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get ready for live localizer

pull/1074/head
Harald Schafer 2020-02-10 15:28:20 -08:00
parent 4f05efb6bc
commit dcb14dd830
2 changed files with 42 additions and 90 deletions
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29
selfdrive/locationd/kalman/live_kf.py
View File

@ -6,20 +6,18 @@ from .kalman_helpers import ObservationKind
from .ekf_sym import EKF_sym
initial_x = np.array([-2.7e6, 4.2e6, 3.8e6,
1, 0, 0, 0,
0, 0, 0,
0, 0, 0,
0, 0, 0,
1,
0, 0, 0,
0, 0, 0])
class LiveKalman():
def __init__(self, N=0, max_tracks=3000):
x_initial = np.array([-2.7e6, 4.2e6, 3.8e6,
1, 0, 0, 0,
0, 0, 0,
0, 0, 0,
0, 0, 0,
1,
0, 0, 0,
0, 0, 0])
# state covariance
P_initial = np.diag([10000**2, 10000**2, 10000**2,
# state covariance
initial_P_diag = np.array([10000**2, 10000**2, 10000**2,
10**2, 10**2, 10**2,
10**2, 10**2, 10**2,
1**2, 1**2, 1**2,
@ -28,6 +26,11 @@ class LiveKalman():
1**2, 1**2, 1**2,
(0.01)**2, (0.01)**2, (0.01)**2])
class LiveKalman():
def __init__(self, N=0, max_tracks=3000):
# process noise
Q = np.diag([0.03**2, 0.03**2, 0.03**2,
0.0**2, 0.0**2, 0.0**2,
@ -52,7 +55,7 @@ class LiveKalman():
gen_model(name, self.dim_state, self.dim_state_err)
# init filter
self.filter = EKF_sym(name, Q, x_initial, P_initial, self.dim_state, self.dim_state_err)
self.filter = EKF_sym(name, Q, initial_x, np.diag(initial_P_diag), self.dim_state, self.dim_state_err)
@property
def x(self):

103
selfdrive/locationd/locationd.py
View File

@ -5,26 +5,18 @@ import numpy as np
from bisect import bisect_right
import cereal.messaging as messaging
from selfdrive.swaglog import cloudlog
from cereal.services import service_list
from common.transformations.orientation import rotations_from_quats, ecef_euler_from_ned, euler2quat, ned_euler_from_ecef, quat2euler
import common.transformations.coordinates as coord
import laika.raw_gnss as gnss
from laika.astro_dog import AstroDog
from selfdrive.locationd.kalman.loc_kf import LocKalman
from selfdrive.locationd.kalman.live_kf import LiveKalman, States, inital_x, initial_P_diag
from selfdrive.locationd.kalman.kalman_helpers import ObservationKind
os.environ["OMP_NUM_THREADS"] = "1"
class Localizer():
def __init__(self, disabled_logs=[], dog=None):
self.kf = LocKalman(0)
self.kf = LiveKalman()
self.reset_kalman()
if dog:
self.dog = dog
else:
self.dog = AstroDog(auto_update=True)
self.max_age = .2 # seconds
self.disabled_logs = disabled_logs
self.week = None
@ -32,32 +24,31 @@ class Localizer():
def liveLocationMsg(self, time):
fix = messaging.log.LiveLocationData.new_message()
predicted_state = self.kf.x
fix_ecef = predicted_state[0:3]
fix_ecef = predicted_state[States.ECEF_POS]
fix_pos_geo = coord.ecef2geodetic(fix_ecef)
fix.lat = float(fix_pos_geo[0])
fix.lon = float(fix_pos_geo[1])
fix.alt = float(fix_pos_geo[2])
fix.speed = float(np.linalg.norm(predicted_state[7:10]))
fix.speed = float(np.linalg.norm(predicted_state[States.ECEF_VELOCITY]))
orientation_ned_euler = ned_euler_from_ecef(fix_ecef, quat2euler(predicted_state[3:7]))
orientation_ned_euler = ned_euler_from_ecef(fix_ecef, quat2euler(predicted_state[States.ECEF_ORIENTATION]))
fix.roll = float(orientation_ned_euler[0]*180/np.pi)
fix.pitch = float(orientation_ned_euler[1]*180/np.pi)
fix.heading = float(orientation_ned_euler[2]*180/np.pi)
fix.gyro = [float(predicted_state[10]), float(predicted_state[11]), float(predicted_state[12])]
fix.accel = [float(predicted_state[19]), float(predicted_state[20]), float(predicted_state[21])]
local_vel = rotations_from_quats(predicted_state[3:7]).T.dot(predicted_state[7:10])
local_vel = rotations_from_quats(predicted_state[States.ECEF_ORIENTATION]).T.dot(predicted_state[States.ECEF_VELOCITY])
fix.pitchCalibration = float((np.arctan2(local_vel[2], local_vel[0]))*180/np.pi)
fix.yawCalibration = float((np.arctan2(local_vel[1], local_vel[0]))*180/np.pi)
fix.imuFrame = [(180/np.pi)*float(predicted_state[23]), (180/np.pi)*float(predicted_state[24]), (180/np.pi)*float(predicted_state[25])]
#fix.imuFrame = [(180/np.pi)*float(predicted_state[23]), (180/np.pi)*float(predicted_state[24]), (180/np.pi)*float(predicted_state[25])]
return fix
def update_kalman(self, time, kind, meas):
idx = bisect_right([x[0] for x in self.observation_buffer], time)
self.observation_buffer.insert(idx, (time, kind, meas))
#print len(self.observation_buffer), idx, self.kf.filter.filter_time, time
while self.observation_buffer[-1][0] - self.observation_buffer[0][0] > self.max_age:
if self.filter_ready:
self.kf.predict_and_observe(*self.observation_buffer.pop(0))
@ -67,38 +58,31 @@ class Localizer():
def handle_gps(self, log, current_time):
self.converter = coord.LocalCoord.from_geodetic([log.gpsLocationExternal.latitude, log.gpsLocationExternal.longitude, log.gpsLocationExternal.altitude])
fix_ecef = self.converter.ned2ecef([0,0,0])
# initing with bad bearing allowed, maybe bad?
if not self.filter_ready and len(list(self.dog.orbits.keys())) >6: # and log.gpsLocationExternal.speed > 5:
# TODO initing with bad bearing not allowed, maybe not bad?
if not self.filter_ready and log.gpsLocationExternal.speed > 5:
self.filter_ready = True
initial_ecef = fix_ecef
initial_state = np.zeros(29)
gps_bearing = log.gpsLocationExternal.bearing*(np.pi/180)
initial_pose_ecef = ecef_euler_from_ned(initial_ecef, [0, 0, gps_bearing])
initial_pose_ecef_quat = euler2quat(initial_pose_ecef)
gps_speed = log.gpsLocationExternal.speed
quat_uncertainty = 0.2**2
initial_pose_ecef_quat = euler2quat(initial_pose_ecef)
initial_state[:3] = initial_ecef
initial_state[3:7] = initial_pose_ecef_quat
initial_state[7:10] = rotations_from_quats(initial_pose_ecef_quat).dot(np.array([gps_speed, 0, 0]))
initial_state[18] = 1
initial_state[22] = 1
covs_diag = np.array([10**2,10**2,10**2,
quat_uncertainty, quat_uncertainty, quat_uncertainty,
2**2, 2**2, 2**2,
1, 1, 1,
20000000**2, 100**2,
0.01**2, 0.01**2, 0.01**2,
0.02**2,
2**2, 2**2, 2**2,
.01**2,
0.01**2, 0.01**2, 0.01**2,
10**2, 1**2,
0.2**2])
self.kf.init_state(initial_state, covs=np.diag(covs_diag), filter_time=current_time)
initial_state = inital_x
initial_covs_diag = initial_P_diag
initial_state[States.ECEF_POS] = initial_ecef
initial_state[States.ECEF_ORIENTATION] = initial_pose_ecef_quat
initial_state[States.ECEF_VELOCITY] = rotations_from_quats(initial_pose_ecef_quat).dot(np.array([gps_speed, 0, 0]))
initial_covs_diag[States.ECEF_POS_ERR] = 10**2
initial_covs_diag[States.ECEF_ORIENTATION_ERR] = quat_uncertainty
initial_covs_diag[States.ECEF_VELOCITY_ERR] = 1**2
self.kf.init_state(initial_state, covs=np.diag(initial_covs_diag), filter_time=current_time)
print("Filter initialized")
elif self.filter_ready:
#self.update_kalman(current_time, ObservationKind.ECEF_POS, fix_ecef)
self.update_kalman(current_time, ObservationKind.ECEF_POS, fix_ecef)
gps_est_error = np.sqrt((self.kf.x[0] - fix_ecef[0])**2 +
(self.kf.x[1] - fix_ecef[1])**2 +
(self.kf.x[2] - fix_ecef[2])**2)
@ -113,34 +97,11 @@ class Localizer():
if log.carState.vEgo == 0:
self.update_kalman(current_time, ObservationKind.NO_ROT, [0, 0, 0])
def handle_ublox_gnss(self, log, current_time):
if hasattr(log.ubloxGnss, 'measurementReport'):
self.raw_gnss_counter += 1
if True or self.raw_gnss_counter % 3==0:
processed_raw = gnss.process_measurements(gnss.read_raw_ublox(log.ubloxGnss.measurementReport), dog=self.dog)
corrected_raw = gnss.correct_measurements(processed_raw, self.kf.x[:3], dog=self.dog)
corrected_raw = np.array([c.as_array() for c in corrected_raw]).reshape((-1,14))
self.update_kalman(current_time, ObservationKind.PSEUDORANGE_GPS, corrected_raw)
self.update_kalman(current_time, ObservationKind.PSEUDORANGE_RATE_GPS, corrected_raw)
#elif hasattr(log.ubloxGnss, 'ephemeris'):
# self.dog.add_ublox_ephems([log])
# if len(self.dog.orbits.keys()) < 6:
# print 'Added ublox ephem now has ', len(self.dog.orbits.keys())
def handle_qcom_gnss(self, log, current_time):
if hasattr(log.qcomGnss, 'drSvPoly') and self.week is not None:
self.dog.add_qcom_ephems([log], self.week)
if len(list(self.dog.orbits.keys())) < 6:
print('Added qcom ephem now has ', len(list(self.dog.orbits.keys())))
if hasattr(log.qcomGnss, 'drMeasurementReport') and log.qcomGnss.drMeasurementReport.source == "gps":
self.week = log.qcomGnss.drMeasurementReport.gpsWeek
def handle_cam_odo(self, log, current_time):
self.update_kalman(current_time, ObservationKind.CAMERA_ODO_ROTATION, np.concatenate([log.cameraOdometry.rot,
log.cameraOdometry.rotStd]))
self.update_kalman(current_time, ObservationKind.CAMERA_ODO_TRANSLATION, np.concatenate([log.cameraOdometry.trans,
log.cameraOdometry.transStd]))
pass
def handle_sensors(self, log, current_time):
for sensor_reading in log.sensorEvents:
@ -148,7 +109,7 @@ class Localizer():
if sensor_reading.type == 4:
self.gyro_counter += 1
if True or self.gyro_counter % 5==0:
if max(abs(self.kf.x[23:26])) > 0.07:
if max(abs(self.kf.x[States.IMU_OFFSET])) > 0.07:
print('imu frame angles exceeded, correcting')
self.update_kalman(current_time, ObservationKind.IMU_FRAME, [0, 0, 0])
self.update_kalman(current_time, ObservationKind.PHONE_GYRO, [-sensor_reading.gyro.v[2], -sensor_reading.gyro.v[1], -sensor_reading.gyro.v[0]])
@ -168,10 +129,6 @@ class Localizer():
self.handle_gps(log, current_time)
elif typ == "carState":
self.handle_car_state(log, current_time)
elif typ == "ubloxGnss":
self.handle_ublox_gnss(log, current_time)
elif typ == "qcomGnss":
self.handle_qcom_gnss(log, current_time)
elif typ == "cameraOdometry":
self.handle_cam_odo(log, current_time)
@ -182,18 +139,16 @@ class Localizer():
self.converter = None
self.gyro_counter = 0
self.acc_counter = 0
self.raw_gnss_counter = 0
self.speed_counter = 0
def locationd_thread(gctx, addr, disabled_logs):
def locationd_thread(gctx, addr, disabled_logs=[]):
poller = zmq.Poller()
#carstate = messaging.sub_sock('carState', poller, addr=addr, conflate=True)
gpsLocationExternal = messaging.sub_sock('gpsLocationExternal', poller, addr=addr, conflate=True)
ubloxGnss = messaging.sub_sock('ubloxGnss', poller, addr=addr, conflate=True)
qcomGnss = messaging.sub_sock('qcomGnss', poller, addr=addr, conflate=True)
sensorEvents = messaging.sub_sock('sensorEvents', poller, addr=addr, conflate=True)
cameraOdometry = messaging.sub_sock('cameraOdometry', poller, addr=addr, conflate=True)
liveLocation = messaging.pub_sock('liveLocation')
@ -219,13 +174,7 @@ def locationd_thread(gctx, addr, disabled_logs):
def main(gctx=None, addr="127.0.0.1"):
IN_CAR = os.getenv("IN_CAR", False)
disabled_logs = os.getenv("DISABLED_LOGS", "").split(",")
# No speed for now
disabled_logs.append('carState')
if IN_CAR:
addr = "192.168.5.11"
locationd_thread(gctx, addr, disabled_logs)
locationd_thread(gctx, addr)
if __name__ == "__main__":