feat(pybot×actpred): R2 姿态反馈方案一——MPU6050 独立 IMU token 全链路

- pybot:recorder 逐帧落盘 imu.npy(T×8,roll,pitch,ax,ay,az,gx,gy,gz,与帧/动作同调用对齐);run_loop 对声明 imu_dim 的 predictor 以 predict(..., imu=) 调用(鸭子类型,旧两参调用向后兼容)

- actpred:新增 --imu-dim;model 序列 [img×F, act×H, (IMU), PRED](imu_dim>0 时 F+H+2,IMU token 位于 PRED 前);dataset/train 读 imu.npy(缺失按零向量兜底);predict/ONNX/Hailo 三后端与 export/gen_calibration/dfc_compile/_npu_test 部署链适配 imu 输入

- 姿态按物理量程固定缩放归一化(imu_norm.py,训练/推理共用,零状态)

- 测试:actpred 128 passed / pybot loop+recorder 28 passed
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qing committed 2026-08-14 09:07:24 +08:00
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@@ -58,9 +58,19 @@ name alias;
A angle;
@
@I2C
name path;
i2c-1 /dev/i2c-1;
@
@PCA9685
name I2C address;
pca9685-0 i2c-1 0x40;
@
@Servo
name max min offset controller channel;
s1 90 - - - 0;
s1 90 - - pca9685-0 0;
@
@Action
@@ -281,3 +291,98 @@ def test_loop_empty_queue_falls_back_synthetic(mock_i2c):
# dry_run 合成帧是 numpy 数组(HWC uint8),非 int
assert all(isinstance(f, np.ndarray) for f in frames)
assert frames[0].shape == (240, 320, 3) # LOOP_MT @Camera 320x240
# ---------------- IMU 姿态回流(R2 方案一:独立 IMU token) ----------------
# 在 LOOP_MT 基础上加 @MPU6050_BIND(i2c-1 已定义,相机块之前插入)
LOOP_IMU_MT = LOOP_MT.replace(
"@Camera",
"""@MPU6050_BIND
name I2C addr;
mpu6050-0 i2c-1 0x69;
@
@Camera""")
class ImuPredictor(MockPredictor):
"""声明 imu_dim 的推理器桩:闭环应以 imu= 关键字调用"""
def __init__(self, *args, imu_dim=8, **kwargs):
super().__init__(*args, **kwargs)
self.imu_dim = imu_dim
self.imus = [] # 每步收到的 imu 向量
def predict(self, images, action_history, imu=None):
self.imus.append(None if imu is None else np.asarray(imu).copy())
return super().predict(images, action_history)
def _freeze_imu(robot, name="mpu6050-0", **vals):
"""停掉采样线程并注入固定姿态(避免 10ms 采样覆盖测试值)"""
sensor = robot.M[name].sensor
sensor.stop_daemon()
sensor.wait_daemon()
sensor._latest.update(**vals)
def test_loop_imu_passed_to_predictor(mock_i2c):
"""predictor 声明 imu_dim + 脚本含 @MPU6050_BIND → 每步 imu= 向量"""
robot = _make_robot(LOOP_IMU_MT, mock_i2c)
robot.active()
_freeze_imu(robot, roll=1.5, pitch=-2.0, gz=30.0)
pred = ImuPredictor(frame_len=3, history_len=2, action_dim=4)
robot.run_loop(pred, hz=1000.0, max_steps=3)
robot.deactive()
assert len(pred.imus) == 3
for imu in pred.imus:
assert imu is not None and imu.shape == (8,)
# IMU_KEYS 顺序:roll pitch ax ay az gx gy gz
assert imu[0] == 1.5 and imu[1] == -2.0 and imu[7] == 30.0
def test_loop_imu_zero_without_bind(mock_i2c):
"""predictor 声明 imu_dim 但脚本无 @MPU6050_BIND → imu 零向量输入"""
robot = _make_robot(LOOP_MT, mock_i2c)
robot.active()
pred = ImuPredictor(frame_len=3, history_len=2, action_dim=4)
robot.run_loop(pred, hz=1000.0, max_steps=2)
robot.deactive()
assert len(pred.imus) == 2
for imu in pred.imus:
assert imu is not None and imu.shape == (8,)
assert np.allclose(imu, 0.0)
def test_loop_imu_not_passed_to_legacy_predictor(mock_i2c):
"""未声明 imu_dim 的旧推理器:保持两参调用(向后兼容)"""
robot = _make_robot(LOOP_IMU_MT, mock_i2c)
robot.active()
_freeze_imu(robot, roll=9.0)
pred = MockPredictor(frame_len=3, history_len=2, action_dim=4)
robot.run_loop(pred, hz=1000.0, max_steps=2) # 不炸即兼容
robot.deactive()
assert len(pred.calls) == 2
def test_loop_imu_recorded(mock_i2c, tmp_path):
"""闭环录制:含 IMU 时 imu.npy 与 actions.npy 帧对齐(T 一致)"""
from pybot.recorder import EpisodeRecorder
robot = _make_robot(LOOP_IMU_MT, mock_i2c)
robot.active()
_freeze_imu(robot, roll=3.0, ay=0.5)
rec = EpisodeRecorder(str(tmp_path), action_dim=18)
pred = MockPredictor(frame_len=3, history_len=2, action_dim=4)
robot.run_loop(pred, hz=1000.0, max_steps=4, recorder=rec)
robot.deactive()
ep = tmp_path / "episode_0000"
actions = np.load(ep / "actions.npy")
imus = np.load(ep / "imu.npy")
assert actions.shape == (4, 18)
assert imus.shape == (4, 8) # 与 actions 帧数对齐
assert np.allclose(imus[:, 0], 3.0) # roll
assert np.allclose(imus[:, 3], 0.5) # ay
+89
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@@ -285,6 +285,95 @@ def test_delay_not_multiple_of_10(tmp_path, mock_i2c):
robot.deactive()
# ---------------- IMU 姿态录制(R2) ----------------
# @Camera + @MPU6050_BIND + 2 行 @Action —— 脚本驱动录制姿态
IMU_MT = """
@I2C
name path;
i2c-1 /dev/i2c-1;
@
@MPU6050_BIND
name I2C addr;
mpu6050-0 i2c-1 0x69;
@
@Camera
name width height framerate capacity;
cam0 320 240 15 2;
@
@Action
cam0.frame;
0;
0;
@
"""
def test_imu_npy_written_with_dict(tmp_path):
"""record 传姿态 dict → flush 产出 imu.npy(T×8),键序 roll..gz"""
rec = EpisodeRecorder(str(tmp_path), action_dim=18)
imu = {"roll": 1.0, "pitch": 2.0, "ax": 3.0, "ay": 4.0,
"az": 5.0, "gx": 6.0, "gy": 7.0, "gz": 8.0}
rec.record(None, [0.0], imu_vec=imu)
rec.record(None, [0.0], imu_vec=imu)
rec.flush()
imus = np.load(tmp_path / "episode_0000" / "imu.npy")
assert imus.shape == (2, 8)
assert list(imus[0]) == [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0]
def test_imu_mixed_none_marks_zero(tmp_path):
"""混合数据集:部分帧无姿态 → 该帧记零向量,仍产出 imu.npy"""
rec = EpisodeRecorder(str(tmp_path), action_dim=18)
rec.record(None, [0.0], imu_vec=None)
rec.record(None, [0.0], imu_vec={"roll": 9.0})
rec.flush()
imus = np.load(tmp_path / "episode_0000" / "imu.npy")
assert imus.shape == (2, 8)
assert np.allclose(imus[0], 0.0)
assert imus[1, 0] == 9.0
def test_no_imu_no_file(tmp_path):
"""全程无姿态(旧数据路径)→ 不产出 imu.npy,保持旧格式兼容"""
robot = RobotStruct(CAMERA_MT, dry_run=True)
robot.active()
rec = EpisodeRecorder(str(tmp_path), action_dim=18)
robot.run(recorder=rec)
robot.deactive()
ep_dir = tmp_path / "episode_0000"
assert (ep_dir / "actions.npy").exists()
assert not (ep_dir / "imu.npy").exists()
def test_run_with_imu_block(tmp_path, mock_i2c):
"""脚本含 @MPU6050_BIND 时 run() 录制产出 imu.npy 且与 actions 帧对齐"""
robot = RobotStruct(IMU_MT, dry_run=True)
robot.active()
# 停采样线程注入固定姿态,避免 mock 采样值干扰断言
sensor = robot.M["mpu6050-0"].sensor
sensor.stop_daemon()
sensor.wait_daemon()
sensor._latest.update(roll=-4.0, gz=12.0)
rec = EpisodeRecorder(str(tmp_path), action_dim=18)
robot.run(recorder=rec)
robot.deactive()
ep_dir = tmp_path / "episode_0000"
actions = np.load(ep_dir / "actions.npy")
imus = np.load(ep_dir / "imu.npy")
assert actions.shape == (2, 18) # 2 行 @Action,无 Speaker 不分解
assert imus.shape == (2, 8)
assert np.allclose(imus[:, 0], -4.0)
assert np.allclose(imus[:, 7], 12.0)
def test_actpred_compatibility(tmp_path, mock_i2c):
"""用 actpred 的 ActionDataset 加载录制的 episode"""
pytest.importorskip("torch")