mirror of https://github.com/ArduPilot/ardupilot
922 lines
32 KiB
C++
922 lines
32 KiB
C++
/*
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This program is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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/*
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* The intention of a magnetometer in a compass application is to measure
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* Earth's magnetic field. Measurements other than those of Earth's magnetic
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* field are considered errors. This algorithm computes a set of correction
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* parameters that null out errors from various sources:
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*
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* - Sensor bias error
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* - "Hard iron" error caused by materials fixed to the vehicle body that
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* produce static magnetic fields.
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* - Sensor scale-factor error
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* - Sensor cross-axis sensitivity
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* - "Soft iron" error caused by materials fixed to the vehicle body that
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* distort magnetic fields.
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*
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* This is done by taking a set of samples that are assumed to be the product
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* of rotation in earth's magnetic field and fitting an offset ellipsoid to
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* them, determining the correction to be applied to adjust the samples into an
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* origin-centered sphere.
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*
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* The state machine of this library is described entirely by the
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* compass_cal_status_t enum, and all state transitions are managed by the
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* set_status function. Normally, the library is in the NOT_STARTED state. When
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* the start function is called, the state transitions to WAITING_TO_START,
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* until two conditions are met: the delay as elapsed, and the memory for the
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* sample buffer has been successfully allocated.
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* Once these conditions are met, the state transitions to RUNNING_STEP_ONE, and
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* samples are collected via calls to the new_sample function. These samples are
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* accepted or rejected based on distance to the nearest sample. The samples are
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* assumed to cover the surface of a sphere, and the radius of that sphere is
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* initialized to a conservative value. Based on a circle-packing pattern, the
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* minimum distance is set such that some percentage of the surface of that
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* sphere must be covered by samples.
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*
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* Once the sample buffer is full, a sphere fitting algorithm is run, which
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* computes a new sphere radius. The sample buffer is thinned of samples which
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* no longer meet the acceptance criteria, and the state transitions to
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* RUNNING_STEP_TWO. Samples continue to be collected until the buffer is full
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* again, the full ellipsoid fit is run, and the state transitions to either
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* SUCCESS or FAILED.
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*
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* The fitting algorithm used is Levenberg-Marquardt. See also:
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* http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm
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*/
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#include "CompassCalibrator.h"
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#include <AP_HAL/AP_HAL.h>
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#include <AP_Math/AP_GeodesicGrid.h>
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#include <AP_AHRS/AP_AHRS.h>
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#include <GCS_MAVLink/GCS.h>
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extern const AP_HAL::HAL& hal;
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////////////////////////////////////////////////////////////
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///////////////////// PUBLIC INTERFACE /////////////////////
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////////////////////////////////////////////////////////////
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CompassCalibrator::CompassCalibrator():
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_tolerance(COMPASS_CAL_DEFAULT_TOLERANCE),
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_sample_buffer(nullptr)
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{
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stop();
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}
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void CompassCalibrator::stop()
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{
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set_status(COMPASS_CAL_NOT_STARTED);
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}
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void CompassCalibrator::set_orientation(enum Rotation orientation, bool is_external, bool fix_orientation)
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{
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_check_orientation = true;
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_orientation = orientation;
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_orig_orientation = orientation;
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_is_external = is_external;
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_fix_orientation = fix_orientation;
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}
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void CompassCalibrator::start(bool retry, float delay, uint16_t offset_max, uint8_t compass_idx)
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{
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if (running()) {
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return;
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}
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_offset_max = offset_max;
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_attempt = 1;
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_retry = retry;
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_delay_start_sec = delay;
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_start_time_ms = AP_HAL::millis();
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_compass_idx = compass_idx;
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set_status(COMPASS_CAL_WAITING_TO_START);
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}
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void CompassCalibrator::get_calibration(Vector3f &offsets, Vector3f &diagonals, Vector3f &offdiagonals)
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{
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if (_status != COMPASS_CAL_SUCCESS) {
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return;
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}
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offsets = _params.offset;
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diagonals = _params.diag;
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offdiagonals = _params.offdiag;
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}
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float CompassCalibrator::get_completion_percent() const
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{
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// first sampling step is 1/3rd of the progress bar
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// never return more than 99% unless _status is COMPASS_CAL_SUCCESS
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switch (_status) {
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case COMPASS_CAL_NOT_STARTED:
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case COMPASS_CAL_WAITING_TO_START:
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return 0.0f;
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case COMPASS_CAL_RUNNING_STEP_ONE:
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return 33.3f * _samples_collected/COMPASS_CAL_NUM_SAMPLES;
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case COMPASS_CAL_RUNNING_STEP_TWO:
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return 33.3f + 65.7f*((float)(_samples_collected-_samples_thinned)/(COMPASS_CAL_NUM_SAMPLES-_samples_thinned));
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case COMPASS_CAL_SUCCESS:
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return 100.0f;
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case COMPASS_CAL_FAILED:
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case COMPASS_CAL_BAD_ORIENTATION:
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default:
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return 0.0f;
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};
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}
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// update completion mask based on latest sample
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// used to ensure we have collected samples in all directions
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void CompassCalibrator::update_completion_mask(const Vector3f& v)
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{
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Matrix3f softiron {
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_params.diag.x, _params.offdiag.x, _params.offdiag.y,
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_params.offdiag.x, _params.diag.y, _params.offdiag.z,
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_params.offdiag.y, _params.offdiag.z, _params.diag.z
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};
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Vector3f corrected = softiron * (v + _params.offset);
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int section = AP_GeodesicGrid::section(corrected, true);
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if (section < 0) {
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return;
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}
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_completion_mask[section / 8] |= 1 << (section % 8);
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}
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// reset and updated the completion mask using all samples in the sample buffer
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void CompassCalibrator::update_completion_mask()
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{
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memset(_completion_mask, 0, sizeof(_completion_mask));
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for (int i = 0; i < _samples_collected; i++) {
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update_completion_mask(_sample_buffer[i].get());
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}
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}
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bool CompassCalibrator::check_for_timeout()
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{
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uint32_t tnow = AP_HAL::millis();
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if (running() && tnow - _last_sample_ms > 1000) {
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_retry = false;
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set_status(COMPASS_CAL_FAILED);
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return true;
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}
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return false;
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}
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void CompassCalibrator::new_sample(const Vector3f& sample)
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{
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_last_sample_ms = AP_HAL::millis();
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if (_status == COMPASS_CAL_WAITING_TO_START) {
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set_status(COMPASS_CAL_RUNNING_STEP_ONE);
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}
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if (running() && _samples_collected < COMPASS_CAL_NUM_SAMPLES && accept_sample(sample)) {
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update_completion_mask(sample);
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_sample_buffer[_samples_collected].set(sample);
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_sample_buffer[_samples_collected].att.set_from_ahrs();
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_samples_collected++;
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}
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}
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void CompassCalibrator::update(bool &failure)
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{
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failure = false;
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// collect the minimum number of samples
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if (!fitting()) {
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return;
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}
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if (_status == COMPASS_CAL_RUNNING_STEP_ONE) {
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if (_fit_step >= 10) {
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if (is_equal(_fitness, _initial_fitness) || isnan(_fitness)) { // if true, means that fitness is diverging instead of converging
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set_status(COMPASS_CAL_FAILED);
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failure = true;
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}
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set_status(COMPASS_CAL_RUNNING_STEP_TWO);
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} else {
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if (_fit_step == 0) {
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calc_initial_offset();
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}
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run_sphere_fit();
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_fit_step++;
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}
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} else if (_status == COMPASS_CAL_RUNNING_STEP_TWO) {
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if (_fit_step >= 35) {
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if (fit_acceptable() && calculate_orientation()) {
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set_status(COMPASS_CAL_SUCCESS);
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} else {
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set_status(COMPASS_CAL_FAILED);
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failure = true;
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}
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} else if (_fit_step < 15) {
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run_sphere_fit();
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_fit_step++;
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} else {
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run_ellipsoid_fit();
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_fit_step++;
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}
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}
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}
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/////////////////////////////////////////////////////////////
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////////////////////// PRIVATE METHODS //////////////////////
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/////////////////////////////////////////////////////////////
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bool CompassCalibrator::running() const
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{
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return _status == COMPASS_CAL_RUNNING_STEP_ONE || _status == COMPASS_CAL_RUNNING_STEP_TWO;
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}
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bool CompassCalibrator::fitting() const
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{
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return running() && (_samples_collected == COMPASS_CAL_NUM_SAMPLES);
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}
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// initialize fitness before starting a fit
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void CompassCalibrator::initialize_fit()
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{
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if (_samples_collected != 0) {
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_fitness = calc_mean_squared_residuals(_params);
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} else {
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_fitness = 1.0e30f;
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}
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_initial_fitness = _fitness;
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_sphere_lambda = 1.0f;
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_ellipsoid_lambda = 1.0f;
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_fit_step = 0;
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}
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void CompassCalibrator::reset_state()
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{
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_samples_collected = 0;
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_samples_thinned = 0;
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_params.radius = 200;
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_params.offset.zero();
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_params.diag = Vector3f(1.0f,1.0f,1.0f);
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_params.offdiag.zero();
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memset(_completion_mask, 0, sizeof(_completion_mask));
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initialize_fit();
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}
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bool CompassCalibrator::set_status(compass_cal_status_t status)
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{
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if (status != COMPASS_CAL_NOT_STARTED && _status == status) {
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return true;
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}
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switch (status) {
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case COMPASS_CAL_NOT_STARTED:
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reset_state();
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_status = COMPASS_CAL_NOT_STARTED;
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if (_sample_buffer != nullptr) {
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free(_sample_buffer);
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_sample_buffer = nullptr;
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}
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return true;
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case COMPASS_CAL_WAITING_TO_START:
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reset_state();
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_status = COMPASS_CAL_WAITING_TO_START;
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set_status(COMPASS_CAL_RUNNING_STEP_ONE);
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return true;
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case COMPASS_CAL_RUNNING_STEP_ONE:
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if (_status != COMPASS_CAL_WAITING_TO_START) {
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return false;
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}
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// on first attempt delay start if requested by caller
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if (_attempt == 1 && (AP_HAL::millis()-_start_time_ms)*1.0e-3f < _delay_start_sec) {
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return false;
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}
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if (_sample_buffer == nullptr) {
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_sample_buffer = (CompassSample*)calloc(COMPASS_CAL_NUM_SAMPLES, sizeof(CompassSample));
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}
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if (_sample_buffer != nullptr) {
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initialize_fit();
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_status = COMPASS_CAL_RUNNING_STEP_ONE;
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return true;
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}
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return false;
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case COMPASS_CAL_RUNNING_STEP_TWO:
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if (_status != COMPASS_CAL_RUNNING_STEP_ONE) {
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return false;
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}
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thin_samples();
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initialize_fit();
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_status = COMPASS_CAL_RUNNING_STEP_TWO;
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return true;
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case COMPASS_CAL_SUCCESS:
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if (_status != COMPASS_CAL_RUNNING_STEP_TWO) {
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return false;
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}
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if (_sample_buffer != nullptr) {
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free(_sample_buffer);
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_sample_buffer = nullptr;
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}
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_status = COMPASS_CAL_SUCCESS;
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return true;
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case COMPASS_CAL_FAILED:
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if (_status == COMPASS_CAL_BAD_ORIENTATION) {
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// don't overwrite bad orientation status
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return false;
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}
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FALLTHROUGH;
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case COMPASS_CAL_BAD_ORIENTATION:
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if (_status == COMPASS_CAL_NOT_STARTED) {
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return false;
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}
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if (_retry && set_status(COMPASS_CAL_WAITING_TO_START)) {
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_attempt++;
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return true;
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}
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if (_sample_buffer != nullptr) {
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free(_sample_buffer);
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_sample_buffer = nullptr;
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}
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_status = status;
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return true;
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default:
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return false;
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};
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}
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bool CompassCalibrator::fit_acceptable()
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{
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if (!isnan(_fitness) &&
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_params.radius > 150 && _params.radius < 950 && //Earth's magnetic field strength range: 250-850mG
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fabsf(_params.offset.x) < _offset_max &&
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fabsf(_params.offset.y) < _offset_max &&
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fabsf(_params.offset.z) < _offset_max &&
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_params.diag.x > 0.2f && _params.diag.x < 5.0f &&
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_params.diag.y > 0.2f && _params.diag.y < 5.0f &&
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_params.diag.z > 0.2f && _params.diag.z < 5.0f &&
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fabsf(_params.offdiag.x) < 1.0f && //absolute of sine/cosine output cannot be greater than 1
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fabsf(_params.offdiag.y) < 1.0f &&
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fabsf(_params.offdiag.z) < 1.0f ) {
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return _fitness <= sq(_tolerance);
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}
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return false;
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}
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void CompassCalibrator::thin_samples()
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{
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if (_sample_buffer == nullptr) {
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return;
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}
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_samples_thinned = 0;
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// shuffle the samples http://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle
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// this is so that adjacent samples don't get sequentially eliminated
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for (uint16_t i=_samples_collected-1; i>=1; i--) {
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uint16_t j = get_random16() % (i+1);
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CompassSample temp = _sample_buffer[i];
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_sample_buffer[i] = _sample_buffer[j];
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_sample_buffer[j] = temp;
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}
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for (uint16_t i=0; i < _samples_collected; i++) {
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if (!accept_sample(_sample_buffer[i])) {
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_sample_buffer[i] = _sample_buffer[_samples_collected-1];
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_samples_collected--;
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_samples_thinned++;
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}
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}
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update_completion_mask();
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}
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/*
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* The sample acceptance distance is determined as follows:
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* For any regular polyhedron with triangular faces, the angle theta subtended
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* by two closest points is defined as
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*
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* theta = arccos(cos(A)/(1-cos(A)))
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*
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* Where:
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* A = (4pi/F + pi)/3
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* and
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* F = 2V - 4 is the number of faces for the polyhedron in consideration,
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* which depends on the number of vertices V
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*
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* The above equation was proved after solving for spherical triangular excess
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* and related equations.
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*/
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bool CompassCalibrator::accept_sample(const Vector3f& sample)
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{
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static const uint16_t faces = (2 * COMPASS_CAL_NUM_SAMPLES - 4);
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static const float a = (4.0f * M_PI / (3.0f * faces)) + M_PI / 3.0f;
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static const float theta = 0.5f * acosf(cosf(a) / (1.0f - cosf(a)));
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if (_sample_buffer == nullptr) {
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return false;
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}
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float min_distance = _params.radius * 2*sinf(theta/2);
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for (uint16_t i = 0; i<_samples_collected; i++) {
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float distance = (sample - _sample_buffer[i].get()).length();
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if (distance < min_distance) {
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return false;
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}
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}
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return true;
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}
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bool CompassCalibrator::accept_sample(const CompassSample& sample)
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{
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return accept_sample(sample.get());
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}
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float CompassCalibrator::calc_residual(const Vector3f& sample, const param_t& params) const
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{
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Matrix3f softiron(
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params.diag.x , params.offdiag.x , params.offdiag.y,
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params.offdiag.x , params.diag.y , params.offdiag.z,
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params.offdiag.y , params.offdiag.z , params.diag.z
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);
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return params.radius - (softiron*(sample+params.offset)).length();
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}
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// calc the fitness given a set of parameters (offsets, diagonals, off diagonals)
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float CompassCalibrator::calc_mean_squared_residuals(const param_t& params) const
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{
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if (_sample_buffer == nullptr || _samples_collected == 0) {
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return 1.0e30f;
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}
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float sum = 0.0f;
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for (uint16_t i=0; i < _samples_collected; i++) {
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Vector3f sample = _sample_buffer[i].get();
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float resid = calc_residual(sample, params);
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sum += sq(resid);
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}
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sum /= _samples_collected;
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return sum;
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}
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// calculate initial offsets by simply taking the average values of the samples
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void CompassCalibrator::calc_initial_offset()
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{
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// Set initial offset to the average value of the samples
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_params.offset.zero();
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for (uint16_t k = 0; k < _samples_collected; k++) {
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_params.offset -= _sample_buffer[k].get();
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}
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_params.offset /= _samples_collected;
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}
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void CompassCalibrator::calc_sphere_jacob(const Vector3f& sample, const param_t& params, float* ret) const
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{
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const Vector3f &offset = params.offset;
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const Vector3f &diag = params.diag;
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const Vector3f &offdiag = params.offdiag;
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Matrix3f softiron(
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diag.x , offdiag.x , offdiag.y,
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offdiag.x , diag.y , offdiag.z,
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offdiag.y , offdiag.z , diag.z
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);
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|
|
float A = (diag.x * (sample.x + offset.x)) + (offdiag.x * (sample.y + offset.y)) + (offdiag.y * (sample.z + offset.z));
|
|
float B = (offdiag.x * (sample.x + offset.x)) + (diag.y * (sample.y + offset.y)) + (offdiag.z * (sample.z + offset.z));
|
|
float C = (offdiag.y * (sample.x + offset.x)) + (offdiag.z * (sample.y + offset.y)) + (diag.z * (sample.z + offset.z));
|
|
float length = (softiron*(sample+offset)).length();
|
|
|
|
// 0: partial derivative (radius wrt fitness fn) fn operated on sample
|
|
ret[0] = 1.0f;
|
|
// 1-3: partial derivative (offsets wrt fitness fn) fn operated on sample
|
|
ret[1] = -1.0f * (((diag.x * A) + (offdiag.x * B) + (offdiag.y * C))/length);
|
|
ret[2] = -1.0f * (((offdiag.x * A) + (diag.y * B) + (offdiag.z * C))/length);
|
|
ret[3] = -1.0f * (((offdiag.y * A) + (offdiag.z * B) + (diag.z * C))/length);
|
|
}
|
|
|
|
// run sphere fit to calculate diagonals and offdiagonals
|
|
void CompassCalibrator::run_sphere_fit()
|
|
{
|
|
if (_sample_buffer == nullptr) {
|
|
return;
|
|
}
|
|
|
|
const float lma_damping = 10.0f;
|
|
|
|
// take backup of fitness and parameters so we can determine later if this fit has improved the calibration
|
|
float fitness = _fitness;
|
|
float fit1, fit2;
|
|
param_t fit1_params, fit2_params;
|
|
fit1_params = fit2_params = _params;
|
|
|
|
float JTJ[COMPASS_CAL_NUM_SPHERE_PARAMS*COMPASS_CAL_NUM_SPHERE_PARAMS] = { };
|
|
float JTJ2[COMPASS_CAL_NUM_SPHERE_PARAMS*COMPASS_CAL_NUM_SPHERE_PARAMS] = { };
|
|
float JTFI[COMPASS_CAL_NUM_SPHERE_PARAMS] = { };
|
|
|
|
// Gauss Newton Part common for all kind of extensions including LM
|
|
for (uint16_t k = 0; k<_samples_collected; k++) {
|
|
Vector3f sample = _sample_buffer[k].get();
|
|
|
|
float sphere_jacob[COMPASS_CAL_NUM_SPHERE_PARAMS];
|
|
|
|
calc_sphere_jacob(sample, fit1_params, sphere_jacob);
|
|
|
|
for (uint8_t i = 0;i < COMPASS_CAL_NUM_SPHERE_PARAMS; i++) {
|
|
// compute JTJ
|
|
for (uint8_t j = 0; j < COMPASS_CAL_NUM_SPHERE_PARAMS; j++) {
|
|
JTJ[i*COMPASS_CAL_NUM_SPHERE_PARAMS+j] += sphere_jacob[i] * sphere_jacob[j];
|
|
JTJ2[i*COMPASS_CAL_NUM_SPHERE_PARAMS+j] += sphere_jacob[i] * sphere_jacob[j]; //a backup JTJ for LM
|
|
}
|
|
// compute JTFI
|
|
JTFI[i] += sphere_jacob[i] * calc_residual(sample, fit1_params);
|
|
}
|
|
}
|
|
|
|
//------------------------Levenberg-Marquardt-part-starts-here---------------------------------//
|
|
// refer: http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm#Choice_of_damping_parameter
|
|
for (uint8_t i = 0; i < COMPASS_CAL_NUM_SPHERE_PARAMS; i++) {
|
|
JTJ[i*COMPASS_CAL_NUM_SPHERE_PARAMS+i] += _sphere_lambda;
|
|
JTJ2[i*COMPASS_CAL_NUM_SPHERE_PARAMS+i] += _sphere_lambda/lma_damping;
|
|
}
|
|
|
|
if (!inverse(JTJ, JTJ, 4)) {
|
|
return;
|
|
}
|
|
|
|
if (!inverse(JTJ2, JTJ2, 4)) {
|
|
return;
|
|
}
|
|
|
|
// extract radius, offset, diagonals and offdiagonal parameters
|
|
for (uint8_t row=0; row < COMPASS_CAL_NUM_SPHERE_PARAMS; row++) {
|
|
for (uint8_t col=0; col < COMPASS_CAL_NUM_SPHERE_PARAMS; col++) {
|
|
fit1_params.get_sphere_params()[row] -= JTFI[col] * JTJ[row*COMPASS_CAL_NUM_SPHERE_PARAMS+col];
|
|
fit2_params.get_sphere_params()[row] -= JTFI[col] * JTJ2[row*COMPASS_CAL_NUM_SPHERE_PARAMS+col];
|
|
}
|
|
}
|
|
|
|
// calculate fitness of two possible sets of parameters
|
|
fit1 = calc_mean_squared_residuals(fit1_params);
|
|
fit2 = calc_mean_squared_residuals(fit2_params);
|
|
|
|
// decide which of the two sets of parameters is best and store in fit1_params
|
|
if (fit1 > _fitness && fit2 > _fitness) {
|
|
// if neither set of parameters provided better results, increase lambda
|
|
_sphere_lambda *= lma_damping;
|
|
} else if (fit2 < _fitness && fit2 < fit1) {
|
|
// if fit2 was better we will use it. decrease lambda
|
|
_sphere_lambda /= lma_damping;
|
|
fit1_params = fit2_params;
|
|
fitness = fit2;
|
|
} else if (fit1 < _fitness) {
|
|
fitness = fit1;
|
|
}
|
|
//--------------------Levenberg-Marquardt-part-ends-here--------------------------------//
|
|
|
|
// store new parameters and update fitness
|
|
if (!isnan(fitness) && fitness < _fitness) {
|
|
_fitness = fitness;
|
|
_params = fit1_params;
|
|
update_completion_mask();
|
|
}
|
|
}
|
|
|
|
void CompassCalibrator::calc_ellipsoid_jacob(const Vector3f& sample, const param_t& params, float* ret) const
|
|
{
|
|
const Vector3f &offset = params.offset;
|
|
const Vector3f &diag = params.diag;
|
|
const Vector3f &offdiag = params.offdiag;
|
|
Matrix3f softiron(
|
|
diag.x , offdiag.x , offdiag.y,
|
|
offdiag.x , diag.y , offdiag.z,
|
|
offdiag.y , offdiag.z , diag.z
|
|
);
|
|
|
|
float A = (diag.x * (sample.x + offset.x)) + (offdiag.x * (sample.y + offset.y)) + (offdiag.y * (sample.z + offset.z));
|
|
float B = (offdiag.x * (sample.x + offset.x)) + (diag.y * (sample.y + offset.y)) + (offdiag.z * (sample.z + offset.z));
|
|
float C = (offdiag.y * (sample.x + offset.x)) + (offdiag.z * (sample.y + offset.y)) + (diag.z * (sample.z + offset.z));
|
|
float length = (softiron*(sample+offset)).length();
|
|
|
|
// 0-2: partial derivative (offset wrt fitness fn) fn operated on sample
|
|
ret[0] = -1.0f * (((diag.x * A) + (offdiag.x * B) + (offdiag.y * C))/length);
|
|
ret[1] = -1.0f * (((offdiag.x * A) + (diag.y * B) + (offdiag.z * C))/length);
|
|
ret[2] = -1.0f * (((offdiag.y * A) + (offdiag.z * B) + (diag.z * C))/length);
|
|
// 3-5: partial derivative (diag offset wrt fitness fn) fn operated on sample
|
|
ret[3] = -1.0f * ((sample.x + offset.x) * A)/length;
|
|
ret[4] = -1.0f * ((sample.y + offset.y) * B)/length;
|
|
ret[5] = -1.0f * ((sample.z + offset.z) * C)/length;
|
|
// 6-8: partial derivative (off-diag offset wrt fitness fn) fn operated on sample
|
|
ret[6] = -1.0f * (((sample.y + offset.y) * A) + ((sample.x + offset.x) * B))/length;
|
|
ret[7] = -1.0f * (((sample.z + offset.z) * A) + ((sample.x + offset.x) * C))/length;
|
|
ret[8] = -1.0f * (((sample.z + offset.z) * B) + ((sample.y + offset.y) * C))/length;
|
|
}
|
|
|
|
void CompassCalibrator::run_ellipsoid_fit()
|
|
{
|
|
if (_sample_buffer == nullptr) {
|
|
return;
|
|
}
|
|
|
|
const float lma_damping = 10.0f;
|
|
|
|
// take backup of fitness and parameters so we can determine later if this fit has improved the calibration
|
|
float fitness = _fitness;
|
|
float fit1, fit2;
|
|
param_t fit1_params, fit2_params;
|
|
fit1_params = fit2_params = _params;
|
|
|
|
float JTJ[COMPASS_CAL_NUM_ELLIPSOID_PARAMS*COMPASS_CAL_NUM_ELLIPSOID_PARAMS] = { };
|
|
float JTJ2[COMPASS_CAL_NUM_ELLIPSOID_PARAMS*COMPASS_CAL_NUM_ELLIPSOID_PARAMS] = { };
|
|
float JTFI[COMPASS_CAL_NUM_ELLIPSOID_PARAMS] = { };
|
|
|
|
// Gauss Newton Part common for all kind of extensions including LM
|
|
for (uint16_t k = 0; k<_samples_collected; k++) {
|
|
Vector3f sample = _sample_buffer[k].get();
|
|
|
|
float ellipsoid_jacob[COMPASS_CAL_NUM_ELLIPSOID_PARAMS];
|
|
|
|
calc_ellipsoid_jacob(sample, fit1_params, ellipsoid_jacob);
|
|
|
|
for (uint8_t i = 0;i < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; i++) {
|
|
// compute JTJ
|
|
for (uint8_t j = 0; j < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; j++) {
|
|
JTJ [i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+j] += ellipsoid_jacob[i] * ellipsoid_jacob[j];
|
|
JTJ2[i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+j] += ellipsoid_jacob[i] * ellipsoid_jacob[j];
|
|
}
|
|
// compute JTFI
|
|
JTFI[i] += ellipsoid_jacob[i] * calc_residual(sample, fit1_params);
|
|
}
|
|
}
|
|
|
|
//------------------------Levenberg-Marquardt-part-starts-here---------------------------------//
|
|
//refer: http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm#Choice_of_damping_parameter
|
|
for (uint8_t i = 0; i < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; i++) {
|
|
JTJ[i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+i] += _ellipsoid_lambda;
|
|
JTJ2[i*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+i] += _ellipsoid_lambda/lma_damping;
|
|
}
|
|
|
|
if (!inverse(JTJ, JTJ, 9)) {
|
|
return;
|
|
}
|
|
|
|
if (!inverse(JTJ2, JTJ2, 9)) {
|
|
return;
|
|
}
|
|
|
|
// extract radius, offset, diagonals and offdiagonal parameters
|
|
for (uint8_t row=0; row < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; row++) {
|
|
for (uint8_t col=0; col < COMPASS_CAL_NUM_ELLIPSOID_PARAMS; col++) {
|
|
fit1_params.get_ellipsoid_params()[row] -= JTFI[col] * JTJ[row*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+col];
|
|
fit2_params.get_ellipsoid_params()[row] -= JTFI[col] * JTJ2[row*COMPASS_CAL_NUM_ELLIPSOID_PARAMS+col];
|
|
}
|
|
}
|
|
|
|
// calculate fitness of two possible sets of parameters
|
|
fit1 = calc_mean_squared_residuals(fit1_params);
|
|
fit2 = calc_mean_squared_residuals(fit2_params);
|
|
|
|
// decide which of the two sets of parameters is best and store in fit1_params
|
|
if (fit1 > _fitness && fit2 > _fitness) {
|
|
// if neither set of parameters provided better results, increase lambda
|
|
_ellipsoid_lambda *= lma_damping;
|
|
} else if (fit2 < _fitness && fit2 < fit1) {
|
|
// if fit2 was better we will use it. decrease lambda
|
|
_ellipsoid_lambda /= lma_damping;
|
|
fit1_params = fit2_params;
|
|
fitness = fit2;
|
|
} else if (fit1 < _fitness) {
|
|
fitness = fit1;
|
|
}
|
|
//--------------------Levenberg-part-ends-here--------------------------------//
|
|
|
|
// store new parameters and update fitness
|
|
if (fitness < _fitness) {
|
|
_fitness = fitness;
|
|
_params = fit1_params;
|
|
update_completion_mask();
|
|
}
|
|
}
|
|
|
|
|
|
//////////////////////////////////////////////////////////
|
|
//////////// CompassSample public interface //////////////
|
|
//////////////////////////////////////////////////////////
|
|
|
|
#define COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(__X) ((int16_t)constrain_float(roundf(__X*8.0f), INT16_MIN, INT16_MAX))
|
|
#define COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(__X) (__X/8.0f)
|
|
|
|
Vector3f CompassCalibrator::CompassSample::get() const
|
|
{
|
|
return Vector3f(COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(x),
|
|
COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(y),
|
|
COMPASS_CAL_SAMPLE_SCALE_TO_FLOAT(z));
|
|
}
|
|
|
|
void CompassCalibrator::CompassSample::set(const Vector3f &in)
|
|
{
|
|
x = COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(in.x);
|
|
y = COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(in.y);
|
|
z = COMPASS_CAL_SAMPLE_SCALE_TO_FIXED(in.z);
|
|
}
|
|
|
|
void CompassCalibrator::AttitudeSample::set_from_ahrs(void)
|
|
{
|
|
const Matrix3f &dcm = AP::ahrs().get_DCM_rotation_body_to_ned();
|
|
float roll_rad, pitch_rad, yaw_rad;
|
|
dcm.to_euler(&roll_rad, &pitch_rad, &yaw_rad);
|
|
roll = constrain_int16(127 * (roll_rad / M_PI), -127, 127);
|
|
pitch = constrain_int16(127 * (pitch_rad / M_PI_2), -127, 127);
|
|
yaw = constrain_int16(127 * (yaw_rad / M_PI), -127, 127);
|
|
}
|
|
|
|
Matrix3f CompassCalibrator::AttitudeSample::get_rotmat(void)
|
|
{
|
|
float roll_rad, pitch_rad, yaw_rad;
|
|
roll_rad = roll * (M_PI / 127);
|
|
pitch_rad = pitch * (M_PI_2 / 127);
|
|
yaw_rad = yaw * (M_PI / 127);
|
|
Matrix3f dcm;
|
|
dcm.from_euler(roll_rad, pitch_rad, yaw_rad);
|
|
return dcm;
|
|
}
|
|
|
|
/*
|
|
calculate the implied earth field for a compass sample and compass
|
|
rotation. This is used to check for consistency between
|
|
samples.
|
|
|
|
If the orientation is correct then when rotated the same (or
|
|
similar) earth field should be given for all samples.
|
|
|
|
Note that this earth field uses an arbitrary north reference, so it
|
|
may not match the true earth field.
|
|
*/
|
|
Vector3f CompassCalibrator::calculate_earth_field(CompassSample &sample, enum Rotation r)
|
|
{
|
|
Vector3f v = sample.get();
|
|
|
|
// convert the sample back to sensor frame
|
|
v.rotate_inverse(_orientation);
|
|
|
|
// rotate to body frame for this rotation
|
|
v.rotate(r);
|
|
|
|
// apply offsets, rotating them for the orientation we are testing
|
|
Vector3f rot_offsets = _params.offset;
|
|
rot_offsets.rotate_inverse(_orientation);
|
|
|
|
rot_offsets.rotate(r);
|
|
|
|
v += rot_offsets;
|
|
|
|
// rotate the sample from body frame back to earth frame
|
|
Matrix3f rot = sample.att.get_rotmat();
|
|
|
|
Vector3f efield = rot * v;
|
|
|
|
// earth field is the mag sample in earth frame
|
|
return efield;
|
|
}
|
|
|
|
/*
|
|
calculate compass orientation using the attitude estimate associated
|
|
with each sample, and fix orientation on external compasses if
|
|
the feature is enabled
|
|
*/
|
|
bool CompassCalibrator::calculate_orientation(void)
|
|
{
|
|
if (!_check_orientation) {
|
|
// we are not checking orientation
|
|
return true;
|
|
}
|
|
|
|
// this function is very slow
|
|
EXPECT_DELAY_MS(1000);
|
|
|
|
float variance[ROTATION_MAX] {};
|
|
|
|
for (enum Rotation r = ROTATION_NONE; r<ROTATION_MAX; r = (enum Rotation)(r+1)) {
|
|
// calculate the average implied earth field across all samples
|
|
Vector3f total_ef {};
|
|
for (uint32_t i=0; i<_samples_collected; i++) {
|
|
Vector3f efield = calculate_earth_field(_sample_buffer[i], r);
|
|
total_ef += efield;
|
|
}
|
|
Vector3f avg_efield = total_ef / _samples_collected;
|
|
|
|
// now calculate the square error for this rotation against the average earth field
|
|
for (uint32_t i=0; i<_samples_collected; i++) {
|
|
Vector3f efield = calculate_earth_field(_sample_buffer[i], r);
|
|
float err = (efield - avg_efield).length_squared();
|
|
// divide by number of samples collected to get the variance
|
|
variance[r] += err / _samples_collected;
|
|
}
|
|
}
|
|
|
|
// find the rotation with the lowest variance
|
|
enum Rotation besti = ROTATION_NONE;
|
|
float bestv = variance[0];
|
|
for (enum Rotation r = ROTATION_NONE; r<ROTATION_MAX; r = (enum Rotation)(r+1)) {
|
|
if (variance[r] < bestv) {
|
|
bestv = variance[r];
|
|
besti = r;
|
|
}
|
|
}
|
|
|
|
// consider this a pass if the best orientation is 2x better
|
|
// variance than 2nd best
|
|
const float variance_threshold = 2.0;
|
|
|
|
float second_best = besti==ROTATION_NONE?variance[1]:variance[0];
|
|
enum Rotation besti2 = ROTATION_NONE;
|
|
for (enum Rotation r = ROTATION_NONE; r<ROTATION_MAX; r = (enum Rotation)(r+1)) {
|
|
if (!rotation_equal(besti, r)) {
|
|
if (variance[r] < second_best) {
|
|
second_best = variance[r];
|
|
besti2 = r;
|
|
}
|
|
}
|
|
}
|
|
|
|
_orientation_confidence = second_best/bestv;
|
|
|
|
bool pass;
|
|
if (besti == _orientation) {
|
|
// if the orientation matched then allow for a low threshold
|
|
pass = true;
|
|
} else {
|
|
pass = _orientation_confidence > variance_threshold;
|
|
}
|
|
if (!pass) {
|
|
gcs().send_text(MAV_SEVERITY_CRITICAL, "Mag(%u) bad orientation: %u/%u %.1f", _compass_idx,
|
|
besti, besti2, (double)_orientation_confidence);
|
|
} else if (besti == _orientation) {
|
|
// no orientation change
|
|
gcs().send_text(MAV_SEVERITY_INFO, "Mag(%u) good orientation: %u %.1f", _compass_idx, besti, (double)_orientation_confidence);
|
|
} else if (!_is_external || !_fix_orientation) {
|
|
gcs().send_text(MAV_SEVERITY_CRITICAL, "Mag(%u) internal bad orientation: %u %.1f", _compass_idx, besti, (double)_orientation_confidence);
|
|
} else {
|
|
gcs().send_text(MAV_SEVERITY_INFO, "Mag(%u) new orientation: %u was %u %.1f", _compass_idx, besti, _orientation, (double)_orientation_confidence);
|
|
}
|
|
|
|
if (!pass) {
|
|
set_status(COMPASS_CAL_BAD_ORIENTATION);
|
|
return false;
|
|
}
|
|
|
|
if (_orientation == besti) {
|
|
// no orientation change
|
|
return true;
|
|
}
|
|
|
|
if (!_is_external || !_fix_orientation) {
|
|
// we won't change the orientation, but we set _orientation
|
|
// for reporting purposes
|
|
_orientation = besti;
|
|
set_status(COMPASS_CAL_BAD_ORIENTATION);
|
|
return false;
|
|
}
|
|
|
|
// correct the offsets for the new orientation
|
|
Vector3f rot_offsets = _params.offset;
|
|
rot_offsets.rotate_inverse(_orientation);
|
|
rot_offsets.rotate(besti);
|
|
_params.offset = rot_offsets;
|
|
|
|
// rotate the samples for the new orientation
|
|
for (uint32_t i=0; i<_samples_collected; i++) {
|
|
Vector3f s = _sample_buffer[i].get();
|
|
s.rotate_inverse(_orientation);
|
|
s.rotate(besti);
|
|
_sample_buffer[i].set(s);
|
|
}
|
|
|
|
_orientation = besti;
|
|
|
|
// re-run the fit to get the diagonals and off-diagonals for the
|
|
// new orientation
|
|
initialize_fit();
|
|
run_sphere_fit();
|
|
run_ellipsoid_fit();
|
|
|
|
return fit_acceptable();
|
|
}
|