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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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Tools/ecl_ekf/plotting/pdf_report.py
+8 -10
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@@ -17,7 +17,7 @@ from plotting.data_plots import TimeSeriesPlot, InnovationPlot, ControlModeSumma
from analysis.detectors import PreconditionError
import analysis.data_version_handler as dvh
def create_pdf_report(ulog: ULog, output_plot_filename: str) -> None:
def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str) -> None:
"""
creates a pdf report of the ekf analysis.
:param ulog:
@@ -29,20 +29,18 @@ def create_pdf_report(ulog: ULog, output_plot_filename: str) -> None:
# save the plots to PDF
try:
estimator_status = ulog.get_dataset('estimator_status').data
print('found estimator_status data')
estimator_status = ulog.get_dataset('estimator_status', multi_instance).data
except:
raise PreconditionError('could not find estimator_status data')
raise PreconditionError('could not find estimator_status instance', multi_instance)
try:
estimator_states = ulog.get_dataset('estimator_states').data
print('found estimator_states data')
estimator_states = ulog.get_dataset('estimator_states', multi_instance).data
except:
raise PreconditionError('could not find estimator_states data')
raise PreconditionError('could not find estimator_states instance', multi_instance)
try:
estimator_innovations = ulog.get_dataset('estimator_innovations').data
estimator_innovation_variances = ulog.get_dataset('estimator_innovation_variances').data
estimator_innovations = ulog.get_dataset('estimator_innovations', multi_instance).data
estimator_innovation_variances = ulog.get_dataset('estimator_innovation_variances', multi_instance).data
innovation_data = estimator_innovations
for key in estimator_innovation_variances:
# append 'var' to the field name such that we can distingush between innov and innov_var
@@ -65,7 +63,7 @@ def create_pdf_report(ulog: ULog, output_plot_filename: str) -> None:
for key in innovation_data:
innovation_data[key] = innovation_data[key][0:innovation_data_min_length]
print('found innovation data (merged estimator_innovations + estimator_innovation_variances)')
print('found innovation data (merged estimator_innovations + estimator_innovation_variances) instance', multi_instance)
except:
raise PreconditionError('could not find innovation data')