Add gnss kalman filter to laikad (#24578)
* Add gnss kalman filter to laikad
* Fix analysis
* Fix analysis
* Update laika
* Refactor a bit
* cleanup, improve unit test
* Also commit test
* fix
* Always return messages. Use Measurement struct that contains std and valid keys
* Push cereal
* Change prints to cloudlog
* Always send valid messages
* Only send gnssMeasurement msg when measurementReport type
old-commit-hash: ef97329c0e
taco
parent
109916df80
commit
e72a8d9330
4 changed files with 158 additions and 49 deletions
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Subproject commit b43ac3de527ad4f885af544cd0e9e9d4a9b1a6c2 |
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Subproject commit be1a213a5ffa3cafe2b4f2d53f6df5d2452ad910 |
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Subproject commit f5f76d28b4827c3fb706d542729651ceef6c06bd |
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#!/usr/bin/env python3 |
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from typing import List |
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import numpy as np |
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from collections import defaultdict |
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from cereal import log, messaging |
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from laika import AstroDog |
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from laika.helpers import ConstellationId |
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from laika.raw_gnss import GNSSMeasurement, calc_pos_fix, correct_measurements, process_measurements, read_raw_ublox |
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from selfdrive.locationd.models.constants import GENERATED_DIR, ObservationKind |
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from selfdrive.locationd.models.gnss_kf import GNSSKalman |
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from selfdrive.locationd.models.gnss_kf import States as GStates |
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import common.transformations.coordinates as coord |
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from selfdrive.swaglog import cloudlog |
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MAX_TIME_GAP = 10 |
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def correct_and_pos_fix(processed_measurements: List[GNSSMeasurement], dog: AstroDog): |
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# pos fix needs more than 5 processed_measurements |
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pos_fix = calc_pos_fix(processed_measurements) |
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if len(pos_fix) == 0: |
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return [], [] |
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est_pos = pos_fix[0][:3] |
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corrected = correct_measurements(processed_measurements, est_pos, dog) |
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return calc_pos_fix(corrected), corrected |
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class Laikad: |
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def __init__(self): |
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self.gnss_kf = GNSSKalman(GENERATED_DIR) |
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def process_ublox_msg(ublox_msg, dog, ublox_mono_time: int): |
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def process_ublox_msg(self, ublox_msg, dog: AstroDog, ublox_mono_time: int): |
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if ublox_msg.which == 'measurementReport': |
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report = ublox_msg.measurementReport |
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if len(report.measurements) == 0: |
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return None |
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new_meas = read_raw_ublox(report) |
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processed_measurements = process_measurements(new_meas, dog) |
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measurements = process_measurements(new_meas, dog) |
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corrected = correct_and_pos_fix(processed_measurements, dog) |
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pos_fix, _ = corrected |
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# todo send corrected messages instead of processed_measurements. Need fix for when having less than 6 measurements |
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correct_meas_msgs = [create_measurement_msg(m) for m in processed_measurements] |
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# pos fix can be an empty list if not enough correct measurements are available |
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pos_fix = calc_pos_fix(measurements) |
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# To get a position fix a minimum of 5 measurements are needed. |
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# Each report can contain less and some measurement can't be processed. |
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if len(pos_fix) > 0: |
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corrected_pos = pos_fix[0][:3].tolist() |
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else: |
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corrected_pos = [0., 0., 0.] |
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dat = messaging.new_message('gnssMeasurements') |
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measurements = correct_measurements(measurements, pos_fix[0][:3], dog) |
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meas_msgs = [create_measurement_msg(m) for m in measurements] |
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t = ublox_mono_time * 1e-9 |
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self.update_localizer(pos_fix, t, measurements) |
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localizer_valid = self.localizer_valid(t) |
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ecef_pos = self.gnss_kf.x[GStates.ECEF_POS].tolist() |
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ecef_vel = self.gnss_kf.x[GStates.ECEF_VELOCITY].tolist() |
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pos_std = float(np.linalg.norm(self.gnss_kf.P[GStates.ECEF_POS])) |
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vel_std = float(np.linalg.norm(self.gnss_kf.P[GStates.ECEF_VELOCITY])) |
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bearing_deg, bearing_std = get_bearing_from_gnss(ecef_pos, ecef_vel, vel_std) |
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dat = messaging.new_message("gnssMeasurements") |
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measurement_msg = log.GnssMeasurements.Measurement.new_message |
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dat.gnssMeasurements = { |
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"position": corrected_pos, |
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"positionECEF": measurement_msg(value=ecef_pos, std=pos_std, valid=localizer_valid), |
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"velocityECEF": measurement_msg(value=ecef_vel, std=vel_std, valid=localizer_valid), |
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"bearingDeg": measurement_msg(value=[bearing_deg], std=bearing_std, valid=localizer_valid), |
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"ubloxMonoTime": ublox_mono_time, |
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"correctedMeasurements": correct_meas_msgs |
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"correctedMeasurements": meas_msgs |
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} |
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return dat |
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def update_localizer(self, pos_fix, t: float, measurements: List[GNSSMeasurement]): |
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# Check time and outputs are valid |
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if not self.localizer_valid(t): |
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# A position fix is needed when resetting the kalman filter. |
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if len(pos_fix) == 0: |
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return |
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post_est = pos_fix[0][:3].tolist() |
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if self.gnss_kf.filter.filter_time is None: |
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cloudlog.info("Init gnss kalman filter") |
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elif (self.gnss_kf.filter.filter_time - t) > MAX_TIME_GAP: |
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cloudlog.error("Time gap of over 10s detected, gnss kalman reset") |
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else: |
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cloudlog.error("Gnss kalman filter state is nan") |
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self.init_gnss_localizer(post_est) |
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if len(measurements) > 0: |
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kf_add_observations(self.gnss_kf, t, measurements) |
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else: |
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# Ensure gnss filter is updated even with no new measurements |
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self.gnss_kf.predict(t) |
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def localizer_valid(self, t: float): |
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filter_time = self.gnss_kf.filter.filter_time |
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return filter_time is not None and (filter_time - t) < MAX_TIME_GAP and \ |
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all(np.isfinite(self.gnss_kf.x[GStates.ECEF_POS])) |
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def init_gnss_localizer(self, est_pos): |
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x_initial, p_initial_diag = np.copy(GNSSKalman.x_initial), np.copy(np.diagonal(GNSSKalman.P_initial)) |
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x_initial[GStates.ECEF_POS] = est_pos |
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p_initial_diag[GStates.ECEF_POS] = 1000 ** 2 |
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self.gnss_kf.init_state(x_initial, covs_diag=p_initial_diag) |
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def create_measurement_msg(meas: GNSSMeasurement): |
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c = log.GnssMeasurements.CorrectedMeasurement.new_message() |
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c.constellationId = meas.constellation_id.value |
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c.svId = int(meas.prn[1:]) |
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c.svId = meas.sv_id |
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observables = meas.observables_final |
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c.glonassFrequency = meas.glonass_freq if meas.constellation_id == ConstellationId.GLONASS else 0 |
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c.pseudorange = float(meas.observables['C1C']) # todo should be observables_final when using corrected measurements |
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c.pseudorange = float(observables['C1C']) |
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c.pseudorangeStd = float(meas.observables_std['C1C']) |
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c.pseudorangeRate = float(meas.observables['D1C']) # todo should be observables_final when using corrected measurements |
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c.pseudorangeRate = float(observables['D1C']) |
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c.pseudorangeRateStd = float(meas.observables_std['D1C']) |
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c.satPos = meas.sat_pos_final.tolist() |
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c.satVel = meas.sat_vel.tolist() |
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return c |
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def kf_add_observations(gnss_kf: GNSSKalman, t: float, measurements: List[GNSSMeasurement]): |
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ekf_data = defaultdict(list) |
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for m in measurements: |
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m_arr = m.as_array() |
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if m.constellation_id == ConstellationId.GPS: |
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ekf_data[ObservationKind.PSEUDORANGE_GPS].append(m_arr) |
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ekf_data[ObservationKind.PSEUDORANGE_RATE_GPS].append(m_arr) |
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elif m.constellation_id == ConstellationId.GLONASS: |
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ekf_data[ObservationKind.PSEUDORANGE_GLONASS].append(m_arr) |
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ekf_data[ObservationKind.PSEUDORANGE_RATE_GLONASS].append(m_arr) |
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for kind, data in ekf_data.items(): |
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gnss_kf.predict_and_observe(t, kind, data) |
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def get_bearing_from_gnss(ecef_pos, ecef_vel, vel_std): |
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# init orientation with direction of velocity |
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converter = coord.LocalCoord.from_ecef(ecef_pos) |
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ned_vel = np.einsum('ij,j ->i', converter.ned_from_ecef_matrix, ecef_vel) |
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bearing = np.arctan2(ned_vel[1], ned_vel[0]) |
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bearing_std = np.arctan2(vel_std, np.linalg.norm(ned_vel)) |
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return float(np.rad2deg(bearing)), float(bearing_std) |
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def main(): |
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dog = AstroDog() |
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dog = AstroDog(use_internet=True) |
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sm = messaging.SubMaster(['ubloxGnss']) |
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pm = messaging.PubMaster(['gnssMeasurements']) |
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laikad = Laikad() |
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while True: |
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sm.update() |
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# Todo if no internet available use latest ephemeris |
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if sm.updated['ubloxGnss']: |
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ublox_msg = sm['ubloxGnss'] |
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msg = process_ublox_msg(ublox_msg, dog, sm.logMonoTime['ubloxGnss']) |
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if msg is None: |
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msg = messaging.new_message('gnssMeasurements') |
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msg = laikad.process_ublox_msg(ublox_msg, dog, sm.logMonoTime['ubloxGnss']) |
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if msg is not None: |
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pm.send('gnssMeasurements', msg) |
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if __name__ == "__main__": |
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main() |
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