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ardupilot/libraries/AP_AHRS/AP_AHRS_DCM.cpp

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/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
/*
* APM_AHRS_DCM.cpp
*
* AHRS system using DCM matrices
*
* Based on DCM code by Doug Weibel, Jordi Muñoz and Jose Julio. DIYDrones.com
*
* Adapted for the general ArduPilot AHRS interface by Andrew Tridgell
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public License
* as published by the Free Software Foundation; either version 2.1
* of the License, or (at your option) any later version.
*/
#include <FastSerial.h>
#include <AP_AHRS.h>
// this is the speed in cm/s above which we first get a yaw lock with
// the GPS
#define GPS_SPEED_MIN 300
// this is the speed in cm/s at which we stop using drift correction
// from the GPS and wait for the ground speed to get above GPS_SPEED_MIN
#define GPS_SPEED_RESET 100
// the limit (in degrees/second) beyond which we stop integrating
// omega_I. At larger spin rates the DCM PI controller can get 'dizzy'
// which results in false gyro drift. See
// http://gentlenav.googlecode.com/files/fastRotations.pdf
#define SPIN_RATE_LIMIT 20
// run a full DCM update round
void
AP_AHRS_DCM::update(void)
{
float delta_t;
// tell the IMU to grab some data
_imu->update();
// ask the IMU how much time this sensor reading represents
delta_t = _imu->get_delta_time();
// Get current values for gyros
_gyro_vector = _imu->get_gyro();
_accel_vector = _imu->get_accel();
// Integrate the DCM matrix using gyro inputs
matrix_update(delta_t);
// Normalize the DCM matrix
normalize();
// Perform drift correction
drift_correction(delta_t);
// paranoid check for bad values in the DCM matrix
check_matrix();
// Calculate pitch, roll, yaw for stabilization and navigation
euler_angles();
}
// update the DCM matrix using only the gyros
void
AP_AHRS_DCM::matrix_update(float _G_Dt)
{
// note that we do not include the P terms in _omega. This is
// because the spin_rate is calculated from _omega.length(),
// and including the P terms would give positive feedback into
// the _P_gain() calculation, which can lead to a very large P
// value
_omega = _gyro_vector + _omega_I;
_dcm_matrix.rotate((_omega + _omega_P + _omega_yaw_P) * _G_Dt);
}
/*
* reset the DCM matrix and omega. Used on ground start, and on
* extreme errors in the matrix
*/
void
AP_AHRS_DCM::reset(bool recover_eulers)
{
// reset the integration terms
_omega_I.zero();
_omega_P.zero();
_omega_yaw_P.zero();
_omega.zero();
// if the caller wants us to try to recover to the current
// attitude then calculate the dcm matrix from the current
// roll/pitch/yaw values
if (recover_eulers && !isnan(roll) && !isnan(pitch) && !isnan(yaw)) {
_dcm_matrix.from_euler(roll, pitch, yaw);
} else {
// otherwise make it flat
_dcm_matrix.from_euler(0, 0, 0);
}
}
/*
* check the DCM matrix for pathological values
*/
void
AP_AHRS_DCM::check_matrix(void)
{
if (_dcm_matrix.is_nan()) {
//Serial.printf("ERROR: DCM matrix NAN\n");
SITL_debug("ERROR: DCM matrix NAN\n");
renorm_blowup_count++;
reset(true);
return;
}
// some DCM matrix values can lead to an out of range error in
// the pitch calculation via asin(). These NaN values can
// feed back into the rest of the DCM matrix via the
// error_course value.
if (!(_dcm_matrix.c.x < 1.0 &&
_dcm_matrix.c.x > -1.0)) {
// We have an invalid matrix. Force a normalisation.
renorm_range_count++;
normalize();
if (_dcm_matrix.is_nan() ||
fabs(_dcm_matrix.c.x) > 10) {
// normalisation didn't fix the problem! We're
// in real trouble. All we can do is reset
//Serial.printf("ERROR: DCM matrix error. _dcm_matrix.c.x=%f\n",
// _dcm_matrix.c.x);
SITL_debug("ERROR: DCM matrix error. _dcm_matrix.c.x=%f\n",
_dcm_matrix.c.x);
renorm_blowup_count++;
reset(true);
}
}
}
// renormalise one vector component of the DCM matrix
// this will return false if renormalization fails
bool
AP_AHRS_DCM::renorm(Vector3f const &a, Vector3f &result)
{
float renorm_val;
// numerical errors will slowly build up over time in DCM,
// causing inaccuracies. We can keep ahead of those errors
// using the renormalization technique from the DCM IMU paper
// (see equations 18 to 21).
// For APM we don't bother with the taylor expansion
// optimisation from the paper as on our 2560 CPU the cost of
// the sqrt() is 44 microseconds, and the small time saving of
// the taylor expansion is not worth the potential of
// additional error buildup.
// Note that we can get significant renormalisation values
// when we have a larger delta_t due to a glitch eleswhere in
// APM, such as a I2c timeout or a set of EEPROM writes. While
// we would like to avoid these if possible, if it does happen
// we don't want to compound the error by making DCM less
// accurate.
renorm_val = 1.0 / a.length();
// keep the average for reporting
_renorm_val_sum += renorm_val;
_renorm_val_count++;
if (!(renorm_val < 2.0 && renorm_val > 0.5)) {
// this is larger than it should get - log it as a warning
renorm_range_count++;
if (!(renorm_val < 1.0e6 && renorm_val > 1.0e-6)) {
// we are getting values which are way out of
// range, we will reset the matrix and hope we
// can recover our attitude using drift
// correction before we hit the ground!
//Serial.printf("ERROR: DCM renormalisation error. renorm_val=%f\n",
// renorm_val);
SITL_debug("ERROR: DCM renormalisation error. renorm_val=%f\n",
renorm_val);
renorm_blowup_count++;
return false;
}
}
result = a * renorm_val;
return true;
}
/*************************************************
* Direction Cosine Matrix IMU: Theory
* William Premerlani and Paul Bizard
*
* Numerical errors will gradually reduce the orthogonality conditions expressed by equation 5
* to approximations rather than identities. In effect, the axes in the two frames of reference no
* longer describe a rigid body. Fortunately, numerical error accumulates very slowly, so it is a
* simple matter to stay ahead of it.
* We call the process of enforcing the orthogonality conditions ÒrenormalizationÓ.
*/
void
AP_AHRS_DCM::normalize(void)
{
float error;
Vector3f t0, t1, t2;
error = _dcm_matrix.a * _dcm_matrix.b; // eq.18
t0 = _dcm_matrix.a - (_dcm_matrix.b * (0.5f * error)); // eq.19
t1 = _dcm_matrix.b - (_dcm_matrix.a * (0.5f * error)); // eq.19
t2 = t0 % t1; // c= a x b // eq.20
if (!renorm(t0, _dcm_matrix.a) ||
!renorm(t1, _dcm_matrix.b) ||
!renorm(t2, _dcm_matrix.c)) {
// Our solution is blowing up and we will force back
// to last euler angles
reset(true);
}
}
// produce a yaw error value. The returned value is proportional
// to sin() of the current heading error in earth frame
float
AP_AHRS_DCM::yaw_error_compass(void)
{
Vector3f mag = Vector3f(_compass->mag_x, _compass->mag_y, _compass->mag_z);
// get the mag vector in the earth frame
Vector3f rb = _dcm_matrix * mag;
rb.normalize();
if (rb.is_inf()) {
// not a valid vector
return 0.0;
}
// get the earths magnetic field (only X and Y components needed)
Vector3f mag_earth = Vector3f(cos(_compass->get_declination()),
sin(_compass->get_declination()), 0);
// calculate the error term in earth frame
Vector3f error = rb % mag_earth;
return error.z;
}
// produce a yaw error value using the GPS. The returned value is proportional
// to sin() of the current heading error in earth frame
float
AP_AHRS_DCM::yaw_error_gps(void)
{
return sin(ToRad(_gps->ground_course * 0.01) - yaw);
}
// the _P_gain raises the gain of the PI controller
// when we are spinning fast. See the fastRotations
// paper from Bill.
float
AP_AHRS_DCM::_P_gain(float spin_rate)
{
if (spin_rate < ToDeg(50)) {
return 1.0;
}
if (spin_rate > ToDeg(500)) {
return 10.0;
}
return spin_rate/ToDeg(50);
}
// return true if we have and should use GPS
bool AP_AHRS_DCM::have_gps(void)
{
if (!_gps || _gps->status() != GPS::GPS_OK || !_gps_use) {
return false;
}
return true;
}
// yaw drift correction using the compass or GPS
// this function prodoces the _omega_yaw_P vector, and also
// contributes to the _omega_I.z long term yaw drift estimate
void
AP_AHRS_DCM::drift_correction_yaw(void)
{
bool new_value = false;
float yaw_error;
float yaw_deltat;
if (_compass && _compass->use_for_yaw()) {
if (_compass->last_update != _compass_last_update) {
yaw_deltat = (_compass->last_update - _compass_last_update) * 1.0e-6;
_compass_last_update = _compass->last_update;
// we force an additional compass read()
// here. This has the effect of throwing away
// the first compass value, which can be bad
if (!_have_initial_yaw && _compass->read()) {
float heading = _compass->calculate_heading(_dcm_matrix);
_dcm_matrix.from_euler(roll, pitch, heading);
_omega_yaw_P.zero();
_have_initial_yaw = true;
}
new_value = true;
yaw_error = yaw_error_compass();
}
} else if (_fly_forward && have_gps()) {
if (_gps->last_fix_time != _gps_last_update &&
_gps->ground_speed >= GPS_SPEED_MIN) {
yaw_deltat = (_gps->last_fix_time - _gps_last_update) * 1.0e-3;
_gps_last_update = _gps->last_fix_time;
if (!_have_initial_yaw) {
_dcm_matrix.from_euler(roll, pitch, ToRad(_gps->ground_course*0.01));
_omega_yaw_P.zero();
_have_initial_yaw = true;
}
new_value = true;
yaw_error = yaw_error_gps();
}
}
if (!new_value) {
// we don't have any new yaw information
// slowly decay _omega_yaw_P to cope with loss
// of our yaw source
_omega_yaw_P *= 0.97;
return;
}
// the yaw error is a vector in earth frame
Vector3f error = Vector3f(0,0, yaw_error);
// convert the error vector to body frame
error = _dcm_matrix.mul_transpose(error);
// the spin rate changes the P gain, and disables the
// integration at higher rates
float spin_rate = _omega.length();
// update the proportional control to drag the
// yaw back to the right value. We use a gain
// that depends on the spin rate. See the fastRotations.pdf
// paper from Bill Premerlani
_omega_yaw_P.z = error.z * _P_gain(spin_rate) * _kp_yaw;
if (_fast_ground_gains) {
_omega_yaw_P.z *= 8;
}
// don't update the drift term if we lost the yaw reference
// for more than 2 seconds
if (yaw_deltat < 2.0 && spin_rate < ToRad(SPIN_RATE_LIMIT)) {
// also add to the I term
_omega_I_sum.z += error.z * _ki_yaw * yaw_deltat;
}
_error_yaw_sum += fabs(yaw_error);
_error_yaw_count++;
}
// perform drift correction. This function aims to update _omega_P and
// _omega_I with our best estimate of the short term and long term
// gyro error. The _omega_P value is what pulls our attitude solution
// back towards the reference vector quickly. The _omega_I term is an
// attempt to learn the long term drift rate of the gyros.
//
// This drift correction implementation is based on a paper
// by Bill Premerlani from here:
// http://gentlenav.googlecode.com/files/RollPitchDriftCompensation.pdf
void
AP_AHRS_DCM::drift_correction(float deltat)
{
Vector3f velocity;
uint32_t last_correction_time;
// perform yaw drift correction if we have a new yaw reference
// vector
drift_correction_yaw();
// integrate the accel vector in the earth frame between GPS readings
_ra_sum += _dcm_matrix * (_accel_vector * deltat);
// keep a sum of the deltat values, so we know how much time
// we have integrated over
_ra_deltat += deltat;
if (!have_gps() || _gps->num_sats < 6) {
// no GPS, or not a good lock. From experience we need at
// least 6 satellites to get a really reliable velocity number
// from the GPS.
//
// As a fallback we use the fixed wing acceleration correction
// if we have an airspeed estimate (which we only have if
// _fly_forward is set), otherwise no correction
if (_ra_deltat < 0.2) {
// not enough time has accumulated
return;
}
float airspeed;
if (_airspeed && _airspeed->use()) {
airspeed = _airspeed->get_airspeed();
} else {
airspeed = _last_airspeed;
}
// use airspeed to estimate our ground velocity in
// earth frame by subtracting the wind
velocity = _dcm_matrix.colx() * airspeed;
// add in wind estimate
velocity += _wind;
last_correction_time = millis();
_have_gps_lock = false;
// update position delta for get_position()
_position_offset_north += velocity.x * _ra_deltat;
_position_offset_east += velocity.y * _ra_deltat;
} else {
if (_gps->last_fix_time == _ra_sum_start) {
// we don't have a new GPS fix - nothing more to do
return;
}
velocity = Vector3f(_gps->velocity_north(), _gps->velocity_east(), _gps->velocity_down());
last_correction_time = _gps->last_fix_time;
if (_have_gps_lock == false) {
// if we didn't have GPS lock in the last drift
// correction interval then set the velocities equal
_last_velocity = velocity;
}
_have_gps_lock = true;
// remember position for get_position()
_last_lat = _gps->latitude;
_last_lng = _gps->longitude;
_position_offset_north = 0;
_position_offset_east = 0;
// once we have a single GPS lock, we update using
// dead-reckoning from then on
_have_position = true;
// keep last airspeed estimate for dead-reckoning purposes
Vector3f airspeed = velocity - _wind;
airspeed.z = 0;
_last_airspeed = airspeed.length();
}
/*
* The barometer for vertical velocity is only enabled if we got
* at least 5 pressure samples for the reading. This ensures we
* don't use very noisy climb rate data
*/
if (_baro_use && _barometer != NULL && _barometer->get_pressure_samples() >= 5) {
// Z velocity is down
velocity.z = -_barometer->get_climb_rate();
}
// see if this is our first time through - in which case we
// just setup the start times and return
if (_ra_sum_start == 0) {
_ra_sum_start = last_correction_time;
_last_velocity = velocity;
return;
}
// equation 9: get the corrected acceleration vector in earth frame. Units
// are m/s/s
Vector3f GA_e;
float v_scale = gps_gain.get()/(_ra_deltat*_gravity);
Vector3f vdelta = (velocity - _last_velocity) * v_scale;
// limit vertical acceleration correction to 0.5 gravities. The
// barometer sometimes gives crazy acceleration changes.
vdelta.z = constrain(vdelta.z, -0.5, 0.5);
GA_e = Vector3f(0, 0, -1.0) + vdelta;
GA_e.normalize();
if (GA_e.is_inf()) {
// wait for some non-zero acceleration information
return;
}
// calculate the error term in earth frame.
Vector3f GA_b = _ra_sum / (_ra_deltat * _gravity);
float length = GA_b.length();
if (length > 1.0) {
GA_b /= length;
if (GA_b.is_inf()) {
// wait for some non-zero acceleration information
return;
}
}
Vector3f error = GA_b % GA_e;
#define YAW_INDEPENDENT_DRIFT_CORRECTION 0
#if YAW_INDEPENDENT_DRIFT_CORRECTION
// step 2 calculate earth_error_Z
float earth_error_Z = error.z;
// equation 10
float tilt = sqrt(sq(GA_e.x) + sq(GA_e.y));
// equation 11
float theta = atan2(GA_b.y, GA_b.x);
// equation 12
Vector3f GA_e2 = Vector3f(cos(theta)*tilt, sin(theta)*tilt, GA_e.z);
// step 6
error = GA_b % GA_e2;
error.z = earth_error_Z;
#endif // YAW_INDEPENDENT_DRIFT_CORRECTION
// to reduce the impact of two competing yaw controllers, we
// reduce the impact of the gps/accelerometers on yaw when we are
// flat, but still allow for yaw correction using the
// accelerometers at high roll angles as long as we have a GPS
if (_compass && _compass->use_for_yaw()) {
if (have_gps() && gps_gain == 1.0) {
error.z *= sin(fabs(roll));
} else {
error.z = 0;
}
}
// convert the error term to body frame
error = _dcm_matrix.mul_transpose(error);
if (error.is_nan() || error.is_inf()) {
// don't allow bad values
check_matrix();
return;
}
_error_rp_sum += error.length();
_error_rp_count++;
// base the P gain on the spin rate
float spin_rate = _omega.length();
// we now want to calculate _omega_P and _omega_I. The
// _omega_P value is what drags us quickly to the
// accelerometer reading.
_omega_P = error * _P_gain(spin_rate) * _kp;
if (_fast_ground_gains) {
_omega_P *= 8;
}
// accumulate some integrator error
if (spin_rate < ToRad(SPIN_RATE_LIMIT)) {
_omega_I_sum += error * _ki * _ra_deltat;
_omega_I_sum_time += _ra_deltat;
}
if (_omega_I_sum_time >= 5) {
// limit the rate of change of omega_I to the hardware
// reported maximum gyro drift rate. This ensures that
// short term errors don't cause a buildup of omega_I
// beyond the physical limits of the device
float change_limit = _gyro_drift_limit * _omega_I_sum_time;
_omega_I_sum.x = constrain(_omega_I_sum.x, -change_limit, change_limit);
_omega_I_sum.y = constrain(_omega_I_sum.y, -change_limit, change_limit);
_omega_I_sum.z = constrain(_omega_I_sum.z, -change_limit, change_limit);
_omega_I += _omega_I_sum;
_omega_I_sum.zero();
_omega_I_sum_time = 0;
}
// zero our accumulator ready for the next GPS step
_ra_sum.zero();
_ra_deltat = 0;
_ra_sum_start = last_correction_time;
// remember the velocity for next time
_last_velocity = velocity;
if (_have_gps_lock && _fly_forward) {
// update wind estimate
estimate_wind(velocity);
}
}
// update our wind speed estimate
void AP_AHRS_DCM::estimate_wind(Vector3f &velocity)
{
// this is based on the wind speed estimation code from MatrixPilot by
// Bill Premerlani. Adaption for ArduPilot by Jon Challinger
// See http://gentlenav.googlecode.com/files/WindEstimation.pdf
Vector3f fuselageDirection = _dcm_matrix.colx();
Vector3f fuselageDirectionDiff = fuselageDirection - _last_fuse;
uint32_t now = millis();
// scrap our data and start over if we're taking too long to get a direction change
if (now - _last_wind_time > 10000) {
_last_wind_time = now;
_last_fuse = fuselageDirection;
_last_vel = velocity;
return;
}
float diff_length = fuselageDirectionDiff.length();
if (diff_length > 0.2) {
// when turning, use the attitude response to estimate
// wind speed
float V;
Vector3f velocityDiff = velocity - _last_vel;
// estimate airspeed it using equation 6
V = velocityDiff.length() / diff_length;
_last_fuse = fuselageDirection;
_last_vel = velocity;
Vector3f fuselageDirectionSum = fuselageDirection + _last_fuse;
Vector3f velocitySum = velocity + _last_vel;
float theta = atan2(velocityDiff.y, velocityDiff.x) - atan2(fuselageDirectionDiff.y, fuselageDirectionDiff.x);
float sintheta = sin(theta);
float costheta = cos(theta);
Vector3f wind = Vector3f();
wind.x = velocitySum.x - V * (costheta * fuselageDirectionSum.x - sintheta * fuselageDirectionSum.y);
wind.y = velocitySum.y - V * (sintheta * fuselageDirectionSum.x + costheta * fuselageDirectionSum.y);
wind.z = velocitySum.z - V * fuselageDirectionSum.z;
wind *= 0.5;
if (wind.length() < _wind.length() + 20) {
_wind = _wind * 0.95 + wind * 0.05;
}
_last_wind_time = now;
} else if (now - _last_wind_time > 2000 && _airspeed && _airspeed->use()) {
// when flying straight use airspeed to get wind estimate if available
Vector3f airspeed = _dcm_matrix.colx() * _airspeed->get_airspeed();
Vector3f wind = velocity - airspeed;
_wind = _wind * 0.92 + wind * 0.08;
}
}
// calculate the euler angles which will be used for high level
// navigation control
void
AP_AHRS_DCM::euler_angles(void)
{
_dcm_matrix.to_euler(&roll, &pitch, &yaw);
roll_sensor = degrees(roll) * 100;
pitch_sensor = degrees(pitch) * 100;
yaw_sensor = degrees(yaw) * 100;
if (yaw_sensor < 0)
yaw_sensor += 36000;
}
/* reporting of DCM state for MAVLink */
// average error_roll_pitch since last call
float AP_AHRS_DCM::get_error_rp(void)
{
if (_error_rp_count == 0) {
// this happens when telemetry is setup on two
// serial ports
return _error_rp_last;
}
_error_rp_last = _error_rp_sum / _error_rp_count;
_error_rp_sum = 0;
_error_rp_count = 0;
return _error_rp_last;
}
// average error_yaw since last call
float AP_AHRS_DCM::get_error_yaw(void)
{
if (_error_yaw_count == 0) {
// this happens when telemetry is setup on two
// serial ports
return _error_yaw_last;
}
_error_yaw_last = _error_yaw_sum / _error_yaw_count;
_error_yaw_sum = 0;
_error_yaw_count = 0;
return _error_yaw_last;
}
// return our current position estimate using
// dead-reckoning or GPS
bool AP_AHRS_DCM::get_position(struct Location *loc)
{
if (!_have_position) {
return false;
}
loc->lat = _last_lat;
loc->lng = _last_lng;
location_offset(loc, _position_offset_north, _position_offset_east);
return true;
}
// return an airspeed estimate if available
bool AP_AHRS_DCM::airspeed_estimate(float *airspeed_ret)
{
bool ret = false;
if (_airspeed && _airspeed->use()) {
*airspeed_ret = _airspeed->get_airspeed();
ret = true;
}
// estimate it via GPS speed and wind
if (have_gps()) {
*airspeed_ret = _last_airspeed;
ret = true;
}
if (ret && _wind_max > 0 && _gps && _gps->status() == GPS::GPS_OK) {
// constrain the airspeed by the ground speed
// and AHRS_WIND_MAX
*airspeed_ret = constrain(*airspeed_ret,
_gps->ground_speed*0.01 - _wind_max,
_gps->ground_speed*0.01 + _wind_max);
}
return ret;
}
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