* EKF: centralize range finder tilt check
* Ekf-control: do not double check for terrain estimate validity
isRangeAidSuitable can only return true if the terrain estimate is valid
so there is no need for an additional check
* range_finder_checks: restructure the checks to avoid early returns
There is now only one clear path that can lead to the validity being
true.
Furthermore, if the _rng_hgt_valid is true, we can trust it and we don't
need for additional checks such as tilt.
The case where we need to provide fake measurements because the drone is
on the ground and the range finder data is bad is already handled
in "controlHeightFusion" so there is no need to hack the range finder
checks with that.
* Add Sensor and SensorRangeFinder classes
The purpose is to encapsulate the checks for each sensor in a dedicated
class with the same interface
* SensorRangeFinder: encapsulate in estimator::sensor namespace
* EKF: rename _sensor_rng to _range_sensor
* Range checks: include limits in valid range
* RangeChecks: update comment in the continuity checks
* RangeChecks: move more low-level checks in functions
Also move setTilt out of the terrain estimator, this is anyway protected internally
to not compute cos/sin if the parameter did not change.
* Sensor: remove unused virtual functions
Those are not required yet but can still be added later
* SensorRangeFinder: re-organise member variables
Also rename getRangeToEarth to getCosTilt
* SensorRangeFinder: split setSensorTilt and setCosMaxTilt functions
* SensorRangeFinder: Add a few unit tests
- good data
- tilt exceeded
- max range exceeded
* SensorRangeFinder: set hysteresis in us instead of ms
* SensorRangeFinder: Add more tests
* SensorRangeFinder: update continuity, hysteresis and stuck tests
* SensorRangeFinder: rename variables
* SensorRangeFinder: get rid of "delayed" specification
From the SensorRangeFinder class point of view, it's not relevant to
know if the data is delayed or not
* SensorRangeFinder: move time_last_valid out of stuck check
* SensorRangeFinder: rename file names to sensor_range_finder
* SensorRangeFinder: address Kamil's comments
* SensorRangeFinder: Add more tilt tests
* SensorRangeFinder: store current tilt offset
This is to avoid recomputing cos/sin functions at each loop
* EKF: Use common rate vector calculation for offset corrections
* EKF: Remove duplicate matrix entry calculations
* EKF: Create a EKF-GSF yaw estimator class
* EKF: add emergency yaw reset functionality
* EKF: remove un-used function
* EKF: Ensure required constants are defined for all builds
* EKF: Fix CI build error
* Revert "EKF: remove un-used function"
This reverts commit 93005309c7f3794414ad99c86218b3062e00bbd3.
* EKF: Replace in-lined Tait-Bryan 312 conversions with function call
Also remove unnecessary operations
* EKF: Remove unnecessary update of external vision rotation matrix
* EKF: Use const
* EKF: use const
* EKF: don't use class variable as a temporary variable
* EKF: update comments
* EKF: Improve efficiency of yaw reset
Use conversion from rotation matrix to Euler angles instead of quaternion to euler angles.
* EKF: use const
* EKF: remove un-used struct element
* EKF: more descriptive function name
* EKF: use existing matrix row operator
* EKF: remove unnecessary rotation matrix update
* EKF: Use square matrix type
* EKF: Improve protection for bad innovation covariance
* EKF: Use matrix library operations
* EKF: Replace memcpy with better alternative
memcpy bypasses compiler sanity checks and is unnecessary in this instance.
* EKF: Split EKF-GSF yaw reset function
Adds a common function to support yaw reset that can be used elsewhere.
* EKF: Use common function for quaternion state and covariance yaw reset
* EKF: Replace inlined matrix operation
* EKF: Use const
* EKF: Change accessor function name
* EKF: Use const
* EKF: Don't create unnecessary duplicate variable locations
* EKF: Remove duplicate covariance innovation inverse
* EKF: Don't create unnecessary duplicate variable locations
* EKF: Rely on geo library to provide gravity
* EKF: Improve protection from bad updates
* EKF: Reduce effect of vibration on yaw estimator AHRS
* EKF: Improve yaw estimator AHRS accuracy during manoeuvre transients
* ekf_control: Inhibit mag fusion when field magnitude is large
Move mag inhibition check in separate function
* ekf_control: pull out of functionalities out of controlMagFusion
- yaw abd mag bias observability checks
- mag 3D conditions
- load mag covariances
- set and clear mag control modes
* ekf_control: refactor mag heading/3D start/stop.
Move mag declination, mag 3d and mag heading fusion out of the main function
* ekf_control: extract mag yaw reset and mag declination fusion requirements
* ekf_control: use WMM in isStronMagneticField for mag fusion inhibition
- Correct units of WMM strength table
* ekf_control: extract mag_state_only functionality of AUTOFW (VTOL custom)
Also split inAirYawReset from onGroundYawReset
* ekf_control: extract mag automatic selection
- transform if-else into switch-case for parameter fusion type selection
* ekf_control: extract run3DMagAndDeclFusion, reorganize functions, fix
flag naming in Test script
* ekf_control: do not run mag fusion if tilt is not aligned.
Reset some variables on ground even if mag fusion is not running yet. It
could be that it runs later so we need to make sure that those variables
are properly set.
* ekf_control: move controlMagFusion and related functions to mag_control.cpp
* ekf control: check for validity of mag strength from WMM and falls back
to average earth mag field with larger gate if not valid
* ekf control: remove evyaw check for mag inhibition
* ekf control: change nested ternary operator into if-else if
* Ekf: create AlphaFilter template class for simple low-pass filtering
0.1/0.9 type low-pass filters are commonly used to smooth data, this
class is meant to abstract the computation of this filter
* ekf control: reset heading using mag_lpf data to avoid resetting on an outlier
fixes ecl issue #525
* ekf control: replace mag_states_only flag with mag_field_disturbed and
add parameter to enable or disable mag field strength check
* ekf control: remove AUTOFW mag fusion type as not needed This was implemented for VTOL but did not solve the problem and should not be used anymore
* ekf control: use start/stop mag functions everywhere instead of setting the flag
* ekf control: Run mag fusion depending on yaw_align instead of tilt_align
as there is no reason to fuse mag when the ekf isn't aligned
* AlphaFilter: add test for float and Vector3f
angle- and delta velocity bias variance
- the contribution of process noise per iteration for these states can be so
small that it gets lost if using standard floating point summation
Signed-off-by: Roman <bapstroman@gmail.com>
Heading data is assumed to be from a dual antenna array at a specified yaw angle offset in body frame, but with the heading data already corrected for antenna offset. The offset is required to apply the correct compensation for combined rotations and to determine when the yaw observation has become badly conditioned.
* Unfortunately, due to the SWIG dependency, we need sudo to install on
Travis (conflicts when adding with debian-sid source prevent using addons)
which means we cannot use the container-based infrastructure anymore.
* Building the Python bindings requires g++5 (at least with -Werr set).
* When building the Python bindings on Travis, the numpy includes are not found
by cmake, so they have to be added separately by running a Python process with
`numpy.get_include()`
* The build script now (somewhat clumsily) depends on the RUN_PYTEST environment
variable. If it is set to anything other than "", it will make the tests and
run tests and benchmarks
* Add requirements.txt file with required Python packages
* Read requirements.txt from CMakeLists.txt to check dependencies and alert the
user if necessary.
* Add SWIG interface definition (and external numpy interface) to ecl classes
* Add section in CMakeLists.txt to build Python bindings and execute
Python-based tests
* Write (property-based) tests that show the basic functionality of the Python
bindings and the EKF (using pytest and hypothesis libraries)
* Write minimal benchmark for the EKF update (using benchmark plugin for pytest)
* Add plotting utilities to analyze tests
* Add lint script to keep the Python scripts clean
kamilritz