[software] 添加16DOF早期训练仿真与Sim2Real闭环

05_software/real/sim2real/interface/real_io.py

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+import time
+from typing import Callable, Dict, Tuple
+
+import numpy as np
+
+from interface.imu_client import IMUClient
+from interface.motor_driver import HardwareIO
+from tools.math_utils import LowPassFilter, MahonyFilter, get_gravity_orientation
+
+
+class RealIO:
+    def __init__(
+        self,
+        driver_factory: Callable[[str, str, bool], Tuple[object, object]],
+        motor_model: str,
+        can1_port: str,
+        can2_port: str,
+        imu_lib_path: str,
+        control_dt: float = 0.02,
+        kp_leg: float = 80.0,
+        kd_leg: float = 2.5,
+        kd_wheel: float = 2.0,
+        debug: bool = False,
+    ):
+        self.control_dt = control_dt
+        self.kp_leg = kp_leg
+        self.kd_leg = kd_leg
+        self.kd_wheel = kd_wheel
+
+        print("[RealIO] 初始化电机驱动...")
+        self.hw = HardwareIO(driver_factory, motor_model, can1_port, can2_port, debug)
+        print("[RealIO] 初始化 IMU...")
+        self.imu = IMUClient(lib_path=imu_lib_path)
+
+        self.imu_filter = MahonyFilter(kp=2.0, ki=0.0, dt=control_dt)
+        self.quat_wxyz = np.array([1.0, 0.0, 0.0, 0.0], dtype=np.float32)
+
+        self.lpf_legs = LowPassFilter(cutoff_freq=5.0, dt=control_dt, dim=12)
+        self.lpf_wheels = LowPassFilter(cutoff_freq=15.0, dt=control_dt, dim=4)
+
+        self._last_imu_age_ms = -1.0
+        self._last_imu_fresh = False
+
+    def connect(self, imu_timeout_ms: int = 8000):
+        self.hw.connect()
+        self.imu.start(timeout_ms=imu_timeout_ms)
+        if self.imu.initial_gravity is not None:
+            self.imu_filter.reset_with_accel(self.imu.initial_gravity)
+            self.quat_wxyz = self.imu_filter.q.copy()
+
+    def disconnect(self):
+        try:
+            self.hw.disable_all()
+        finally:
+            self.imu.stop()
+            self.hw.disconnect()
+
+    def enable_motors(self):
+        self.hw.enable_all()
+
+    def disable_motors(self):
+        self.hw.disable_all()
+
+    def damping_brake(self):
+        self.hw.damping_brake(self.kd_leg, self.kd_wheel)
+
+    def wait_feedback_ready(self, max_attempts: int = 20, poll_interval: float = 0.05):
+        return self.hw.wait_feedback_ready(max_attempts=max_attempts, poll_interval=poll_interval)
+
+    def read_measured_pose(self) -> np.ndarray:
+        return self.hw.read_measured_pose()
+
+    def read_state(self) -> Dict[str, object]:
+        joint_pos, joint_vel, joint_torque, motor_diag = self.hw.read_state()
+        gyro, accel, age_ms, fresh = self.imu.get_latest()
+        self._last_imu_age_ms = age_ms
+        self._last_imu_fresh = fresh
+        self.quat_wxyz = self.imu_filter.update(accel, gyro)
+        projected_gravity = get_gravity_orientation(self.quat_wxyz)
+
+        return {
+            "joint_pos": joint_pos,
+            "joint_vel": joint_vel,
+            "joint_torque": joint_torque,
+            "imu_gyro": gyro,
+            "imu_accel": accel,
+            "quat_wxyz": self.quat_wxyz.copy(),
+            "projected_gravity": projected_gravity,
+            "imu_age_ms": age_ms,
+            "imu_fresh": fresh,
+            "motor_stale": motor_diag,
+        }
+
+    def get_obs_policy(
+        self,
+        state: Dict[str, object],
+        command: np.ndarray,
+        default_dof_pos: np.ndarray,
+        last_actions_raw: np.ndarray,
+    ) -> np.ndarray:
+        gyro = state["imu_gyro"]
+        joint_pos = state["joint_pos"]
+        joint_vel = state["joint_vel"]
+        projected_gravity = state["projected_gravity"]
+
+        base_ang_vel = (gyro * 0.25).astype(np.float32)
+        joint_pos_rel = (joint_pos[:12] - default_dof_pos[:12]).astype(np.float32)
+        joint_vel_leg = (joint_vel[:12] * 0.05).astype(np.float32)
+        wheel_vel = (joint_vel[12:] * 0.05).astype(np.float32)
+
+        return np.concatenate(
+            [
+                base_ang_vel,
+                projected_gravity,
+                command.astype(np.float32),
+                joint_pos_rel,
+                joint_vel_leg,
+                wheel_vel,
+                last_actions_raw,
+            ]
+        ).astype(np.float32)
+
+    def send_actions(self, scaled_actions: np.ndarray, default_dof_pos: np.ndarray):
+        act = (scaled_actions + default_dof_pos).astype(np.float32)
+        act = np.clip(act, -100.0, 100.0)
+        act[:12] = self.lpf_legs.filter(act[:12])
+        act[12:] = self.lpf_wheels.filter(act[12:])
+        self.hw.send_control(act, self.kp_leg, self.kd_leg, self.kd_wheel)
+        return act
+
+    def hold_pose(self, sim_target_pose: np.ndarray, kp_scale: float = 1.0):
+        target = np.clip(sim_target_pose.astype(np.float32), -100.0, 100.0)
+        kp_scale = float(np.clip(kp_scale, 0.0, 1.0))
+        self.hw.send_control(target, self.kp_leg * kp_scale, self.kd_leg, self.kd_wheel)
+        return target