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