void Ekf::controlOpticalFlowFusion()
{
// Check for new optical flow data that has fallen behind the fusion time horizon
if (_flow_data_ready) {
// optical flow fusion mode selection logic
if ((_params.fusion_mode & MASK_USE_OF) // optical flow has been selected by the user
&& !_control_status.flags.opt_flow // we are not yet using flow data
&& _control_status.flags.tilt_align // we know our tilt attitude
&& (_time_last_imu - _time_last_hagl_fuse) < 5e5) // we have a valid distance to ground estimate
{
// If the heading is not aligned, reset the yaw and magnetic field states
if (!_control_status.flags.yaw_align) {
_control_status.flags.yaw_align = resetMagHeading(_mag_sample_delayed.mag);
}
// If the heading is valid, start using optical flow aiding
if (_control_status.flags.yaw_align) {
// set the flag and reset the fusion timeout
_control_status.flags.opt_flow = true;
_time_last_of_fuse = _time_last_imu;
// if we are not using GPS then the velocity and position states and covariances need to be set
if (!_control_status.flags.gps) {
// constrain height above ground to be above minimum possible
float heightAboveGndEst = fmaxf((_terrain_vpos - _state.pos(2)), _params.rng_gnd_clearance);
// calculate absolute distance from focal point to centre of frame assuming a flat earth
float range = heightAboveGndEst / _R_to_earth(2, 2);
if ((range - _params.rng_gnd_clearance) > 0.3f && _flow_sample_delayed.dt > 0.05f) {
// we should have reliable OF measurements so
// calculate X and Y body relative velocities from OF measurements
Vector3f vel_optflow_body;
vel_optflow_body(0) = - range * _flow_sample_delayed.flowRadXYcomp(1) / _flow_sample_delayed.dt;
vel_optflow_body(1) = range * _flow_sample_delayed.flowRadXYcomp(0) / _flow_sample_delayed.dt;
vel_optflow_body(2) = 0.0f;
// rotate from body to earth frame
Vector3f vel_optflow_earth;
vel_optflow_earth = _R_to_earth * vel_optflow_body;
// take x and Y components
_state.vel(0) = vel_optflow_earth(0);
_state.vel(1) = vel_optflow_earth(1);
} else {
_state.vel(0) = 0.0f;
_state.vel(1) = 0.0f;
}
// reset the velocity covariance terms
zeroRows(P,4,5);
zeroCols(P,4,5);
// reset the horizontal velocity variance using the optical flow noise variance
P[5][5] = P[4][4] = sq(range) * calcOptFlowMeasVar();
if (!_control_status.flags.in_air) {
// we are likely starting OF for the first time so reset the horizontal position and vertical velocity states
_state.pos(0) = 0.0f;
_state.pos(1) = 0.0f;
// reset the corresponding covariances
// we are by definition at the origin at commencement so variances are also zeroed
zeroRows(P,7,8);
zeroCols(P,7,8);
// align the output observer to the EKF states
alignOutputFilter();
}
}
}
} else if (!(_params.fusion_mode & MASK_USE_OF)) {
_control_status.flags.opt_flow = false;
}
// handle the case when we are relying on optical flow fusion and lose it
if (_control_status.flags.opt_flow && !_control_status.flags.gps) {
// We are relying on flow aiding to constrain attitude drift so after 5s without aiding we need to do something
if ((_time_last_imu - _time_last_of_fuse > 5e6)) {
// Switch to the non-aiding mode, zero the velocity states
// and set the synthetic position to the current estimate
_control_status.flags.opt_flow = false;
_last_known_posNE(0) = _state.pos(0);
_last_known_posNE(1) = _state.pos(1);
_state.vel.setZero();
}
}
// fuse the data
if (_control_status.flags.opt_flow) {
// Update optical flow bias estimates
calcOptFlowBias();
// Fuse optical flow LOS rate observations into the main filter
fuseOptFlow();
_last_known_posNE(0) = _state.pos(0);
_last_known_posNE(1) = _state.pos(1);
}
}
}
bool Ekf::update()
{
if (!_filter_initialised) {
_filter_initialised = initialiseFilter();
if (!_filter_initialised) {
return false;
}
}
// Only run the filter if IMU data in the buffer has been updated
if (_imu_updated) {
// perform state and covariance prediction for the main filter
predictState();
predictCovariance();
// perform state and variance prediction for the terrain estimator
if (!_terrain_initialised) {
_terrain_initialised = initHagl();
} else {
predictHagl();
}
// control logic
controlFusionModes();
// measurement updates
// Fuse magnetometer data using the selected fuson method and only if angular alignment is complete
if (_mag_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_mag_sample_delayed)) {
if (_control_status.flags.mag_3D && _control_status.flags.yaw_align) {
fuseMag();
if (_control_status.flags.mag_dec) {
fuseDeclination();
}
} else if (_control_status.flags.mag_2D && _control_status.flags.yaw_align) {
fuseMag2D();
} else if (_control_status.flags.mag_hdg && _control_status.flags.yaw_align) {
// fusion of a Euler yaw angle from either a 321 or 312 rotation sequence
fuseHeading();
} else {
// do no fusion at all
}
}
// determine if range finder data has fallen behind the fusin time horizon fuse it if we are
// not tilted too much to use it
if (_range_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_range_sample_delayed)
&& (_R_prev(2, 2) > 0.7071f)) {
// if we have range data we always try to estimate terrain height
_fuse_hagl_data = true;
// only use range finder as a height observation in the main filter if specifically enabled
if (_control_status.flags.rng_hgt) {
_fuse_height = true;
}
} else if ((_time_last_imu - _time_last_hgt_fuse) > 2 * RNG_MAX_INTERVAL && _control_status.flags.rng_hgt) {
// If we are supposed to be using range finder data as the primary height sensor, have missed or rejected measurements
// and are on the ground, then synthesise a measurement at the expected on ground value
if (!_in_air) {
_range_sample_delayed.rng = _params.rng_gnd_clearance;
_range_sample_delayed.time_us = _imu_sample_delayed.time_us;
}
_fuse_height = true;
}
// determine if baro data has fallen behind the fuson time horizon and fuse it in the main filter if enabled
if (_baro_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_baro_sample_delayed)) {
if (_control_status.flags.baro_hgt) {
_fuse_height = true;
} else {
// calculate a filtered offset between the baro origin and local NED origin if we are not using the baro as a height reference
float offset_error = _state.pos(2) + _baro_sample_delayed.hgt - _hgt_sensor_offset - _baro_hgt_offset;
_baro_hgt_offset += 0.02f * math::constrain(offset_error, -5.0f, 5.0f);
}
}
// If we are using GPS aiding and data has fallen behind the fusion time horizon then fuse it
if (_gps_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_gps_sample_delayed)) {
// Only use GPS data for position and velocity aiding if enabled
if (_control_status.flags.gps) {
_fuse_pos = true;
_fuse_vert_vel = true;
_fuse_hor_vel = true;
}
// only use gps height observation in the main filter if specifically enabled
if (_control_status.flags.gps_hgt) {
_fuse_height = true;
}
}
// If we are using optical flow aiding and data has fallen behind the fusion time horizon, then fuse it
if (_flow_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_flow_sample_delayed)
&& _control_status.flags.opt_flow && (_time_last_imu - _time_last_optflow) < 2e5
&& (_R_prev(2, 2) > 0.7071f)) {
_fuse_flow = true;
}
// if we aren't doing any aiding, fake GPS measurements at the last known position to constrain drift
// Coincide fake measurements with baro data for efficiency with a minimum fusion rate of 5Hz
if (!_control_status.flags.gps && !_control_status.flags.opt_flow
&& ((_time_last_imu - _time_last_fake_gps > 2e5) || _fuse_height)) {
_fuse_pos = true;
_gps_sample_delayed.pos(0) = _last_known_posNE(0);
_gps_sample_delayed.pos(1) = _last_known_posNE(1);
_time_last_fake_gps = _time_last_imu;
}
// fuse available range finder data into a terrain height estimator if it has been initialised
if (_fuse_hagl_data && _terrain_initialised) {
fuseHagl();
_fuse_hagl_data = false;
}
// Fuse available NED velocity and position data into the main filter
if (_fuse_height || _fuse_pos || _fuse_hor_vel || _fuse_vert_vel) {
fuseVelPosHeight();
_fuse_hor_vel = _fuse_vert_vel = _fuse_pos = _fuse_height = false;
}
// Update optical flow bias estimates
calcOptFlowBias();
// Fuse optical flow LOS rate observations into the main filter
if (_fuse_flow) {
fuseOptFlow();
_last_known_posNE(0) = _state.pos(0);
_last_known_posNE(1) = _state.pos(1);
_fuse_flow = false;
}
// TODO This is just to get the logic inside but we will only start fusion once we tested this again
if (_airspeed_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_airspeed_sample_delayed) && false) {
fuseAirspeed();
}
}
// the output observer always runs
calculateOutputStates();
// check for NaN on attitude states
if (isnan(_state.quat_nominal(0)) || isnan(_output_new.quat_nominal(0))) {
return false;
}
// We don't have valid data to output until tilt and yaw alignment is complete
if (_control_status.flags.tilt_align && _control_status.flags.yaw_align) {
return true;
} else {
return false;
}
}
