- _flt_mag_align_complete was not set when choosing pure 3D mag fusion.
one effect of this was that the declination used in the filter was not
the one calculated from the magnetic field states.
Signed-off-by: Roman <bapstroman@gmail.com>
The handling of invalid flow data when on ground is performed in controlOpticalFlowFusion() where it is able to handle flow sensors that don't publish gyro data.
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.
The parameter used to control the maximum dead reckoning time had 'gps' in the parameter name which was confusing because it was used for all measurement types capable of constraining horizontal velocity error growth. The parameter variable has been renamed and the documentation for it improved.
The parameter used to control the maximum time since fusing a measurement before the measurement is considered to be not contributing to aiding had misleading documentation which has been updated.
* terrain_estimator : guard against case where latest range sample is newer than IMU sample
* EKF : control : correct detection of no optical flow fusion over a time period
Motion compensated optical flow rates are supposed to be zeroed if reported flow quality is below the minimum threshold value when on ground.
The comments and logic have been amended to be consistent and make the design intent clearer.
Terrain validity is determined solely by successful range finder fusion and terrain state initialisation.
A range finder that has been declared faulty requires continuous range finder data fusion requires data to be continuous before the fault status _rng_hgt_faulty can be cleared. This will enforce the requirement for continuous data before fusion can commence.
Eliminate race condition caused by checking for data freshness using time stamps from buffer push instead than buffer pop events.
Consistent use of range data ready and range data fault flags. This achieved by ensuring that _rng_hgt_faulty is set to true for all range data faults, not just data freshness.
Include range data validity requirement in rangeAidConditionsMet() check.
* optical flow: fixed calculation of velocity of the flow sensor relative to
the IMU
- gyroXYZ holds a delta angle and first needs to converted to a gyro rate
Signed-off-by: Roman <bapstroman@gmail.com>
* optical flow: calculate height above the ground with respect to the flow
camera
- the flow camera can be offset from the IMU which needs to be considered
Signed-off-by: Roman <bapstroman@gmail.com>
* estimator interface: fixed comment regarding optical flow sample timestamp
- the timestamp on an optical flow sample corresponds to the trailing
edge of the flow integration period
Signed-off-by: Roman <bapstroman@gmail.com>
This brings all the range finder data checks (excluding innovation consistency checks) into one place and eliminates the need to perform range checking external to the library.
The hard coded optical flow tilt limit is changed to use the same value as the range finder.
Variable names are changed to make a clear distinction between the max/min values calculated by the stuck range check and the max/min valid values for the sensor.
* EKF angle constants in degrees for readability
* EKF make FILTER_UPDATE_PERIOD_MS static constexpr and add FILTER_UPDATE_PERIOD_S
* EKF controlOpticalFlowFusion() use constants and update comments
* EKF controlMagFusion() use angle in degrees
* EKF move earth spin rate to geo and update usage
* EKF: Fix numerical constant error and clean up comments
Comments do not need to contain numerical values when the code makes these clear.
* EKF collect_imu take const imu sample and populate buffer
* EKF calculateOutputStates cleanup
* EKF add calculate_quaternion output predictor method
* EKF: update documentation
* EKF: remove unnecessary getter function
* EKF calculateOutputStates only apply dt correction to bias
* EKF pytest assert attitude validity, not update() return
* EKF: correct documentation
* EKF: Do not make attitude validity dependent on yaw alignment status
Yaw alignment could fail in flight due to temporary loss of data and yet the quaternions would still usable for stabilisation even though the absolute earth yaw angle wrt true north was uncertain.
CarlOlsson
Paul Riseborough
Roman
jie.zhang
Daniel Agar
Dion Gonano
Kabir Mohammed
dakejahl
Paul Riseborough
Philipp Oettershagen