From 033cfb3d0b2027c70698e9d2643bb13a182fc952 Mon Sep 17 00:00:00 2001
From: Martino Russi <nopyeps@gmail.com>
Date: Wed, 3 Dec 2025 17:02:18 +0100
Subject: [PATCH] add amazon/unitree locomotion policies

---
 examples/unitree_g1/holosoma_locomotion.py    | 507 ++++++++++++++++++
 examples/unitree_g1/unitree_rl_locomotion.py  | 460 ++++++++++++++++
 .../robots/unitree_g1/config_unitree_g1.py    |   2 +-
 3 files changed, 968 insertions(+), 1 deletion(-)
 create mode 100644 examples/unitree_g1/holosoma_locomotion.py
 create mode 100644 examples/unitree_g1/unitree_rl_locomotion.py

diff --git a/examples/unitree_g1/holosoma_locomotion.py b/examples/unitree_g1/holosoma_locomotion.py
new file mode 100644
index 000000000..f1ba06537
--- /dev/null
+++ b/examples/unitree_g1/holosoma_locomotion.py
@@ -0,0 +1,507 @@
+#!/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Example: Holosoma 29-DOF Whole-Body Locomotion
+
+This example demonstrates loading Amazon/Holosoma 29-DOF whole-body locomotion
+policies and running them on the Unitree G1 robot.
+
+Key differences from GR00T:
+- Single policy (not dual Balance/Walk)
+- 100D observations, 29D actions (all joints)
+- Phase-based gait with standing/walking modes
+"""
+
+import argparse
+import logging
+import threading
+import time
+
+import numpy as np
+import onnxruntime as ort
+from huggingface_hub import hf_hub_download
+from scipy.spatial.transform import Rotation as R
+
+from lerobot.robots.unitree_g1.config_unitree_g1 import UnitreeG1Config
+from lerobot.robots.unitree_g1.unitree_g1 import UnitreeG1
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Default joint angles from holosoma (29 DOF)
+# fmt: off
+HOLOSOMA_DEFAULT_ANGLES = np.array([
+    -0.312, 0.0, 0.0, 0.669, -0.363, 0.0,  # left leg (hip_pitch, hip_roll, hip_yaw, knee, ankle_pitch, ankle_roll)
+    -0.312, 0.0, 0.0, 0.669, -0.363, 0.0,  # right leg
+    0.0, 0.0, 0.0,                          # waist (yaw, roll, pitch)
+    0.2, 0.2, 0.0, 0.6, 0.0, 0.0, 0.0,     # left arm (shoulder_pitch/roll/yaw, elbow, wrist_roll/pitch/yaw)
+    0.2, -0.2, 0.0, 0.6, 0.0, 0.0, 0.0,    # right arm
+], dtype=np.float32)
+
+# KP/KD values from holosoma (tuned for G1 hardware)
+HOLOSOMA_KP = np.array([
+    40.179238471,   # left_hip_pitch
+    99.098427777,   # left_hip_roll
+    40.179238471,   # left_hip_yaw
+    99.098427777,   # left_knee
+    28.501246196,   # left_ankle_pitch
+    28.501246196,   # left_ankle_roll
+    40.179238471,   # right_hip_pitch
+    99.098427777,   # right_hip_roll
+    40.179238471,   # right_hip_yaw
+    99.098427777,   # right_knee
+    28.501246196,   # right_ankle_pitch
+    28.501246196,   # right_ankle_roll
+    40.179238471,   # waist_yaw
+    28.501246196,   # waist_roll
+    28.501246196,   # waist_pitch
+    14.250623098,   # left_shoulder_pitch
+    14.250623098,   # left_shoulder_roll
+    14.250623098,   # left_shoulder_yaw
+    14.250623098,   # left_elbow
+    14.250623098,   # left_wrist_roll
+    16.778327481,   # left_wrist_pitch
+    16.778327481,   # left_wrist_yaw
+    14.250623098,   # right_shoulder_pitch
+    14.250623098,   # right_shoulder_roll
+    14.250623098,   # right_shoulder_yaw
+    14.250623098,   # right_elbow
+    14.250623098,   # right_wrist_roll
+    16.778327481,   # right_wrist_pitch
+    16.778327481,   # right_wrist_yaw
+], dtype=np.float32)
+
+HOLOSOMA_KD = np.array([
+    2.557889765,    # left_hip_pitch
+    6.308801854,    # left_hip_roll
+    2.557889765,    # left_hip_yaw
+    6.308801854,    # left_knee
+    1.814445687,    # left_ankle_pitch
+    1.814445687,    # left_ankle_roll
+    2.557889765,    # right_hip_pitch
+    6.308801854,    # right_hip_roll
+    2.557889765,    # right_hip_yaw
+    6.308801854,    # right_knee
+    1.814445687,    # right_ankle_pitch
+    1.814445687,    # right_ankle_roll
+    2.557889765,    # waist_yaw
+    1.814445687,    # waist_roll
+    1.814445687,    # waist_pitch
+    0.907222843,    # left_shoulder_pitch
+    0.907222843,    # left_shoulder_roll
+    0.907222843,    # left_shoulder_yaw
+    0.907222843,    # left_elbow
+    0.907222843,    # left_wrist_roll
+    1.068141502,    # left_wrist_pitch
+    1.068141502,    # left_wrist_yaw
+    0.907222843,    # right_shoulder_pitch
+    0.907222843,    # right_shoulder_roll
+    0.907222843,    # right_shoulder_yaw
+    0.907222843,    # right_elbow
+    0.907222843,    # right_wrist_roll
+    1.068141502,    # right_wrist_pitch
+    1.068141502,    # right_wrist_yaw
+], dtype=np.float32)
+# fmt: on
+
+# G1 model configuration
+G1_MODEL = "g1_23"  # or "g1_29"
+MISSING_JOINTS = []
+if G1_MODEL == "g1_23":
+    # Joints that G1 23-DOF doesn't have (freeze these)
+    # 12: waist_yaw, 14: waist_pitch
+    # 20: left_wrist_pitch, 21: left_wrist_yaw
+    # 27: right_wrist_pitch, 28: right_wrist_yaw
+    MISSING_JOINTS = [12, 14, 20, 21, 27, 28]
+
+# Control parameters
+LOCOMOTION_CONTROL_DT = 0.02  # 50Hz control rate
+LOCOMOTION_ACTION_SCALE = 0.25
+ANG_VEL_SCALE = 0.25
+DOF_POS_SCALE = 1.0
+DOF_VEL_SCALE = 0.05
+
+# Gait parameters
+GAIT_PERIOD = 1.0  # seconds
+
+DEFAULT_HOLOSOMA_REPO_ID = "nepyope/holosoma_locomotion"
+
+
+def load_holosoma_policy(
+    repo_id: str = DEFAULT_HOLOSOMA_REPO_ID,
+    policy_name: str = "fastsac",
+) -> ort.InferenceSession:
+    """Load Holosoma 29-DOF locomotion policy from Hugging Face Hub.
+
+    Args:
+        repo_id: Hugging Face Hub repository ID containing the ONNX policies.
+        policy_name: Policy variant to load ("fastsac" or "ppo").
+    """
+    filename_map = {
+        "fastsac": "fastsac_g1_29dof.onnx",
+        "ppo": "ppo_g1_29dof.onnx",
+    }
+
+    if policy_name not in filename_map:
+        raise ValueError(f"Unknown policy_name: {policy_name}. Must be one of {list(filename_map.keys())}")
+
+    logger.info(f"Loading Holosoma {policy_name} policy from Hugging Face Hub ({repo_id})...")
+
+    policy_path = hf_hub_download(
+        repo_id=repo_id,
+        filename=filename_map[policy_name],
+    )
+
+    policy = ort.InferenceSession(policy_path)
+
+    logger.info(f"Holosoma {policy_name} policy loaded successfully")
+    logger.info(f"  Input: {policy.get_inputs()[0].name}, shape: {policy.get_inputs()[0].shape}")
+    logger.info(f"  Output: {policy.get_outputs()[0].name}, shape: {policy.get_outputs()[0].shape}")
+
+    return policy
+
+
+class HolosomaLocomotionController:
+    """
+    Handles Holosoma-style 29-DOF whole-body locomotion control for the Unitree G1 robot.
+
+    This controller manages:
+    - Single ONNX policy (FastSAC or PPO)
+    - 100D observations (single frame)
+    - 29D action output (all joints: legs + waist + arms)
+    - Phase-based gait with standing/walking modes
+    """
+
+    def __init__(self, policy, robot, config):
+        self.policy = policy
+        self.robot = robot
+        self.config = config
+
+        # Velocity commands (vx, vy, yaw_rate)
+        self.locomotion_cmd = np.array([0.0, 0.0, 0.0], dtype=np.float32)
+
+        # State variables (29 DOF)
+        self.qj = np.zeros(29, dtype=np.float32)
+        self.dqj = np.zeros(29, dtype=np.float32)
+        self.locomotion_action = np.zeros(29, dtype=np.float32)
+        self.locomotion_obs = np.zeros(100, dtype=np.float32)
+
+        # Phase state for gait (2D: left foot, right foot)
+        self.phase = np.zeros((1, 2), dtype=np.float32)
+        self.phase[0, 0] = 0.0      # left foot starts at 0
+        self.phase[0, 1] = np.pi    # right foot starts at π (opposite phase)
+        self.phase_dt = 2 * np.pi / (50.0 * GAIT_PERIOD)  # 50Hz control rate
+        self.is_standing = False
+
+        # Store last unscaled action for observation (policy expects previous actions)
+        self.last_unscaled_action = np.zeros(29, dtype=np.float32)
+
+        # Counter for logging
+        self.counter = 0
+
+        # Thread management
+        self.locomotion_running = False
+        self.locomotion_thread = None
+
+        logger.info("HolosomaLocomotionController initialized")
+        logger.info(f"  Observation dim: 100, Action dim: 29")
+        logger.info(f"  Missing joints (G1 23-DOF): {MISSING_JOINTS}")
+
+    def _transform_imu_data(self, waist_yaw, waist_yaw_omega, imu_quat, imu_omega):
+        """Transform IMU data from torso to pelvis frame."""
+        RzWaist = R.from_euler("z", waist_yaw).as_matrix()
+        R_torso = R.from_quat([imu_quat[1], imu_quat[2], imu_quat[3], imu_quat[0]]).as_matrix()
+        R_pelvis = np.dot(R_torso, RzWaist.T)
+        w = np.dot(RzWaist, imu_omega) - np.array([0, 0, waist_yaw_omega])
+        return R.from_matrix(R_pelvis).as_quat()[[3, 0, 1, 2]], w
+
+    def holosoma_locomotion_run(self):
+        """29-DOF whole-body locomotion policy loop - controls ALL 29 joints."""
+        self.counter += 1
+
+        if self.counter == 1:
+            print("\n" + "=" * 60)
+            print("🚀 RUNNING HOLOSOMA 29-DOF LOCOMOTION POLICY")
+            print("   100D observations → 29D actions (all joints)")
+            print("=" * 60 + "\n")
+
+        # Get current observation
+        robot_state = self.robot.get_observation()
+        if robot_state is None:
+            return
+
+        # Get command from remote controller
+        if robot_state.wireless_remote is not None:
+            self.robot.remote_controller.set(robot_state.wireless_remote)
+        else:
+            self.robot.remote_controller.lx = 0.0
+            self.robot.remote_controller.ly = 0.0
+            self.robot.remote_controller.rx = 0.0
+            self.robot.remote_controller.ry = 0.0
+
+        # Apply deadzone (0.1) like holosoma does
+        ly = self.robot.remote_controller.ly if abs(self.robot.remote_controller.ly) > 0.1 else 0.0
+        lx = self.robot.remote_controller.lx if abs(self.robot.remote_controller.lx) > 0.1 else 0.0
+        rx = self.robot.remote_controller.rx if abs(self.robot.remote_controller.rx) > 0.1 else 0.0
+
+        self.locomotion_cmd[0] = ly       # forward/backward
+        self.locomotion_cmd[1] = -lx      # left/right (inverted)
+        self.locomotion_cmd[2] = -rx      # yaw (inverted)
+
+        # Get ALL 29 joint positions and velocities
+        for i in range(29):
+            self.qj[i] = robot_state.motor_state[i].q
+            self.dqj[i] = robot_state.motor_state[i].dq
+
+        # Get IMU data
+        quat = robot_state.imu_state.quaternion
+        ang_vel = np.array(robot_state.imu_state.gyroscope, dtype=np.float32)
+
+        # Transform IMU from torso to pelvis frame (if using torso IMU)
+        #waist_yaw = robot_state.motor_state[12].q
+        #waist_yaw_omega = robot_state.motor_state[12].dq
+        #quat, ang_vel = self._transform_imu_data(waist_yaw, waist_yaw_omega, quat, ang_vel)
+
+        # Zero out observations for joints missing in G1 23-DOF
+        for joint_idx in MISSING_JOINTS:
+            self.qj[joint_idx] = 0.0
+            self.dqj[joint_idx] = 0.0
+
+        # Create observation with correct scaling factors
+        gravity_orientation = self.robot.get_gravity_orientation(quat)
+        qj_obs = (self.qj - HOLOSOMA_DEFAULT_ANGLES) * DOF_POS_SCALE
+        dqj_obs = self.dqj * DOF_VEL_SCALE
+        ang_vel_scaled = ang_vel * ANG_VEL_SCALE
+
+        # Update phase using holosoma's method
+        cmd_norm = np.linalg.norm(self.locomotion_cmd[:2])
+        ang_cmd_norm = np.abs(self.locomotion_cmd[2])
+
+        if cmd_norm < 0.01 and ang_cmd_norm < 0.01:
+            # Standing still - both feet at π
+            self.phase[0, :] = np.pi * np.ones(2)
+            self.is_standing = True
+        elif self.is_standing:
+            # Resuming walking from standing - reset phase to initial state
+            self.phase = np.array([[0.0, np.pi]], dtype=np.float32)
+            self.is_standing = False
+        else:
+            # Walking - update phase
+            phase_tp1 = self.phase + self.phase_dt
+            self.phase = np.fmod(phase_tp1 + np.pi, 2 * np.pi) - np.pi
+
+        # Compute sin/cos phase for both feet
+        sin_phase = np.sin(self.phase[0, :])  # shape (2,)
+        cos_phase = np.cos(self.phase[0, :])  # shape (2,)
+
+        # Build 100D observation vector (components in ALPHABETICAL order!)
+        # Joints within each 29D component stay in motor index order (0-28)
+        self.locomotion_obs[0:29] = self.last_unscaled_action   # 1. actions (previous UNSCALED, ×1.0)
+        self.locomotion_obs[29:32] = ang_vel_scaled              # 2. base_ang_vel (×0.25)
+        self.locomotion_obs[32] = self.locomotion_cmd[2]         # 3. command_ang_vel (yaw, ×1.0)
+        self.locomotion_obs[33:35] = self.locomotion_cmd[:2]     # 4. command_lin_vel (vx, vy, ×1.0)
+        self.locomotion_obs[35:37] = cos_phase                   # 5. cos_phase (2D: left, right)
+        self.locomotion_obs[37:66] = qj_obs                      # 6. dof_pos (relative, ×1.0)
+        self.locomotion_obs[66:95] = dqj_obs                     # 7. dof_vel (×0.05)
+        self.locomotion_obs[95:98] = gravity_orientation         # 8. projected_gravity (×1.0)
+        self.locomotion_obs[98:100] = sin_phase                  # 9. sin_phase (2D: left, right)
+
+        # Run policy inference (ONNX)
+        obs_input = self.locomotion_obs.reshape(1, -1).astype(np.float32)
+        ort_inputs = {self.policy.get_inputs()[0].name: obs_input}
+        ort_outs = self.policy.run(None, ort_inputs)
+
+        # Post-process ONNX output: clip to ±100, then scale by 0.25
+        raw_action = ort_outs[0].squeeze()
+        clipped_action = np.clip(raw_action, -100.0, 100.0)
+
+        # Zero out actions for joints missing in G1 23-DOF
+        for joint_idx in MISSING_JOINTS:
+            clipped_action[joint_idx] = 0.0
+
+        self.last_unscaled_action = clipped_action.copy()  # Store UNSCALED for next obs
+        self.locomotion_action = clipped_action * LOCOMOTION_ACTION_SCALE  # Scale by 0.25 for motors
+
+        # Debug logging (first 3 iterations)
+        if self.counter <= 3:
+            print(f"\n[Holosoma Debug #{self.counter}]")
+            print(f"  Phase (left, right): ({self.phase[0, 0]:.3f}, {self.phase[0, 1]:.3f})")
+            print(f"  Cmd (vx, vy, yaw): ({self.locomotion_cmd[0]:.2f}, {self.locomotion_cmd[1]:.2f}, {self.locomotion_cmd[2]:.2f})")
+            print(f"  Raw action range: [{raw_action.min():.3f}, {raw_action.max():.3f}]")
+            print(f"  Scaled action range: [{self.locomotion_action.min():.3f}, {self.locomotion_action.max():.3f}]")
+
+        # Transform action to target joint positions (ALL 29 joints)
+        target_dof_pos = HOLOSOMA_DEFAULT_ANGLES + self.locomotion_action
+
+        # Send commands to ALL 29 motors
+        for i in range(29):
+            self.robot.msg.motor_cmd[i].q = target_dof_pos[i]
+            self.robot.msg.motor_cmd[i].qd = 0
+            self.robot.msg.motor_cmd[i].kp = HOLOSOMA_KP[i]
+            self.robot.msg.motor_cmd[i].kd = HOLOSOMA_KD[i]
+            self.robot.msg.motor_cmd[i].tau = 0
+
+        # Send command
+        self.robot.send_action(self.robot.msg)
+
+    def _locomotion_thread_loop(self):
+        """Background thread that runs the locomotion policy at specified rate."""
+        logger.info("Locomotion thread started")
+        while self.locomotion_running:
+            start_time = time.time()
+            try:
+                self.holosoma_locomotion_run()
+            except Exception as e:
+                logger.error(f"Error in locomotion loop: {e}")
+                import traceback
+                traceback.print_exc()
+
+            # Sleep to maintain control rate
+            elapsed = time.time() - start_time
+            sleep_time = max(0, LOCOMOTION_CONTROL_DT - elapsed)
+            time.sleep(sleep_time)
+        logger.info("Locomotion thread stopped")
+
+    def start_locomotion_thread(self):
+        if self.locomotion_running:
+            logger.warning("Locomotion thread already running")
+            return
+
+        logger.info("Starting locomotion control thread...")
+        self.locomotion_running = True
+        self.locomotion_thread = threading.Thread(target=self._locomotion_thread_loop, daemon=True)
+        self.locomotion_thread.start()
+
+        logger.info("Locomotion control thread started!")
+
+    def stop_locomotion_thread(self):
+        if not self.locomotion_running:
+            return
+
+        logger.info("Stopping locomotion control thread...")
+        self.locomotion_running = False
+        if self.locomotion_thread:
+            self.locomotion_thread.join(timeout=2.0)
+        logger.info("Locomotion control thread stopped")
+
+    def reset_robot(self):
+        """Move all 29 joints to default standing position over 3 seconds."""
+        logger.info("Moving all 29 joints to default position...")
+
+        total_time = 3.0
+        num_step = int(total_time / self.robot.control_dt)
+        default_pos = HOLOSOMA_DEFAULT_ANGLES
+
+        # Get current state
+        robot_state = self.robot.get_observation()
+
+        # Record current positions
+        init_dof_pos = np.zeros(29, dtype=np.float32)
+        for i in range(29):
+            init_dof_pos[i] = robot_state.motor_state[i].q
+
+        # Interpolate to target
+        for i in range(num_step):
+            alpha = i / num_step
+            for motor_idx in range(29):
+                target_pos = default_pos[motor_idx]
+                self.robot.msg.motor_cmd[motor_idx].q = (
+                    init_dof_pos[motor_idx] * (1 - alpha) + target_pos * alpha
+                )
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = HOLOSOMA_KP[motor_idx]
+                self.robot.msg.motor_cmd[motor_idx].kd = HOLOSOMA_KD[motor_idx]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            self.robot.msg.crc = self.robot.crc.Crc(self.robot.msg)
+            self.robot.lowcmd_publisher.Write(self.robot.msg)
+            time.sleep(self.robot.control_dt)
+
+        logger.info("Reached default position (all 29 joints)")
+
+        # Hold position for 2 seconds
+        logger.info("Holding default position for 2 seconds...")
+        hold_time = 2.0
+        num_hold_steps = int(hold_time / self.robot.control_dt)
+
+        for _ in range(num_hold_steps):
+            for motor_idx in range(29):
+                self.robot.msg.motor_cmd[motor_idx].q = default_pos[motor_idx]
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = HOLOSOMA_KP[motor_idx]
+                self.robot.msg.motor_cmd[motor_idx].kd = HOLOSOMA_KD[motor_idx]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            self.robot.msg.crc = self.robot.crc.Crc(self.robot.msg)
+            self.robot.lowcmd_publisher.Write(self.robot.msg)
+            time.sleep(self.robot.control_dt)
+
+        logger.info("Ready to start locomotion!")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Holosoma 29-DOF Locomotion Controller for Unitree G1")
+    parser.add_argument(
+        "--repo-id",
+        type=str,
+        default=DEFAULT_HOLOSOMA_REPO_ID,
+        help=f"Hugging Face Hub repo ID for Holosoma policies (default: {DEFAULT_HOLOSOMA_REPO_ID})",
+    )
+    parser.add_argument(
+        "--policy",
+        type=str,
+        default="fastsac",
+        choices=["fastsac", "ppo"],
+        help="Policy variant to load (default: fastsac)",
+    )
+    args = parser.parse_args()
+
+    # Load policy
+    policy = load_holosoma_policy(repo_id=args.repo_id, policy_name=args.policy)
+
+    # Initialize robot
+    config = UnitreeG1Config()
+    robot = UnitreeG1(config)
+
+    # Initialize holosoma locomotion controller
+    holosoma_controller = HolosomaLocomotionController(
+        policy=policy,
+        robot=robot,
+        config=config,
+    )
+
+    # Reset robot and start locomotion thread
+    try:
+        holosoma_controller.reset_robot()
+        holosoma_controller.start_locomotion_thread()
+
+        # Log status
+        logger.info(f"Robot initialized with Holosoma {args.policy} locomotion policy")
+        logger.info("Locomotion controller running in background thread")
+        logger.info("Use remote controller to command velocity:")
+        logger.info("  Left stick Y: forward/backward")
+        logger.info("  Left stick X: left/right")
+        logger.info("  Right stick X: rotate")
+        logger.info("Press Ctrl+C to stop")
+
+        # Keep robot alive
+        while True:
+            time.sleep(1.0)
+    except KeyboardInterrupt:
+        print("\nStopping locomotion...")
+        holosoma_controller.stop_locomotion_thread()
+        print("Done!")
+
diff --git a/examples/unitree_g1/unitree_rl_locomotion.py b/examples/unitree_g1/unitree_rl_locomotion.py
new file mode 100644
index 000000000..383637ebc
--- /dev/null
+++ b/examples/unitree_g1/unitree_rl_locomotion.py
@@ -0,0 +1,460 @@
+#!/usr/bin/env python
+
+# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+Example: Unitree RL 12-DOF Legs-Only Locomotion (TorchScript)
+
+This example demonstrates loading a 12-DOF legs-only locomotion policy
+(TorchScript .pt format) and running it on the Unitree G1 robot.
+
+Key characteristics:
+- Single TorchScript policy (.pt)
+- 47D observations, 12D actions (legs only)
+- Phase-based gait timing
+- Arms and waist held at fixed positions
+"""
+
+import argparse
+import logging
+import threading
+import time
+
+import numpy as np
+import torch
+from huggingface_hub import hf_hub_download
+from scipy.spatial.transform import Rotation as R
+
+from lerobot.robots.unitree_g1.config_unitree_g1 import UnitreeG1Config
+from lerobot.robots.unitree_g1.unitree_g1 import UnitreeG1
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# 12-DOF leg joint configuration
+# Joint order: [L_hip_pitch, L_hip_roll, L_hip_yaw, L_knee, L_ankle_pitch, L_ankle_roll,
+#               R_hip_pitch, R_hip_roll, R_hip_yaw, R_knee, R_ankle_pitch, R_ankle_roll]
+LEG_JOINT_INDICES = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
+
+# Default leg angles for standing
+DEFAULT_LEG_ANGLES = np.array([
+    -0.1, 0.0, 0.0, 0.3, -0.2, 0.0,   # left leg
+    -0.1, 0.0, 0.0, 0.3, -0.2, 0.0,   # right leg
+], dtype=np.float32)
+
+# KP/KD for leg joints
+LEG_KPS = np.array([150, 150, 150, 300, 40, 40, 150, 150, 150, 300, 40, 40], dtype=np.float32)
+LEG_KDS = np.array([6, 6, 6, 4, 2, 2, 6, 6, 6, 4, 2, 2], dtype=np.float32)
+
+# Waist configuration (held at zero)
+WAIST_JOINT_INDICES = [12, 13, 14]  # yaw, roll, pitch
+WAIST_KPS = np.array([250, 250, 250], dtype=np.float32)
+WAIST_KDS = np.array([5, 5, 5], dtype=np.float32)
+
+# Arm configuration (indices 15-28, held at initial position)
+ARM_JOINT_INDICES = list(range(15, 29))
+ARM_KPS = np.array([80, 80, 80, 80, 40, 40, 40,   # left arm (shoulder + wrist)
+                   80, 80, 80, 80, 40, 40, 40], dtype=np.float32)  # right arm
+ARM_KDS = np.array([3, 3, 3, 3, 1.5, 1.5, 1.5,
+                   3, 3, 3, 3, 1.5, 1.5, 1.5], dtype=np.float32)
+
+# Control parameters
+LOCOMOTION_CONTROL_DT = 0.02  # 50Hz control rate
+LOCOMOTION_ACTION_SCALE = 0.25
+ANG_VEL_SCALE = 0.25
+DOF_POS_SCALE = 1.0
+DOF_VEL_SCALE = 0.05
+CMD_SCALE = np.array([2.0, 2.0, 0.25], dtype=np.float32)
+MAX_CMD = np.array([0.8, 0.5, 1.57], dtype=np.float32)  # max vx, vy, yaw_rate
+
+# Gait parameters
+GAIT_PERIOD = 0.8  # seconds
+
+DEFAULT_REPO_ID = "nepyope/unitree_rl_locomotion"
+
+
+def load_torchscript_policy(
+    repo_id: str = DEFAULT_REPO_ID,
+    filename: str = "motion.pt",
+) -> torch.jit.ScriptModule:
+    """Load TorchScript locomotion policy from Hugging Face Hub.
+
+    Args:
+        repo_id: Hugging Face Hub repository ID containing the policy.
+        filename: Policy filename (default: motion.pt).
+    """
+    logger.info(f"Loading TorchScript policy from Hugging Face Hub ({repo_id}/{filename})...")
+
+    policy_path = hf_hub_download(
+        repo_id=repo_id,
+        filename=filename,
+    )
+
+    policy = torch.jit.load(policy_path)
+    policy.eval()
+
+    logger.info("TorchScript policy loaded successfully")
+
+    return policy
+
+
+class UnitreeRLLocomotionController:
+    """
+    Handles 12-DOF legs-only locomotion control for the Unitree G1 robot.
+
+    This controller manages:
+    - Single TorchScript policy
+    - 47D observations (single frame)
+    - 12D action output (legs only)
+    - Arms and waist held at fixed positions
+    - Phase-based gait timing
+    """
+
+    def __init__(self, policy, robot, config):
+        self.policy = policy
+        self.robot = robot
+        self.config = config
+
+        # Velocity commands (vx, vy, yaw_rate)
+        self.locomotion_cmd = np.array([0.0, 0.0, 0.0], dtype=np.float32)
+
+        # State variables (12 DOF legs)
+        self.qj = np.zeros(12, dtype=np.float32)
+        self.dqj = np.zeros(12, dtype=np.float32)
+        self.locomotion_action = np.zeros(12, dtype=np.float32)
+        self.locomotion_obs = np.zeros(47, dtype=np.float32)
+
+        # Initial arm positions (captured on reset)
+        self.initial_arm_positions = np.zeros(14, dtype=np.float32)
+
+        # Counter for phase calculation
+        self.counter = 0
+
+        # Thread management
+        self.locomotion_running = False
+        self.locomotion_thread = None
+
+        logger.info("UnitreeRLLocomotionController initialized")
+        logger.info("  Observation dim: 47, Action dim: 12 (legs only)")
+
+    def _transform_imu_data(self, waist_yaw, waist_yaw_omega, imu_quat, imu_omega):
+        """Transform IMU data from torso to pelvis frame."""
+        RzWaist = R.from_euler("z", waist_yaw).as_matrix()
+        R_torso = R.from_quat([imu_quat[1], imu_quat[2], imu_quat[3], imu_quat[0]]).as_matrix()
+        R_pelvis = np.dot(R_torso, RzWaist.T)
+        w = np.dot(RzWaist, imu_omega) - np.array([0, 0, waist_yaw_omega])
+        return R.from_matrix(R_pelvis).as_quat()[[3, 0, 1, 2]], w
+
+    def locomotion_run(self):
+        """12-DOF legs-only locomotion policy loop."""
+        self.counter += 1
+
+        if self.counter == 1:
+            print("\n" + "=" * 60)
+            print("🚀 RUNNING UNITREE RL 12-DOF LOCOMOTION POLICY")
+            print("   47D observations → 12D actions (legs only)")
+            print("   Arms and waist held at fixed positions")
+            print("=" * 60 + "\n")
+
+        # Get current observation
+        robot_state = self.robot.get_observation()
+        if robot_state is None:
+            return
+
+        # Get command from remote controller
+        if robot_state.wireless_remote is not None:
+            self.robot.remote_controller.set(robot_state.wireless_remote)
+        else:
+            self.robot.remote_controller.lx = 0.0
+            self.robot.remote_controller.ly = 0.0
+            self.robot.remote_controller.rx = 0.0
+            self.robot.remote_controller.ry = 0.0
+
+        self.locomotion_cmd[0] = self.robot.remote_controller.ly       # forward/backward
+        self.locomotion_cmd[1] = self.robot.remote_controller.lx * -1  # left/right (inverted)
+        self.locomotion_cmd[2] = self.robot.remote_controller.rx * -1  # yaw (inverted)
+
+        # Get leg joint positions and velocities (12 DOF)
+        for i, motor_idx in enumerate(LEG_JOINT_INDICES):
+            self.qj[i] = robot_state.motor_state[motor_idx].q
+            self.dqj[i] = robot_state.motor_state[motor_idx].dq
+
+        # Get IMU data
+        quat = robot_state.imu_state.quaternion
+        ang_vel = np.array(robot_state.imu_state.gyroscope, dtype=np.float32)
+
+        # Transform IMU from torso to pelvis frame
+        waist_yaw = robot_state.motor_state[12].q
+        waist_yaw_omega = robot_state.motor_state[12].dq
+        quat, ang_vel = self._transform_imu_data(waist_yaw, waist_yaw_omega, quat, ang_vel)
+
+        # Scale observations
+        gravity_orientation = self.robot.get_gravity_orientation(quat)
+        qj_obs = (self.qj - DEFAULT_LEG_ANGLES) * DOF_POS_SCALE
+        dqj_obs = self.dqj * DOF_VEL_SCALE
+        ang_vel_scaled = ang_vel * ANG_VEL_SCALE
+
+        # Calculate phase
+        count = self.counter * LOCOMOTION_CONTROL_DT
+        phase = (count % GAIT_PERIOD) / GAIT_PERIOD
+        sin_phase = np.sin(2 * np.pi * phase)
+        cos_phase = np.cos(2 * np.pi * phase)
+
+        # Build 47D observation vector
+        # [0:3]   - angular velocity (scaled)
+        # [3:6]   - gravity orientation
+        # [6:9]   - velocity command (scaled)
+        # [9:21]  - joint positions (12D, relative to default)
+        # [21:33] - joint velocities (12D, scaled)
+        # [33:45] - previous actions (12D)
+        # [45]    - sin_phase
+        # [46]    - cos_phase
+        self.locomotion_obs[0:3] = ang_vel_scaled
+        self.locomotion_obs[3:6] = gravity_orientation
+        self.locomotion_obs[6:9] = self.locomotion_cmd * CMD_SCALE * MAX_CMD
+        self.locomotion_obs[9:21] = qj_obs
+        self.locomotion_obs[21:33] = dqj_obs
+        self.locomotion_obs[33:45] = self.locomotion_action
+        self.locomotion_obs[45] = sin_phase
+        self.locomotion_obs[46] = cos_phase
+
+        # Run policy inference (TorchScript)
+        obs_tensor = torch.from_numpy(self.locomotion_obs).unsqueeze(0).float()
+        with torch.no_grad():
+            action_tensor = self.policy(obs_tensor)
+        self.locomotion_action = action_tensor.squeeze().numpy()
+
+        # Transform action to target joint positions
+        target_leg_pos = DEFAULT_LEG_ANGLES + self.locomotion_action * LOCOMOTION_ACTION_SCALE
+
+        # Debug logging (first 3 iterations)
+        if self.counter <= 3:
+            print(f"\n[Unitree RL Debug #{self.counter}]")
+            print(f"  Phase: {phase:.3f} (sin={sin_phase:.3f}, cos={cos_phase:.3f})")
+            print(f"  Cmd (vx, vy, yaw): ({self.locomotion_cmd[0]:.2f}, {self.locomotion_cmd[1]:.2f}, {self.locomotion_cmd[2]:.2f})")
+            print(f"  Action range: [{self.locomotion_action.min():.3f}, {self.locomotion_action.max():.3f}]")
+
+        # Send commands to LEG motors (0-11)
+        for i, motor_idx in enumerate(LEG_JOINT_INDICES):
+            self.robot.msg.motor_cmd[motor_idx].q = target_leg_pos[i]
+            self.robot.msg.motor_cmd[motor_idx].qd = 0
+            self.robot.msg.motor_cmd[motor_idx].kp = LEG_KPS[i]
+            self.robot.msg.motor_cmd[motor_idx].kd = LEG_KDS[i]
+            self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+        # Hold WAIST motors at zero (12, 13, 14)
+        for i, motor_idx in enumerate(WAIST_JOINT_INDICES):
+            self.robot.msg.motor_cmd[motor_idx].q = 0.0
+            self.robot.msg.motor_cmd[motor_idx].qd = 0
+            self.robot.msg.motor_cmd[motor_idx].kp = WAIST_KPS[i]
+            self.robot.msg.motor_cmd[motor_idx].kd = WAIST_KDS[i]
+            self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+        # Hold ARM motors at initial position (15-28)
+        for i, motor_idx in enumerate(ARM_JOINT_INDICES):
+            self.robot.msg.motor_cmd[motor_idx].q = self.initial_arm_positions[i]
+            self.robot.msg.motor_cmd[motor_idx].qd = 0
+            self.robot.msg.motor_cmd[motor_idx].kp = ARM_KPS[i]
+            self.robot.msg.motor_cmd[motor_idx].kd = ARM_KDS[i]
+            self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+        # Send command
+        self.robot.send_action(self.robot.msg)
+
+    def _locomotion_thread_loop(self):
+        """Background thread that runs the locomotion policy at specified rate."""
+        logger.info("Locomotion thread started")
+        while self.locomotion_running:
+            start_time = time.time()
+            try:
+                self.locomotion_run()
+            except Exception as e:
+                logger.error(f"Error in locomotion loop: {e}")
+                import traceback
+                traceback.print_exc()
+
+            # Sleep to maintain control rate
+            elapsed = time.time() - start_time
+            sleep_time = max(0, LOCOMOTION_CONTROL_DT - elapsed)
+            time.sleep(sleep_time)
+        logger.info("Locomotion thread stopped")
+
+    def start_locomotion_thread(self):
+        if self.locomotion_running:
+            logger.warning("Locomotion thread already running")
+            return
+
+        logger.info("Starting locomotion control thread...")
+        self.locomotion_running = True
+        self.locomotion_thread = threading.Thread(target=self._locomotion_thread_loop, daemon=True)
+        self.locomotion_thread.start()
+
+        logger.info("Locomotion control thread started!")
+
+    def stop_locomotion_thread(self):
+        if not self.locomotion_running:
+            return
+
+        logger.info("Stopping locomotion control thread...")
+        self.locomotion_running = False
+        if self.locomotion_thread:
+            self.locomotion_thread.join(timeout=2.0)
+        logger.info("Locomotion control thread stopped")
+
+    def reset_robot(self):
+        """Move legs to default standing position over 2 seconds (arms are captured and held)."""
+        logger.info("Moving legs to default position...")
+
+        total_time = 2.0
+        num_step = int(total_time / self.robot.control_dt)
+
+        # Get current state
+        robot_state = self.robot.get_observation()
+
+        # Capture initial arm positions (to hold during locomotion)
+        for i, motor_idx in enumerate(ARM_JOINT_INDICES):
+            self.initial_arm_positions[i] = robot_state.motor_state[motor_idx].q
+        logger.info(f"Captured initial arm positions: {self.initial_arm_positions[:4]}...")
+
+        # Record current leg positions
+        init_leg_pos = np.zeros(12, dtype=np.float32)
+        for i, motor_idx in enumerate(LEG_JOINT_INDICES):
+            init_leg_pos[i] = robot_state.motor_state[motor_idx].q
+
+        # Interpolate legs to default position
+        for step in range(num_step):
+            alpha = step / num_step
+
+            # Interpolate leg positions
+            for i, motor_idx in enumerate(LEG_JOINT_INDICES):
+                target_pos = DEFAULT_LEG_ANGLES[i]
+                self.robot.msg.motor_cmd[motor_idx].q = (
+                    init_leg_pos[i] * (1 - alpha) + target_pos * alpha
+                )
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = LEG_KPS[i]
+                self.robot.msg.motor_cmd[motor_idx].kd = LEG_KDS[i]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            # Hold waist at zero
+            for i, motor_idx in enumerate(WAIST_JOINT_INDICES):
+                self.robot.msg.motor_cmd[motor_idx].q = 0.0
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = WAIST_KPS[i]
+                self.robot.msg.motor_cmd[motor_idx].kd = WAIST_KDS[i]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            # Hold arms at initial position
+            for i, motor_idx in enumerate(ARM_JOINT_INDICES):
+                self.robot.msg.motor_cmd[motor_idx].q = self.initial_arm_positions[i]
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = ARM_KPS[i]
+                self.robot.msg.motor_cmd[motor_idx].kd = ARM_KDS[i]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            self.robot.msg.crc = self.robot.crc.Crc(self.robot.msg)
+            self.robot.lowcmd_publisher.Write(self.robot.msg)
+            time.sleep(self.robot.control_dt)
+
+        logger.info("Reached default leg position")
+
+        # Hold position for 2 seconds
+        logger.info("Holding default position for 2 seconds...")
+        hold_time = 2.0
+        num_hold_steps = int(hold_time / self.robot.control_dt)
+
+        for _ in range(num_hold_steps):
+            # Hold legs at default
+            for i, motor_idx in enumerate(LEG_JOINT_INDICES):
+                self.robot.msg.motor_cmd[motor_idx].q = DEFAULT_LEG_ANGLES[i]
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = LEG_KPS[i]
+                self.robot.msg.motor_cmd[motor_idx].kd = LEG_KDS[i]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            # Hold waist at zero
+            for i, motor_idx in enumerate(WAIST_JOINT_INDICES):
+                self.robot.msg.motor_cmd[motor_idx].q = 0.0
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = WAIST_KPS[i]
+                self.robot.msg.motor_cmd[motor_idx].kd = WAIST_KDS[i]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            # Hold arms at initial position
+            for i, motor_idx in enumerate(ARM_JOINT_INDICES):
+                self.robot.msg.motor_cmd[motor_idx].q = self.initial_arm_positions[i]
+                self.robot.msg.motor_cmd[motor_idx].qd = 0
+                self.robot.msg.motor_cmd[motor_idx].kp = ARM_KPS[i]
+                self.robot.msg.motor_cmd[motor_idx].kd = ARM_KDS[i]
+                self.robot.msg.motor_cmd[motor_idx].tau = 0
+
+            self.robot.msg.crc = self.robot.crc.Crc(self.robot.msg)
+            self.robot.lowcmd_publisher.Write(self.robot.msg)
+            time.sleep(self.robot.control_dt)
+
+        logger.info("Ready to start locomotion!")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Unitree RL 12-DOF Locomotion Controller for Unitree G1")
+    parser.add_argument(
+        "--repo-id",
+        type=str,
+        default=DEFAULT_REPO_ID,
+        help=f"Hugging Face Hub repo ID for policy (default: {DEFAULT_REPO_ID})",
+    )
+    parser.add_argument(
+        "--filename",
+        type=str,
+        default="motion.pt",
+        help="Policy filename (default: motion.pt)",
+    )
+    args = parser.parse_args()
+
+    # Load policy
+    policy = load_torchscript_policy(repo_id=args.repo_id, filename=args.filename)
+
+    # Initialize robot
+    config = UnitreeG1Config()
+    robot = UnitreeG1(config)
+
+    # Initialize locomotion controller
+    locomotion_controller = UnitreeRLLocomotionController(
+        policy=policy,
+        robot=robot,
+        config=config,
+    )
+
+    # Reset robot and start locomotion thread
+    try:
+        locomotion_controller.reset_robot()
+        locomotion_controller.start_locomotion_thread()
+
+        # Log status
+        logger.info("Robot initialized with Unitree RL locomotion policy")
+        logger.info("Locomotion controller running in background thread")
+        logger.info("Use remote controller to command velocity:")
+        logger.info("  Left stick Y: forward/backward")
+        logger.info("  Left stick X: left/right")
+        logger.info("  Right stick X: rotate")
+        logger.info("Press Ctrl+C to stop")
+
+        # Keep robot alive
+        while True:
+            time.sleep(1.0)
+    except KeyboardInterrupt:
+        print("\nStopping locomotion...")
+        locomotion_controller.stop_locomotion_thread()
+        print("Done!")
+
diff --git a/src/lerobot/robots/unitree_g1/config_unitree_g1.py b/src/lerobot/robots/unitree_g1/config_unitree_g1.py
index 575ad50bb..613929819 100644
--- a/src/lerobot/robots/unitree_g1/config_unitree_g1.py
+++ b/src/lerobot/robots/unitree_g1/config_unitree_g1.py
@@ -52,4 +52,4 @@ class UnitreeG1Config(RobotConfig):
     control_dt: float = 1.0 / 250.0  # 250Hz
 
     # socket config for ZMQ bridge
-    robot_ip: str = "192.168.123.164"
+    robot_ip: str = "172.18.129.215"