mirror of https://github.com/ArduPilot/ardupilot
490 lines
14 KiB
C++
490 lines
14 KiB
C++
/*
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APM_AHRS_DCM.cpp
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AHRS system using DCM matrices
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Based on DCM code by Doug Weibel, Jordi Muñoz and Jose Julio. DIYDrones.com
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Adapted for the general ArduPilot AHRS interface by Andrew Tridgell
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public License
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as published by the Free Software Foundation; either version 2.1
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of the License, or (at your option) any later version.
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*/
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#include <FastSerial.h>
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#include <AP_AHRS.h>
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// this is the speed in cm/s above which we first get a yaw lock with
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// the GPS
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#define GPS_SPEED_MIN 300
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// this is the speed in cm/s at which we stop using drift correction
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// from the GPS and wait for the ground speed to get above GPS_SPEED_MIN
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#define GPS_SPEED_RESET 100
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// table of user settable parameters
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const AP_Param::GroupInfo AP_AHRS::var_info[] PROGMEM = {
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// @Param: YAW_P
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// @DisplayName: Yaw P
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// @Description: This controls the weight the compass has on the overall heading
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// @Range: 0 .4
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// @Increment: .01
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AP_GROUPINFO("YAW_P", 0, AP_AHRS_DCM, _kp_yaw),
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AP_GROUPEND
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};
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// run a full DCM update round
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void
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AP_AHRS_DCM::update(void)
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{
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float delta_t;
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// tell the IMU to grab some data
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_imu->update();
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// ask the IMU how much time this sensor reading represents
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delta_t = _imu->get_delta_time();
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// Get current values for gyros
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_gyro_vector = _imu->get_gyro();
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_accel_vector = _imu->get_accel();
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// Integrate the DCM matrix using gyro inputs
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matrix_update(delta_t);
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// Normalize the DCM matrix
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normalize();
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// Perform drift correction
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drift_correction(delta_t);
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// paranoid check for bad values in the DCM matrix
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check_matrix();
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// Calculate pitch, roll, yaw for stabilization and navigation
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euler_angles();
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}
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// update the DCM matrix using only the gyros
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void
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AP_AHRS_DCM::matrix_update(float _G_Dt)
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{
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// Equation 16, adding proportional and integral correction terms
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_omega = _gyro_vector + _omega_I;
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// add in P correction terms
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Vector3f r = (_omega + _omega_P + _omega_yaw_P) * _G_Dt;
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_dcm_matrix.rotate(r);
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}
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/*
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reset the DCM matrix and omega. Used on ground start, and on
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extreme errors in the matrix
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*/
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void
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AP_AHRS_DCM::reset(bool recover_eulers)
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{
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// reset the integration terms
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_omega_I.zero();
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_omega_P.zero();
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_omega.zero();
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// if the caller wants us to try to recover to the current
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// attitude then calculate the dcm matrix from the current
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// roll/pitch/yaw values
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if (recover_eulers && !isnan(roll) && !isnan(pitch) && !isnan(yaw)) {
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_dcm_matrix.from_euler(roll, pitch, yaw);
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} else {
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// otherwise make it flat
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_dcm_matrix.from_euler(0, 0, 0);
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}
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}
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/*
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check the DCM matrix for pathological values
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*/
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void
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AP_AHRS_DCM::check_matrix(void)
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{
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if (_dcm_matrix.is_nan()) {
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//Serial.printf("ERROR: DCM matrix NAN\n");
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SITL_debug("ERROR: DCM matrix NAN\n");
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renorm_blowup_count++;
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reset(true);
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return;
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}
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// some DCM matrix values can lead to an out of range error in
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// the pitch calculation via asin(). These NaN values can
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// feed back into the rest of the DCM matrix via the
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// error_course value.
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if (!(_dcm_matrix.c.x < 1.0 &&
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_dcm_matrix.c.x > -1.0)) {
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// We have an invalid matrix. Force a normalisation.
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renorm_range_count++;
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normalize();
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if (_dcm_matrix.is_nan() ||
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fabs(_dcm_matrix.c.x) > 10) {
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// normalisation didn't fix the problem! We're
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// in real trouble. All we can do is reset
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//Serial.printf("ERROR: DCM matrix error. _dcm_matrix.c.x=%f\n",
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// _dcm_matrix.c.x);
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SITL_debug("ERROR: DCM matrix error. _dcm_matrix.c.x=%f\n",
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_dcm_matrix.c.x);
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renorm_blowup_count++;
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reset(true);
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}
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}
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}
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// renormalise one vector component of the DCM matrix
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// this will return false if renormalization fails
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bool
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AP_AHRS_DCM::renorm(Vector3f const &a, Vector3f &result)
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{
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float renorm_val;
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// numerical errors will slowly build up over time in DCM,
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// causing inaccuracies. We can keep ahead of those errors
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// using the renormalization technique from the DCM IMU paper
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// (see equations 18 to 21).
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// For APM we don't bother with the taylor expansion
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// optimisation from the paper as on our 2560 CPU the cost of
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// the sqrt() is 44 microseconds, and the small time saving of
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// the taylor expansion is not worth the potential of
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// additional error buildup.
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// Note that we can get significant renormalisation values
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// when we have a larger delta_t due to a glitch eleswhere in
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// APM, such as a I2c timeout or a set of EEPROM writes. While
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// we would like to avoid these if possible, if it does happen
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// we don't want to compound the error by making DCM less
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// accurate.
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renorm_val = 1.0 / a.length();
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// keep the average for reporting
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_renorm_val_sum += renorm_val;
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_renorm_val_count++;
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if (!(renorm_val < 2.0 && renorm_val > 0.5)) {
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// this is larger than it should get - log it as a warning
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renorm_range_count++;
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if (!(renorm_val < 1.0e6 && renorm_val > 1.0e-6)) {
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// we are getting values which are way out of
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// range, we will reset the matrix and hope we
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// can recover our attitude using drift
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// correction before we hit the ground!
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//Serial.printf("ERROR: DCM renormalisation error. renorm_val=%f\n",
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// renorm_val);
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SITL_debug("ERROR: DCM renormalisation error. renorm_val=%f\n",
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renorm_val);
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renorm_blowup_count++;
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return false;
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}
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}
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result = a * renorm_val;
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return true;
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}
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/*************************************************
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Direction Cosine Matrix IMU: Theory
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William Premerlani and Paul Bizard
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Numerical errors will gradually reduce the orthogonality conditions expressed by equation 5
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to approximations rather than identities. In effect, the axes in the two frames of reference no
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longer describe a rigid body. Fortunately, numerical error accumulates very slowly, so it is a
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simple matter to stay ahead of it.
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We call the process of enforcing the orthogonality conditions ÒrenormalizationÓ.
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*/
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void
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AP_AHRS_DCM::normalize(void)
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{
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float error;
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Vector3f t0, t1, t2;
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error = _dcm_matrix.a * _dcm_matrix.b; // eq.18
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t0 = _dcm_matrix.a - (_dcm_matrix.b * (0.5f * error)); // eq.19
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t1 = _dcm_matrix.b - (_dcm_matrix.a * (0.5f * error)); // eq.19
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t2 = t0 % t1; // c= a x b // eq.20
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if (!renorm(t0, _dcm_matrix.a) ||
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!renorm(t1, _dcm_matrix.b) ||
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!renorm(t2, _dcm_matrix.c)) {
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// Our solution is blowing up and we will force back
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// to last euler angles
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reset(true);
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}
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}
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// produce a yaw error value. The returned value is proportional
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// to sin() of the current heading error in earth frame
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float
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AP_AHRS_DCM::yaw_error_compass(void)
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{
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Vector3f mag = Vector3f(_compass->mag_x, _compass->mag_y, _compass->mag_z);
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// get the mag vector in the earth frame
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Vector3f rb = _dcm_matrix * mag;
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rb.normalize();
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if (rb.is_inf()) {
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// not a valid vector
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return 0.0;
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}
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// get the earths magnetic field (only X and Y components needed)
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Vector3f mag_earth = Vector3f(cos(_compass->get_declination()),
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sin(_compass->get_declination()), 0);
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// calculate the error term in earth frame
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Vector3f error = rb % mag_earth;
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return error.z;
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}
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// produce a yaw error value using the GPS. The returned value is proportional
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// to sin() of the current heading error in earth frame
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float
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AP_AHRS_DCM::yaw_error_gps(void)
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{
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return sin(ToRad(_gps->ground_course * 0.01) - yaw);
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}
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// yaw drift correction using the compass or GPS
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// this function prodoces the _omega_yaw_P vector, and also
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// contributes to the _omega_I.z long term yaw drift estimate
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void
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AP_AHRS_DCM::drift_correction_yaw(float deltat)
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{
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bool new_value = false;
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float yaw_error;
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float yaw_deltat;
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if (_compass && _compass->use_for_yaw()) {
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if (_compass->last_update != _compass_last_update) {
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yaw_deltat = (_compass->last_update - _compass_last_update) * 1.0e-6;
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_compass_last_update = _compass->last_update;
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if (!_have_initial_yaw) {
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float heading = _compass->calculate_heading(_dcm_matrix);
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_dcm_matrix.from_euler(roll, pitch, heading);
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_omega_yaw_P.zero();
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_have_initial_yaw = true;
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}
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new_value = true;
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yaw_error = yaw_error_compass();
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}
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} else if (_gps && _gps->status() == GPS::GPS_OK) {
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if (_gps->last_fix_time != _gps_last_update &&
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_gps->ground_speed >= GPS_SPEED_MIN) {
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yaw_deltat = (_gps->last_fix_time - _gps_last_update) * 1.0e-3;
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_gps_last_update = _gps->last_fix_time;
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if (!_have_initial_yaw) {
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_dcm_matrix.from_euler(roll, pitch, ToRad(_gps->ground_course*0.01));
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_omega_yaw_P.zero();
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_have_initial_yaw = true;
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}
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new_value = true;
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yaw_error = yaw_error_gps();
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}
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}
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if (!new_value) {
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// we don't have any new yaw information
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// slowly decay _omega_yaw_P to cope with loss
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// of our yaw source
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_omega_yaw_P.z *= 0.97;
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return;
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}
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// the yaw error is a vector in earth frame
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Vector3f error = Vector3f(0,0, yaw_error);
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// convert the error vector to body frame
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error = _dcm_matrix.mul_transpose(error);
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// update the proportional control to drag the
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// yaw back to the right value
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_omega_yaw_P = error * _kp_yaw.get();
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// don't update the drift term if we lost the yaw reference
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// for more than 2 seconds
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if (yaw_deltat < 2.0) {
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// also add to the I term
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_omega_I_sum.z += error.z * _ki_yaw * yaw_deltat;
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}
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_error_yaw_sum += fabs(yaw_error);
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_error_yaw_count++;
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}
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// perform drift correction. This function aims to update _omega_P and
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// _omega_I with our best estimate of the short term and long term
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// gyro error. The _omega_P value is what pulls our attitude solution
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// back towards the reference vector quickly. The _omega_I term is an
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// attempt to learn the long term drift rate of the gyros.
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//
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// This drift correction implementation is based on a paper
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// by Bill Premerlani from here:
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// http://gentlenav.googlecode.com/files/RollPitchDriftCompensation.pdf
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void
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AP_AHRS_DCM::drift_correction(float deltat)
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{
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Vector3f error;
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Vector3f velocity;
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uint32_t last_correction_time;
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// perform yaw drift correction if we have a new yaw reference
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// vector
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drift_correction_yaw(deltat);
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// integrate the accel vector in the earth frame between GPS readings
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_ra_sum += _dcm_matrix * (_accel_vector * deltat);
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// keep a sum of the deltat values, so we know how much time
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// we have integrated over
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_ra_deltat += deltat;
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if (_gps == NULL || _gps->status() != GPS::GPS_OK) {
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// no GPS, or no lock. We assume zero velocity. This at
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// least means we can cope with gyro drift while sitting
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// on a bench with no GPS lock
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if (_ra_deltat < 0.1) {
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// not enough time has accumulated
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return;
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}
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velocity.zero();
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_last_velocity.zero();
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last_correction_time = millis();
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} else {
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if (_gps->last_fix_time == _ra_sum_start) {
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// we don't have a new GPS fix - nothing more to do
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return;
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}
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velocity = Vector3f(_gps->velocity_north(), _gps->velocity_east(), 0);
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if (_barometer != NULL) {
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// Z velocity is down
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velocity.z = - _barometer->get_climb_rate();
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}
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last_correction_time = _gps->last_fix_time;
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}
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// see if this is our first time through - in which case we
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// just setup the start times and return
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if (_ra_sum_start == 0) {
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_ra_sum_start = last_correction_time;
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_last_velocity = velocity;
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return;
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}
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// get the corrected acceleration vector in earth frame. Units
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// are m/s/s
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Vector3f ge;
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float v_scale = 1.0/(_ra_deltat*_gravity);
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ge = Vector3f(0, 0, -1.0) + ((velocity - _last_velocity) * v_scale);
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// calculate the error term in earth frame.
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ge.normalize();
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_ra_sum.normalize();
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if (_ra_sum.is_inf() || ge.is_inf()) {
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// the _ra_sum length is zero - we are falling with
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// no apparent gravity. This gives us no information
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// about which way up we are, so treat the error as zero
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error = Vector3f(0,0,0);
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} else {
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error = _ra_sum % ge;
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}
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_error_rp_sum += error.length();
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_error_rp_count++;
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// convert the error term to body frame
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error = _dcm_matrix.mul_transpose(error);
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// we now want to calculate _omega_P and _omega_I. The
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// _omega_P value is what drags us quickly to the
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// accelerometer reading.
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_omega_P = error * _kp;
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// accumulate some integrator error
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_omega_I_sum += error * _ki * _ra_deltat;
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_omega_I_sum_time += _ra_deltat;
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if (_omega_I_sum_time >= 5) {
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// limit the rate of change of omega_I to the hardware
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// reported maximum gyro drift rate. This ensures that
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// short term errors don't cause a buildup of omega_I
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// beyond the physical limits of the device
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float change_limit = _gyro_drift_limit * _omega_I_sum_time;
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_omega_I_sum.x = constrain(_omega_I_sum.x, -change_limit, change_limit);
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_omega_I_sum.y = constrain(_omega_I_sum.y, -change_limit, change_limit);
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_omega_I_sum.z = constrain(_omega_I_sum.z, -change_limit, change_limit);
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_omega_I += _omega_I_sum;
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_omega_I_sum.zero();
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_omega_I_sum_time = 0;
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}
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// zero our accumulator ready for the next GPS step
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_ra_sum.zero();
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_ra_deltat = 0;
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_ra_sum_start = last_correction_time;
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// remember the velocity for next time
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_last_velocity = velocity;
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}
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// calculate the euler angles which will be used for high level
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// navigation control
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void
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AP_AHRS_DCM::euler_angles(void)
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{
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_dcm_matrix.to_euler(&roll, &pitch, &yaw);
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roll_sensor = degrees(roll) * 100;
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pitch_sensor = degrees(pitch) * 100;
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yaw_sensor = degrees(yaw) * 100;
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if (yaw_sensor < 0)
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yaw_sensor += 36000;
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}
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/* reporting of DCM state for MAVLink */
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// average error_roll_pitch since last call
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float AP_AHRS_DCM::get_error_rp(void)
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{
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if (_error_rp_count == 0) {
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// this happens when telemetry is setup on two
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// serial ports
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return _error_rp_last;
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}
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_error_rp_last = _error_rp_sum / _error_rp_count;
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_error_rp_sum = 0;
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_error_rp_count = 0;
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return _error_rp_last;
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}
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// average error_yaw since last call
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float AP_AHRS_DCM::get_error_yaw(void)
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{
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if (_error_yaw_count == 0) {
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// this happens when telemetry is setup on two
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// serial ports
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return _error_yaw_last;
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}
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_error_yaw_last = _error_yaw_sum / _error_yaw_count;
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_error_yaw_sum = 0;
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_error_yaw_count = 0;
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return _error_yaw_last;
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}
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