* ekf2_derivation: use single source of state definition
The state is defined as an ordered dictionary of group elements and
everything else is generated using that state definition
* ekf2: generated state sample add const reference getter
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Co-authored-by: bresch <[brescianimathieu@gmail.com](mailto:brescianimathieu@gmail.com)>
Co-authored-by: Daniel Agar <daniel@agar.ca>
Tests showed that sideslip fusion often starts just before airspeed
fusion, resetting the wind states to 0 instead of using the airspeed
data. A quick look at the wind uncertainty allows to know if the current
wind estimate is meaningful or if we should rather reset it using the
airspeed data.
- pass new airspeed sample around when available
- can't completely eliminate _airspeed_sample_delayed until resetWind()
called from sideslip fusion is updated
- EKF isTimedOut(), isRecent(), and isNewestSampleRecent() need to handle the case where the timestamp has never been set
- reset() more thoroughly reset fields (mainly impacts unit tests)
- refactor all EKF backend output predictor pieces into new OutputPredictor class
- output states are now calculated immediately with new high rate IMU rather than after EKF update
- IMU delayed sample is passed as around as control data to avoid storing an extra copy and make the requirement clear
- update all msgs to be directly compatible with ROS2
- microdds_client improvements
- timesync
- reduced code size
- add to most default builds if we can afford it
- lots of other little changes
- purge fastrtps (I tried to save this multiple times, but kept hitting roadblocks)
- a growing number of samples come into the backend with the time
already delayed (sensor's interrupt setting timestamp sample)
- if the incoming timestamp is already delayed then the new data checks
(relative to latest IMU) can be slightly wrong
- handle almost all timestamps and checks on delayed time horizon,
except for explicit checks of new samples
- isRecent() and isTimedOut() helpers use delayed time
- add new isNewestSampleRecent() used for checking the incoming
timestamp of the incoming (adjusted) data
split the fusion process into:
1. updateAirspeed: computes innov, innov_var, obs_var, ...
2. fuseAirspeed: uses data computed in 1. to generate K, H and fuse the
observation
- ekf2: expose dead reckoning as control status flags
- commander:
- add GPS validity check
- in AUTO MISSION if dependent on GPS then a loss of GPS will
Daniel Agar