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Multi-EKF support (ekf2)

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- ekf2 can now run in multi-instance mode (currently up to 9 instances)
    - in multi mode all estimates are published to alternate topics (eg estimator_attitude instead of vehicle_attitude)
 - new ekf2 selector runs in multi-instance mode to monitor and compare all instances, selecting a primary (eg N x estimator_attitude => vehicle_attitude)
 - sensors module accel & gyro inconsistency checks are now relative to the mean of all instances, rather than the current primary (when active ekf2 selector is responsible for choosing primary accel & gyro)
 - existing consumers of estimator_status must check estimator_selector_status to select current primary instance status
 - ekf2 single instance mode is still fully supported and the default

Co-authored-by: Paul Riseborough <gncsolns@gmail.com>
This commit is contained in:
Daniel Agar
2020-10-27 10:56:11 -04:00
committed by GitHub
co-authored by Paul Riseborough
parent d5245a22d3
commit 0f411d6820
56 changed files with 1747 additions and 295 deletions
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src/modules/sensors/vehicle_air_data/VehicleAirData.cpp
+9 -3
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@@ -137,7 +137,7 @@ void VehicleAirData::Run()
if (!_advertised[uorb_index]) {
// use data's timestamp to throttle advertisement checks
if (hrt_elapsed_time(&_last_data[uorb_index].timestamp) > 1_s) {
if ((_last_data[uorb_index].timestamp == 0) || (hrt_elapsed_time(&_last_data[uorb_index].timestamp) > 1_s)) {
if (_sensor_sub[uorb_index].advertised()) {
if (uorb_index > 0) {
/* the first always exists, but for each further sensor, add a new validator */
@@ -151,12 +151,17 @@ void VehicleAirData::Run()
// force temperature correction update
SensorCorrectionsUpdate(true);
if (_selected_sensor_sub_index < 0) {
_sensor_sub[uorb_index].registerCallback();
}
} else {
_last_data[uorb_index].timestamp = hrt_absolute_time();
}
}
}
} else {
if (_advertised[uorb_index]) {
updated[uorb_index] = _sensor_sub[uorb_index].update(&_last_data[uorb_index]);
if (updated[uorb_index]) {
@@ -204,7 +209,8 @@ void VehicleAirData::Run()
_baro_sum_count++;
if ((_param_sens_baro_rate.get() > 0)
&& hrt_elapsed_time(&_last_publication_timestamp) >= (1e6f / _param_sens_baro_rate.get())) {
&& ((_last_publication_timestamp == 0)
|| (hrt_elapsed_time(&_last_publication_timestamp) >= (1e6f / _param_sens_baro_rate.get())))) {
const float pressure = _baro_sum / _baro_sum_count;
const hrt_abstime timestamp_sample = _baro_timestamp_sum / _baro_sum_count;