qx,qy,qz,qw]
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mat[:3, :3] = r.as_matrix()
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mat[:3, 3] = pose7[:3]
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return mat
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def parse_body_joints(body_joints_flat):
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"""Parse the 56-float body joints array into 8 x 4x4 matrices.
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Returns dict with keys: hips, chest, l_upper, l_lower, l_wrist, r_upper, r_lower, r_wrist.
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All in OpenXR world space.
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"""
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joints = {}
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names = ['hips', 'chest', 'l_upper', 'l_lower', 'l_wrist',
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'r_upper', 'r_lower', 'r_wrist']
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for i, name in enumerate(names):
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p7 = body_joints_flat[i*7:(i+1)*7]
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if np.all(p7 == 0):
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joints[name] = None
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else:
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joints[name] = pose7_to_mat4(p7)
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return joints
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def all_joints_valid(bj):
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"""Check if all 8 body joints are valid (non-None)."""
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return all(bj[k] is not None for k in
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['hips', 'chest', 'l_upper', 'l_lower', 'l_wrist',
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'r_upper', 'r_lower', 'r_wrist'])
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# ---------------------------------------------------------------------------
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# Calibration: captures neutral pose reference rotations
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# ---------------------------------------------------------------------------
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class CalibrationData:
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"""Stores reference relative rotations for calibration.
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When the user stands with arms at sides (robot's zero pose), we capture
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the relative rotation between each parent-child joint pair (R_ref).
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All subsequent tracking computes deltas from these references and
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transforms them to robot frame via a simple basis change.
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"""
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def __init__(self):
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self.calibrated = False
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# Reference relative rotations (3x3 matrices) in XR parent-local frame
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self.ref_waist = None # hips.T @ chest
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self.ref_shoulder_L = None # chest.T @ l_upper
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self.ref_shoulder_R = None # chest.T @ r_upper
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self.ref_elbow_L = None # l_upper.T @ l_lower
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self.ref_elbow_R = None # r_upper.T @ r_lower
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self.ref_wrist_L = None # l_lower.T @ l_wrist
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self.ref_wrist_R = None # r_lower.T @ r_wrist
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def capture(self, bj):
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"""Capture reference rotations from current body joint data.
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Args:
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bj: dict from parse_body_joints(), all entries must be non-None.
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Returns:
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True if calibration succeeded.
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"""
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if not all_joints_valid(bj):
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return False
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self.ref_waist = bj['hips'][:3, :3].T @ bj['chest'][:3, :3]
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self.ref_shoulder_L = bj['hips'][:3, :3].T @ bj['l_upper'][:3, :3]
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self.ref_shoulder_R = bj['hips'][:3, :3].T @ bj['r_upper'][:3, :3]
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self.ref_elbow_L = bj['l_upper'][:3, :3].T @ bj['l_lower'][:3, :3]
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self.ref_elbow_R = bj['r_upper'][:3, :3].T @ bj['r_lower'][:3, :3]
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self.ref_wrist_L = bj['l_lower'][:3, :3].T @ bj['l_wrist'][:3, :3]
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self.ref_wrist_R = bj['r_lower'][:3, :3].T @ bj['r_wrist'][:3, :3]
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self.calibrated = True
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return True
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# ---------------------------------------------------------------------------
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# Direct joint retargeting
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# ---------------------------------------------------------------------------
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def _joint_delta_robot(R_ref, R_cur):
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"""Compute rotation delta from reference to current, in robot frame.
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1. R_delta = R_ref.T @ R_cur (delta in parent-local XR frame)
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2. R_delta_robot = R_basis @ R_delta @ R_basis.T (basis change to robot axes)
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The basis change transforms the rotation's axes from OpenXR (X-right, Y-up,
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Z-back) to Robot (X-forward, Y-left, Z-up) without needing the parent's
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world orientation.
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Args:
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R_ref: 3x3 reference relative rotation (from calibration)
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R_cur: 3x3 current relative rotation
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Returns:
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3x3 delta rotation matrix in robot coordinate frame
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"""
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R_delta = R_ref.T @ R_cur
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return R3_ROBOT_OPENXR @ R_delta @ R3_ROBOT_OPENXR.T
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SOLO_JOINT = None # Set by --solo-joint arg; None = all joints active
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# Map solo-joint names to indices within the 17-element angles array
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SOLO_JOINT_MAP = {
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'l_sh_pitch': 3, # joint 15
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'l_sh_roll': 4, # joint 16
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'l_sh_yaw': 5, # joint 17
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'l_elbow': 6, # joint 18
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'l_wr_roll': 7, # joint 19
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'l_wr_pitch': 8, # joint 20
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'l_wr_yaw': 9, # joint 21
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}
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def compute_all_angles(bj, cal):
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"""Compute all 17 upper body joint angles from body tracking data.
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Uses calibrated references to compute delta rotations, then decomposes
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into Euler angles matching the URDF joint chain axes.
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URDF joint chains:
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Waist: yaw(Z) -> roll(X) -> pitch(Y) = ZXY Euler
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Shoulder: pitch(Y) -> roll(X) -> yaw(Z) = YXZ Euler
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Elbow: pitch(Y) = Y component
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Wrist: roll(X) -> pitch(Y) -> yaw(Z) = XYZ Euler
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Args:
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bj: dict from parse_body_joints()
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cal: CalibrationData (must be calibrated)
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Returns:
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np.ndarray of shape (17,) for joint indices 12-28
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"""
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angles = np.zeros(17) # indices 0-16 map to joints 12-28
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# Axis mappings determined empirically via joint_calibrate.py:
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#
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# After R_basis @ R_delta @ R_basis.T, as_euler('YXZ') returns (Y, X, Z).
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# The mapping to robot joints depends on the parent's orientation:
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#
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# Shoulder (parent=chest, upright): pitch=Y[0], roll=Z[2], yaw=-X[1]
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# Elbow (parent=upper_arm, hanging): pitch=Z[2]
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# Waist (parent=hips, upright): assumed same pattern as shoulder
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# Wrist (parent=lower_arm, hanging): assumed same pattern as elbow
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# --- Waist (0-2): DISABLED (not calibrated) ---
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# angles[0:3] = [0, 0, 0]
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# --- Left shoulder (3-5): hips -> l_upper ---
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# Using hips instead of chest to avoid head rotation contamination
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# Parent (hips) is upright: pitch=Y, roll=Z, yaw=-X
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R_sh_L_cur = bj['hips'][:3, :3].T @ bj['l_upper'][:3, :3]
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R_sd_L = _joint_delta_robot(cal.ref_shoulder_L, R_sh_L_cur)
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sy, sx, sz = Rotation.from_matrix(R_sd_L).as_euler('YXZ')
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angles[3:6] = [sy, sz, -sx] # pitch=Y, roll=Z, yaw=-X
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# --- Left elbow (6): l_upper -> l_lower ---
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# Parent (upper arm) hangs down: pitch=Z
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R_el_L_cur = bj['l_upper'][:3, :3].T @ bj['l_lower'][:3, :3]
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R_ed_L = _joint_delta_robot(cal.ref_elbow_L, R_el_L_cur)
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_, _, ez_L = Rotation.from_matrix(R_ed_L).as_euler('YXZ')
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angles[6] = ez_L # pitch = Z component
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# --- Left wrist (7-9): l_lower -> l_wrist ---
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# Parent (lower arm) hangs down: same pattern as elbow (Z-dominant)
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R_wr_L_cur = bj['l_lower'][:3, :3].T @ bj['l_wrist'][:3, :3]
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R_wrd_L = _joint_delta_robot(cal.ref_wrist_L, R_wr_L_cur)
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wy_wl, wx_wl, wz_wl = Rotation.from_matrix(R_wrd_L).as_euler('YXZ')
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angles[7:10] = [wz_wl, wy_wl, -wx_wl] # roll=Z, pitch=Y, yaw=-X (tentative)
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# --- Right arm (10-16): DISABLED (not calibrated, Quest tracking weak) ---
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# angles[10:17] = [0, 0, 0, 0, 0, 0, 0]
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# Apply per-joint linear mapping: robot_angle = scale * xr_angle + offset
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angles = JOINT_SCALE * angles + JOINT_OFFSET
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# Solo-joint mode: zero everything except the isolated joint
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if SOLO_JOINT is not None and SOLO_JOINT in SOLO_JOINT_MAP:
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solo_idx = SOLO_JOINT_MAP[SOLO_JOINT]
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solo_val = angles[solo_idx]
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angles[:] = 0.0
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angles[solo_idx] = solo_val
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return angles
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def apply_limits(angles_17):
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"""Clamp 17 upper body angles to URDF joint limits."""
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for i in range(17):
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joint_idx = 12 + i
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lo, hi = JOINT_LIMITS[joint_idx]
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angles_17[i] = np.clip(angles_17[i], lo, hi)
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return angles_17
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def smooth_angles(current, target, alpha, max_step):
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"""Apply EMA smoothing + rate limiting.
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Args:
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current: current angles (modified in place)
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target: target angles
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alpha: EMA alpha (higher = less smooth)
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max_step: max change per step (rad)
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Returns:
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smoothed angles
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"""
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blended = alpha * target + (1.0 - alpha) * current
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delta = blended - current
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clipped = np.clip(delta, -max_step, max_step)
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return current + clipped
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# ---------------------------------------------------------------------------
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# DDS publisher
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# ---------------------------------------------------------------------------
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class DDSPublisher:
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"""Publishes G1 joint commands and Inspire hand commands via CycloneDDS."""
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def __init__(self, domain_id=1):
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from unitree_sdk2py.core.channel import (
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ChannelPublisher, ChannelFactoryInitialize)
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from unitree_sdk2py.idl.unitree_hg.msg.dds_ import LowCmd_
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from unitree_sdk2py.idl.default import unitree_hg_msg_dds__LowCmd_
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from unitree_sdk2py.utils.crc import CRC
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from unitree_sdk2py.idl.unitree_go.msg.dds_ import MotorCmds_
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from unitree_sdk2py.idl.default import unitree_go_msg_dds__MotorCmd_
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logger.info(f"Initializing DDS (domain {domain_id})...")
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ChannelFactoryInitialize(domain_id)
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self._body_pub = ChannelPublisher("rt/lowcmd", LowCmd_)
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self._body_pub.Init()
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self._low_cmd = unitree_hg_msg_dds__LowCmd_()
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self._crc = CRC()
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self._MotorCmd_ = unitree_go_msg_dds__MotorCmd_
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self._hand_pub = ChannelPublisher("rt/inspire/cmd", MotorCmds_)
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self._hand_pub.Init()
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self._MotorCmds_ = MotorCmds_
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logger.info("DDS publishers initialized (rt/lowcmd, rt/inspire/cmd)")
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def publish_body(self, joint_angles):
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cmd = self._low_cmd
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cmd.mode_pr = 0
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cmd.mode_machine = 0
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for i in range(NUM_JOINTS):
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cmd.motor_cmd[i].mode = 1
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cmd.motor_cmd[i].q = float(joint_angles[i])
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cmd.motor_cmd[i].dq = 0.0
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cmd.motor_cmd[i].tau = 0.0
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cmd.motor_cmd[i].kp = float(KP[i])
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cmd.motor_cmd[i].kd = float(KD[i])
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# Zero out legs (not retargeted)
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for i in range(12):
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cmd.motor_cmd[i].mode = 0
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cmd.motor_cmd[i].kp = 0.0
|
|
cmd.motor_cmd[i].kd = 0.0
|
|
|
|
cmd.crc = self._crc.Crc(cmd)
|
|
self._body_pub.Write(cmd)
|
|
|
|
def publish_hands(self, hand_values):
|
|
hand_cmd = self._MotorCmds_()
|
|
hand_cmd.cmds = []
|
|
for i in range(12):
|
|
mc = self._MotorCmd_()
|
|
mc.q = float(np.clip(hand_values[i], 0.0, 1.0))
|
|
mc.dq = 0.0
|
|
mc.tau = 0.0
|
|
mc.kp = 5.0
|
|
mc.kd = 0.5
|
|
hand_cmd.cmds.append(mc)
|
|
self._hand_pub.Write(hand_cmd)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Hand retargeting (dex-retargeting, unchanged)
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def init_hand_retargeting():
|
|
from dex_retargeting.retargeting_config import RetargetingConfig
|
|
import yaml
|
|
|
|
urdf_dir = os.path.join(XR_TELEOP_DIR, "assets")
|
|
RetargetingConfig.set_default_urdf_dir(urdf_dir)
|
|
|
|
yml_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "inspire_hand.yml")
|
|
logger.info(f"Loading hand retargeting config from {yml_path}")
|
|
with open(yml_path) as f:
|
|
cfg = yaml.safe_load(f)
|
|
|
|
left_config = RetargetingConfig.from_dict(cfg['left'])
|
|
right_config = RetargetingConfig.from_dict(cfg['right'])
|
|
left_retargeting = left_config.build()
|
|
right_retargeting = right_config.build()
|
|
|
|
left_joint_names = left_retargeting.joint_names
|
|
right_joint_names = right_retargeting.joint_names
|
|
|
|
left_hw_names = ['L_pinky_proximal_joint', 'L_ring_proximal_joint', 'L_middle_proximal_joint',
|
|
'L_index_proximal_joint', 'L_thumb_proximal_pitch_joint', 'L_thumb_proximal_yaw_joint']
|
|
right_hw_names = ['R_pinky_proximal_joint', 'R_ring_proximal_joint', 'R_middle_proximal_joint',
|
|
'R_index_proximal_joint', 'R_thumb_proximal_pitch_joint', 'R_thumb_proximal_yaw_joint']
|
|
|
|
left_hw_map = [left_joint_names.index(n) for n in left_hw_names]
|
|
right_hw_map = [right_joint_names.index(n) for n in right_hw_names]
|
|
|
|
left_indices = left_retargeting.optimizer.target_link_human_indices
|
|
right_indices = right_retargeting.optimizer.target_link_human_indices
|
|
|
|
logger.info("Hand retargeting initialized (dex-retargeting)")
|
|
|
|
return (left_retargeting, right_retargeting,
|
|
left_indices, right_indices,
|
|
left_hw_map, right_hw_map)
|
|
|
|
|
|
def retarget_hands(left_retargeting, right_retargeting,
|
|
left_indices, right_indices,
|
|
left_hw_map, right_hw_map,
|
|
left_hand_pos, right_hand_pos):
|
|
"""Compute 12 normalized Inspire hand values from hand positions."""
|
|
hand_cmd = np.ones(12)
|
|
|
|
left_valid = not np.all(left_hand_pos == 0.0)
|
|
right_valid = not np.all(right_hand_pos == 0.0)
|
|
|
|
if left_valid:
|
|
ref_value = left_hand_pos[left_indices[1, :]] - left_hand_pos[left_indices[0, :]]
|
|
q_rad = left_retargeting.retarget(ref_value)
|
|
q_hw = q_rad[left_hw_map]
|
|
for idx in range(6):
|
|
min_val, max_val = INSPIRE_RANGES[idx]
|
|
hand_cmd[6 + idx] = np.clip((max_val - q_hw[idx]) / (max_val - min_val), 0.0, 1.0)
|
|
|
|
if right_valid:
|
|
ref_value = right_hand_pos[right_indices[1, :]] - right_hand_pos[right_indices[0, :]]
|
|
q_rad = right_retargeting.retarget(ref_value)
|
|
q_hw = q_rad[right_hw_map]
|
|
for idx in range(6):
|
|
min_val, max_val = INSPIRE_RANGES[idx]
|
|
hand_cmd[idx] = np.clip((max_val - q_hw[idx]) / (max_val - min_val), 0.0, 1.0)
|
|
|
|
return hand_cmd
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Main loop
|
|
# ---------------------------------------------------------------------------
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description="Retargeting bridge v4: Quest 3 full body -> G1 direct joint mapping -> DDS")
|
|
parser.add_argument("--port", type=int, default=8765)
|
|
parser.add_argument("--host", default="0.0.0.0")
|
|
parser.add_argument("--dds-domain", type=int, default=1)
|
|
parser.add_argument("--hz", type=float, default=50.0)
|
|
parser.add_argument("--no-hands", action="store_true")
|
|
parser.add_argument("--no-waist", action="store_true", help="Disable waist tracking")
|
|
parser.add_argument("--no-arms", action="store_true", help="Disable arm tracking")
|
|
parser.add_argument("--mirror", action="store_true")
|
|
parser.add_argument("--verbose", action="store_true")
|
|
parser.add_argument("--cal-delay", type=float, default=10.0,
|
|
help="Seconds to wait before auto-calibrating (default: 10.0)")
|
|
parser.add_argument("--gain", type=float, default=None,
|
|
help="Joint angle gain multiplier (default: 1.4)")
|
|
parser.add_argument("--test", choices=["left", "right", "both", "wave"])
|
|
parser.add_argument("--test-hands", action="store_true")
|
|
parser.add_argument("--solo-joint", type=str, default=None,
|
|
help="Isolate a single joint for testing. Options: "
|
|
"l_sh_pitch, l_sh_roll, l_sh_yaw, l_elbow, "
|
|
"l_wr_roll, l_wr_pitch, l_wr_yaw")
|
|
args = parser.parse_args()
|
|
|
|
if args.solo_joint is not None:
|
|
global SOLO_JOINT
|
|
SOLO_JOINT = args.solo_joint
|
|
|
|
logging.basicConfig(
|
|
level=logging.DEBUG if args.verbose else logging.INFO,
|
|
format="%(asctime)s [%(name)s] %(levelname)s: %(message)s"
|
|
)
|
|
|
|
# --- Start teleop server (WebSocket + shared memory) ---
|
|
logger.info(f"Starting teleop server on ws://{args.host}:{args.port}")
|
|
tv_wrapper = NativeTeleWrapper(port=args.port, host=args.host)
|
|
tv_wrapper.start()
|
|
|
|
# --- Initialize DDS ---
|
|
dds = None
|
|
for attempt in range(60):
|
|
try:
|
|
dds = DDSPublisher(domain_id=args.dds_domain)
|
|
break
|
|
except Exception as e:
|
|
logger.warning(f"DDS init attempt {attempt+1} failed ({e}), retrying in 2s...")
|
|
time.sleep(2.0)
|
|
if dds is None:
|
|
logger.error("Failed to initialize DDS after 60 attempts, exiting.")
|
|
sys.exit(1)
|
|
|
|
# --- Test mode ---
|
|
if args.test:
|
|
_run_test_mode(args, dds)
|
|
return
|
|
|
|
# --- Initialize hand retargeting ---
|
|
hand_data = init_hand_retargeting() if not args.no_hands else None
|
|
if hand_data:
|
|
l_retarget, r_retarget, l_indices, r_indices, l_hw_map, r_hw_map = hand_data
|
|
|
|
# --- Control loop state ---
|
|
interval = 1.0 / args.hz
|
|
max_step = MAX_RATE * interval # rad per step
|
|
running = True
|
|
current_angles = np.zeros(NUM_JOINTS)
|
|
smoothed_upper = np.zeros(17) # joints 12-28
|
|
current_hands = np.ones(12)
|
|
tracking_timeout = 0.5
|
|
return_to_zero_rate = 0.02
|
|
last_valid_time = 0.0
|
|
startup_ramp = 0.0
|
|
startup_ramp_duration = 2.0
|
|
startup_time = None
|
|
step_count = 0
|
|
retarget_error_count = 0
|
|
|
|
# Calibration state
|
|
cal = CalibrationData()
|
|
first_data_time = None
|
|
was_tracking = False # track connection state for re-calibration
|
|
|
|
def signal_handler(sig, frame):
|
|
nonlocal running
|
|
running = False
|
|
|
|
signal.signal(signal.SIGINT, signal_handler)
|
|
signal.signal(signal.SIGTERM, signal_handler)
|
|
|
|
logger.info(f"Bridge v4 running at {args.hz} Hz (DIRECT retargeting, no IK)")
|
|
logger.info(f" Waist={'ON' if not args.no_waist else 'OFF'}, "
|
|
f"Arms={'ON' if not args.no_arms else 'OFF'}, "
|
|
f"Hands={'ON' if hand_data else 'OFF'}")
|
|
logger.info(f" Auto-calibration delay: {args.cal_delay}s after first tracking frame")
|
|
logger.info("Waiting for Quest 3...")
|
|
|
|
while running:
|
|
t_start = time.perf_counter()
|
|
|
|
# Read tracking data (for hand positions)
|
|
tele_data = tv_wrapper.get_tele_data()
|
|
data_time = tv_wrapper.last_data_time
|
|
now = time.time()
|
|
|
|
# Read body joints directly from shared memory (world-space pose7)
|
|
with tv_wrapper.server.body_joints_shared.get_lock():
|
|
bj_raw = np.array(tv_wrapper.server.body_joints_shared[:])
|
|
has_body_joints = np.any(bj_raw != 0)
|
|
|
|
if data_time > 0 and (now - data_time) < tracking_timeout:
|
|
last_valid_time = now
|
|
is_tracking = True
|
|
|
|
# Track when first data arrives
|
|
if first_data_time is None:
|
|
first_data_time = now
|
|
logger.info("First tracking data received")
|
|
|
|
# Detect reconnection: tracking resumed after being lost
|
|
if not was_tracking and cal.calibrated:
|
|
logger.info("Tracking resumed after disconnect — RESETTING calibration")
|
|
cal = CalibrationData()
|
|
first_data_time = now
|
|
smoothed_upper = np.zeros(17)
|
|
startup_ramp = 0.0
|
|
startup_time = None
|
|
|
|
was_tracking = True
|
|
|
|
# Startup ramp (starts after calibration)
|
|
if startup_time is not None:
|
|
elapsed_startup = now - startup_time
|
|
startup_ramp = min(elapsed_startup / startup_ramp_duration, 1.0)
|
|
|
|
# --- Parse body joints ---
|
|
if has_body_joints:
|
|
bj = parse_body_joints(bj_raw)
|
|
|
|
# --- Auto-calibrate after delay ---
|
|
if not cal.calibrated and first_data_time is not None:
|
|
if (now - first_data_time) >= args.cal_delay:
|
|
if all_joints_valid(bj):
|
|
if cal.capture(bj):
|
|
logger.info("CALIBRATED — neutral pose captured. Starting retargeting.")
|
|
# Log calibration reference quaternions for debugging
|
|
l_up = bj_raw[BJ_L_UPPER*7:(BJ_L_UPPER+1)*7]
|
|
r_up = bj_raw[BJ_R_UPPER*7:(BJ_R_UPPER+1)*7]
|
|
logger.info(f" Cal ref L_upper quat=[{l_up[3]:.4f},{l_up[4]:.4f},{l_up[5]:.4f},{l_up[6]:.4f}]")
|
|
logger.info(f" Cal ref R_upper quat=[{r_up[3]:.4f},{r_up[4]:.4f},{r_up[5]:.4f},{r_up[6]:.4f}]")
|
|
startup_time = now
|
|
else:
|
|
logger.warning("Calibration capture failed, retrying next frame...")
|
|
else:
|
|
missing = [k for k in ['hips','chest','l_upper','l_lower','l_wrist',
|
|
'r_upper','r_lower','r_wrist'] if bj[k] is None]
|
|
if step_count % 50 == 0:
|
|
logger.info(f"Waiting for all body joints (missing: {missing})")
|
|
|
|
# --- Retarget body joints ---
|
|
if cal.calibrated and all_joints_valid(bj):
|
|
try:
|
|
raw_angles = compute_all_angles(bj, cal)
|
|
raw_angles = apply_limits(raw_angles)
|
|
|
|
# Zero out disabled groups
|
|
if args.no_waist:
|
|
raw_angles[0:3] = 0.0
|
|
if args.no_arms:
|
|
raw_angles[3:17] = 0.0
|
|
|
|
# Smooth
|
|
smoothed_upper = smooth_angles(smoothed_upper, raw_angles, EMA_ALPHA, max_step)
|
|
|
|
# Apply startup ramp and write to output
|
|
current_angles[12:29] = smoothed_upper * startup_ramp
|
|
|
|
except Exception as e:
|
|
retarget_error_count += 1
|
|
if retarget_error_count <= 5 or retarget_error_count % 100 == 0:
|
|
logger.warning(f"Retarget failed ({retarget_error_count}x): {e}")
|
|
|
|
# --- Hand retargeting --- (DISABLED: testing left arm only)
|
|
if False and hand_data and cal.calibrated:
|
|
left_hand_pos = tele_data.left_hand_pos
|
|
right_hand_pos = tele_data.right_hand_pos
|
|
|
|
if args.mirror:
|
|
left_hand_pos, right_hand_pos = right_hand_pos, left_hand_pos
|
|
|
|
try:
|
|
raw_hands = retarget_hands(
|
|
l_retarget, r_retarget,
|
|
l_indices, r_indices,
|
|
l_hw_map, r_hw_map,
|
|
left_hand_pos, right_hand_pos)
|
|
current_hands = raw_hands * startup_ramp + (1.0 - startup_ramp) * 1.0
|
|
except Exception as e:
|
|
logger.warning(f"Hand retarget failed: {e}")
|
|
|
|
else:
|
|
# No tracking data or stale
|
|
was_tracking = False
|
|
if last_valid_time > 0 and (now - last_valid_time) > tracking_timeout:
|
|
# Gradually return to zero
|
|
for i in range(12, NUM_JOINTS):
|
|
if abs(current_angles[i]) > return_to_zero_rate:
|
|
current_angles[i] -= np.sign(current_angles[i]) * return_to_zero_rate
|
|
else:
|
|
current_angles[i] = 0.0
|
|
smoothed_upper *= 0.95 # decay smoothed state too
|
|
current_hands = np.minimum(current_hands + 0.02, 1.0)
|
|
|
|
# --- Publish ---
|
|
dds.publish_body(current_angles)
|
|
if hand_data:
|
|
dds.publish_hands(current_hands)
|
|
|
|
# --- Status logging ---
|
|
step_count += 1
|
|
log_interval = int(args.hz * (1 if args.verbose else 5))
|
|
if log_interval > 0 and step_count % log_interval == 0:
|
|
tracking = data_time > 0 and (now - data_time) < tracking_timeout
|
|
status = "TRACKING" if (tracking and cal.calibrated) else (
|
|
"CALIBRATING" if (tracking and not cal.calibrated) else "WAITING")
|
|
ramp_pct = int(startup_ramp * 100)
|
|
waist = current_angles[12:15]
|
|
l_sh = current_angles[15:18]
|
|
l_el = current_angles[18]
|
|
r_sh = current_angles[22:25]
|
|
r_el = current_angles[25]
|
|
logger.info(
|
|
f"[{status}] step={step_count} ramp={ramp_pct}% "
|
|
f"waist=[{waist[0]:+.2f},{waist[1]:+.2f},{waist[2]:+.2f}] "
|
|
f"L_sh=[{l_sh[0]:+.2f},{l_sh[1]:+.2f},{l_sh[2]:+.2f}] L_el={l_el:+.2f} "
|
|
f"R_sh=[{r_sh[0]:+.2f},{r_sh[1]:+.2f},{r_sh[2]:+.2f}] R_el={r_el:+.2f}")
|
|
if args.verbose and tracking and has_body_joints:
|
|
logger.debug(
|
|
f" Full upper body: {np.array2string(current_angles[12:29], precision=3, separator=',')}")
|
|
# Log raw quaternions for L/R upper arms to diagnose tracking issues
|
|
l_upper_q = bj_raw[BJ_L_UPPER*7:(BJ_L_UPPER+1)*7]
|
|
r_upper_q = bj_raw[BJ_R_UPPER*7:(BJ_R_UPPER+1)*7]
|
|
l_lower_q = bj_raw[BJ_L_LOWER*7:(BJ_L_LOWER+1)*7]
|
|
r_lower_q = bj_raw[BJ_R_LOWER*7:(BJ_R_LOWER+1)*7]
|
|
logger.debug(
|
|
f" L_upper_q=[{l_upper_q[3]:+.4f},{l_upper_q[4]:+.4f},{l_upper_q[5]:+.4f},{l_upper_q[6]:+.4f}] "
|
|
f"R_upper_q=[{r_upper_q[3]:+.4f},{r_upper_q[4]:+.4f},{r_upper_q[5]:+.4f},{r_upper_q[6]:+.4f}]")
|
|
logger.debug(
|
|
f" L_lower_q=[{l_lower_q[3]:+.4f},{l_lower_q[4]:+.4f},{l_lower_q[5]:+.4f},{l_lower_q[6]:+.4f}] "
|
|
f"R_lower_q=[{r_lower_q[3]:+.4f},{r_lower_q[4]:+.4f},{r_lower_q[5]:+.4f},{r_lower_q[6]:+.4f}]")
|
|
if retarget_error_count > 0:
|
|
logger.debug(f" Retarget errors: {retarget_error_count}")
|
|
|
|
sleep_time = interval - (time.perf_counter() - t_start)
|
|
if sleep_time > 0:
|
|
time.sleep(sleep_time)
|
|
|
|
logger.info("Bridge shutting down")
|
|
|
|
|
|
def _run_test_mode(args, dds):
|
|
"""Run test mode: send known poses without Quest."""
|
|
logger.info(f"TEST MODE: '{args.test}' — sending fixed poses (no Quest needed)")
|
|
running = True
|
|
|
|
def signal_handler(sig, frame):
|
|
nonlocal running
|
|
running = False
|
|
|
|
signal.signal(signal.SIGINT, signal_handler)
|
|
signal.signal(signal.SIGTERM, signal_handler)
|
|
|
|
interval = 1.0 / args.hz
|
|
step_count = 0
|
|
t0 = time.time()
|
|
|
|
while running:
|
|
t_start = time.perf_counter()
|
|
angles = np.zeros(NUM_JOINTS)
|
|
elapsed = time.time() - t0
|
|
|
|
if args.test == "left":
|
|
angles[15] = 0.5; angles[16] = 0.3; angles[18] = 0.4
|
|
elif args.test == "right":
|
|
angles[22] = 0.5; angles[23] = -0.3; angles[25] = 0.4
|
|
elif args.test == "both":
|
|
angles[15] = 0.5; angles[16] = 0.3; angles[18] = 0.4
|
|
angles[22] = -0.5; angles[23] = -0.3; angles[25] = 0.8
|
|
elif args.test == "wave":
|
|
wave = np.sin(elapsed * 1.5)
|
|
angles[15] = 0.8 * wave; angles[18] = 0.3 + 0.3 * wave
|
|
angles[22] = -0.8 * wave; angles[25] = 0.3 - 0.3 * wave
|
|
|
|
dds.publish_body(angles)
|
|
|
|
if args.test_hands:
|
|
hand_vals = np.ones(12)
|
|
cycle = (elapsed % 4.0) / 4.0
|
|
curl = 1.0 - np.sin(cycle * np.pi)
|
|
for i in [0, 1, 2, 3, 6, 7, 8, 9]:
|
|
hand_vals[i] = curl
|
|
hand_vals[4] = 0.5 + 0.5 * curl
|
|
hand_vals[10] = 0.5 + 0.5 * curl
|
|
hand_vals[5] = 0.5; hand_vals[11] = 0.5
|
|
dds.publish_hands(hand_vals)
|
|
|
|
step_count += 1
|
|
if step_count % int(args.hz * 2) == 0:
|
|
logger.info(f"[TEST:{args.test}] step={step_count}")
|
|
|
|
sleep_time = interval - (time.perf_counter() - t_start)
|
|
if sleep_time > 0:
|
|
time.sleep(sleep_time)
|
|
|
|
logger.info("Test mode shutting down")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|