paramsd: use livePose (#33099)

* Use livePose instead  of llk

* Update process replay sockets

* Fix import

* Fix calib

* Fix field name

* Dont store device_from_calib

* Update ref commit

selfdrive/locationd/helpers.py

@@ -4,6 +4,14 @@ from typing import Any
 from cereal import log
 
 
+def rotate_cov(rot_matrix, cov_in):
+  return rot_matrix @ cov_in @ rot_matrix.T
+
+
+def rotate_std(rot_matrix, std_in):
+  return np.sqrt(np.diag(rotate_cov(rot_matrix, np.diag(std_in**2))))
+
+
 class NPQueue:
   def __init__(self, maxlen: int, rowsize: int) -> None:
     self.maxlen = maxlen

selfdrive/locationd/paramsd.py

@@ -9,8 +9,10 @@ from cereal import car, log
 from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, DT_MDL
 from openpilot.common.numpy_fast import clip
+from openpilot.common.transformations.orientation import rot_from_euler
 from openpilot.selfdrive.locationd.models.car_kf import CarKalman, ObservationKind, States
 from openpilot.selfdrive.locationd.models.constants import GENERATED_DIR
+from openpilot.selfdrive.locationd.helpers import rotate_std
 from openpilot.common.swaglog import cloudlog
 
 
@@ -38,6 +40,9 @@ class ParamsLearner:
     self.kf.filter.set_global("stiffness_rear", CP.tireStiffnessRear)
 
     self.active = False
+    self.calibrated = False
+
+    self.calib_from_device = np.eye(3)
 
     self.speed = 0.0
     self.yaw_rate = 0.0
@@ -47,12 +52,16 @@ class ParamsLearner:
     self.roll_valid = False
 
   def handle_log(self, t, which, msg):
-    if which == 'liveLocationKalman':
+    if which == 'livePose':
-      self.yaw_rate = msg.angularVelocityCalibrated.value[2]
+      angular_velocity_device = np.array([msg.angularVelocityDevice.x, msg.angularVelocityDevice.y, msg.angularVelocityDevice.z])
-      self.yaw_rate_std = msg.angularVelocityCalibrated.std[2]
+      angular_velocity_device_std = np.array([msg.angularVelocityDevice.xStd, msg.angularVelocityDevice.yStd, msg.angularVelocityDevice.zStd])
+      angular_velocity_calibrated = np.matmul(self.calib_from_device, angular_velocity_device)
+      angular_velocity_calibrated_std = rotate_std(self.calib_from_device, angular_velocity_device_std)
+
+      self.yaw_rate, self.yaw_rate_std = angular_velocity_calibrated[2], angular_velocity_calibrated_std[2]
 
-      localizer_roll = msg.orientationNED.value[0]
+      localizer_roll = msg.orientationNED.x
-      localizer_roll_std = np.radians(1) if np.isnan(msg.orientationNED.std[0]) else msg.orientationNED.std[0]
+      localizer_roll_std = np.radians(1) if np.isnan(msg.orientationNED.xStd) else msg.orientationNED.xStd
       self.roll_valid = (localizer_roll_std < ROLL_STD_MAX) and (ROLL_MIN < localizer_roll < ROLL_MAX) and msg.sensorsOK
       if self.roll_valid:
         roll = localizer_roll
@@ -64,7 +73,7 @@ class ParamsLearner:
         roll_std = np.radians(10.0)
       self.roll = clip(roll, self.roll - ROLL_MAX_DELTA, self.roll + ROLL_MAX_DELTA)
 
-      yaw_rate_valid = msg.angularVelocityCalibrated.valid
+      yaw_rate_valid = msg.angularVelocityDevice.valid and self.calibrated
       yaw_rate_valid = yaw_rate_valid and 0 < self.yaw_rate_std < 10  # rad/s
       yaw_rate_valid = yaw_rate_valid and abs(self.yaw_rate) < 1  # rad/s
 
@@ -91,6 +100,11 @@ class ParamsLearner:
         self.kf.predict_and_observe(t, ObservationKind.STIFFNESS, np.array([[stiffness]]))
         self.kf.predict_and_observe(t, ObservationKind.STEER_RATIO, np.array([[steer_ratio]]))
 
+    elif which == 'liveCalibration':
+      self.calibrated  = msg.calStatus == log.LiveCalibrationData.Status.calibrated
+      device_from_calib = rot_from_euler(np.array(msg.rpyCalib))
+      self.calib_from_device = device_from_calib.T
+
     elif which == 'carState':
       self.steering_angle = msg.steeringAngleDeg
       self.speed = msg.vEgo
@@ -123,7 +137,7 @@ def main():
   REPLAY = bool(int(os.getenv("REPLAY", "0")))
 
   pm = messaging.PubMaster(['liveParameters'])
-  sm = messaging.SubMaster(['liveLocationKalman', 'carState'], poll='liveLocationKalman')
+  sm = messaging.SubMaster(['livePose', 'liveCalibration', 'carState'], poll='livePose')
 
   params_reader = Params()
   # wait for stats about the car to come in from controls
@@ -188,7 +202,7 @@ def main():
           t = sm.logMonoTime[which] * 1e-9
           learner.handle_log(t, which, sm[which])
 
-    if sm.updated['liveLocationKalman']:
+    if sm.updated['livePose']:
       x = learner.kf.x
       P = np.sqrt(learner.kf.P.diagonal())
       if not all(map(math.isfinite, x)):

selfdrive/test/process_replay/process_replay.py

@@ -539,11 +539,11 @@ CONFIGS = [
   ),
   ProcessConfig(
     proc_name="paramsd",
-    pubs=["liveLocationKalman", "carState"],
+    pubs=["livePose", "liveCalibration", "carState"],
     subs=["liveParameters"],
     ignore=["logMonoTime"],
     init_callback=get_car_params_callback,
-    should_recv_callback=FrequencyBasedRcvCallback("liveLocationKalman"),
+    should_recv_callback=FrequencyBasedRcvCallback("livePose"),
     tolerance=NUMPY_TOLERANCE,
     processing_time=0.004,
   ),

selfdrive/test/process_replay/ref_commit

@@ -1 +1 @@
-949909bd80599698c1307b3304010456dded6a15
+3e8feca20cd64f6a05dcbbdc0ace04a8c12bf86d