forked from Archive/PX4-Autopilot
526 lines
14 KiB
C++
526 lines
14 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2015 Estimation and Control Library (ECL). All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* 3. Neither the name ECL nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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****************************************************************************/
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/**
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* @file ekf.cpp
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* Core functions for ekf attitude and position estimator.
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*
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* @author Roman Bast <bapstroman@gmail.com>
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*
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*/
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#include "ekf.h"
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#include <drivers/drv_hrt.h>
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Ekf::Ekf():
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_control_status{},
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_filter_initialised(false),
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_earth_rate_initialised(false),
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_fuse_height(false),
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_fuse_pos(false),
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_fuse_hor_vel(false),
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_fuse_vert_vel(false),
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_time_last_fake_gps(0),
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_time_last_pos_fuse(0),
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_time_last_vel_fuse(0),
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_time_last_hgt_fuse(0),
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_time_last_of_fuse(0),
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_vel_pos_innov{},
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_mag_innov{},
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_heading_innov{},
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_vel_pos_innov_var{},
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_mag_innov_var{},
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_heading_innov_var{}
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{
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_earth_rate_NED.setZero();
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_R_prev = matrix::Dcm<float>();
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_delta_angle_corr.setZero();
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_delta_vel_corr.setZero();
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_vel_corr.setZero();
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_last_known_posNE.setZero();
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}
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Ekf::~Ekf()
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{
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}
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bool Ekf::init(uint64_t timestamp)
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{
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bool ret = initialise_interface(timestamp);
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_state.ang_error.setZero();
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_state.vel.setZero();
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_state.pos.setZero();
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_state.gyro_bias.setZero();
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_state.gyro_scale(0) = 1.0f;
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_state.gyro_scale(1) = 1.0f;
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_state.gyro_scale(2) = 1.0f;
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_state.accel_z_bias = 0.0f;
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_state.mag_I.setZero();
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_state.mag_B.setZero();
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_state.wind_vel.setZero();
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_state.quat_nominal.setZero();
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_state.quat_nominal(0) = 1.0f;
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_output_new.vel.setZero();
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_output_new.pos.setZero();
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_output_new.quat_nominal = matrix::Quaternion<float>();
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_imu_down_sampled.delta_ang.setZero();
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_imu_down_sampled.delta_vel.setZero();
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_imu_down_sampled.delta_ang_dt = 0.0f;
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_imu_down_sampled.delta_vel_dt = 0.0f;
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_imu_down_sampled.time_us = timestamp;
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_q_down_sampled(0) = 1.0f;
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_q_down_sampled(1) = 0.0f;
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_q_down_sampled(2) = 0.0f;
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_q_down_sampled(3) = 0.0f;
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_imu_updated = false;
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_NED_origin_initialised = false;
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_gps_speed_valid = false;
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_mag_healthy = false;
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return ret;
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}
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bool Ekf::update()
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{
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bool ret = false; // indicates if there has been an update
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if (!_filter_initialised) {
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_filter_initialised = initialiseFilter();
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if (!_filter_initialised) {
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return false;
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}
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}
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//printStates();
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//printStatesFast();
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// prediction
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if (_imu_updated) {
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ret = true;
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predictState();
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predictCovariance();
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}
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// control logic
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controlFusionModes();
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// measurement updates
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// Fuse magnetometer data using the selected fuson method and only if angular alignment is complete
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if (_mag_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_mag_sample_delayed)) {
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if (_control_status.flags.mag_3D && _control_status.flags.angle_align) {
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fuseMag();
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if (_control_status.flags.mag_dec) {
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fuseDeclination();
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}
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} else if (_control_status.flags.mag_hdg && _control_status.flags.angle_align) {
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fuseHeading();
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}
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}
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if (_baro_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_baro_sample_delayed)) {
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_fuse_height = true;
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}
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// If we are using GPS aiding and data has fallen behind the fusion time horizon then fuse it
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// if we aren't doing any aiding, fake GPS measurements at the last known position to constrain drift
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// Coincide fake measurements with baro data for efficiency with a minimum fusion rate of 5Hz
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if (_gps_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_gps_sample_delayed) && _control_status.flags.gps) {
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_fuse_pos = true;
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_fuse_vert_vel = true;
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_fuse_hor_vel = true;
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} else if (!_control_status.flags.gps && !_control_status.flags.opt_flow
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&& ((_time_last_imu - _time_last_fake_gps > 2e5) || _fuse_height)) {
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_fuse_pos = true;
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_gps_sample_delayed.pos(0) = _last_known_posNE(0);
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_gps_sample_delayed.pos(1) = _last_known_posNE(1);
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_time_last_fake_gps = _time_last_imu;
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}
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if (_fuse_height || _fuse_pos || _fuse_hor_vel || _fuse_vert_vel) {
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fuseVelPosHeight();
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_fuse_hor_vel = _fuse_vert_vel = _fuse_pos = _fuse_height = false;
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}
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if (_range_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_range_sample_delayed)) {
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fuseRange();
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}
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if (_airspeed_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_airspeed_sample_delayed)) {
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fuseAirspeed();
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}
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calculateOutputStates();
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return ret;
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}
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bool Ekf::initialiseFilter(void)
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{
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// Keep accumulating measurements until we have a minimum of 10 samples for the baro and magnetoemter
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// Sum the IMU delta angle measurements
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_delVel_sum += _imu_down_sampled.delta_vel;
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// Sum the magnetometer measurements
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magSample mag_init = _mag_buffer.get_newest();
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if (mag_init.time_us != 0) {
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_mag_counter ++;
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_mag_sum += mag_init.mag;
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}
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// Sum the barometer measurements
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// initialize vertical position with newest baro measurement
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baroSample baro_init = _baro_buffer.get_newest();
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if (baro_init.time_us != 0) {
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_baro_counter ++;
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_baro_sum += baro_init.hgt;
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}
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// check to see if we have enough measruements and return false if not
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if (_baro_counter < 10 || _mag_counter < 10) {
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return false;
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} else {
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// Zero all of the states
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_state.ang_error.setZero();
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_state.vel.setZero();
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_state.pos.setZero();
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_state.gyro_bias.setZero();
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_state.gyro_scale(0) = _state.gyro_scale(1) = _state.gyro_scale(2) = 1.0f;
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_state.accel_z_bias = 0.0f;
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_state.mag_I.setZero();
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_state.mag_B.setZero();
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_state.wind_vel.setZero();
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// get initial roll and pitch estimate from delta velocity vector, assuming vehicle is static
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float pitch = 0.0f;
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float roll = 0.0f;
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if (_delVel_sum.norm() > 0.001f) {
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_delVel_sum.normalize();
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pitch = asinf(_delVel_sum(0));
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roll = -asinf(_delVel_sum(1) / cosf(pitch));
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} else {
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return false;
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}
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// calculate the averaged magnetometer reading
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Vector3f mag_init = _mag_sum * (1.0f / (float(_mag_counter)));
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// rotate magnetic field into earth frame assuming zero yaw and estimate yaw angle assuming zero declination
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// TODO use declination if available
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matrix::Euler<float> euler_init(roll, pitch, 0.0f);
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matrix::Dcm<float> R_to_earth_zeroyaw(euler_init);
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Vector3f mag_ef_zeroyaw = R_to_earth_zeroyaw * mag_init;
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float declination = 0.0f;
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euler_init(2) = declination - atan2f(mag_ef_zeroyaw(1), mag_ef_zeroyaw(0));
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// calculate initial quaternion states
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_state.quat_nominal = Quaternion(euler_init);
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_output_new.quat_nominal = _state.quat_nominal;
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// TODO replace this with a conditional test based on fitered angle error states.
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_control_status.flags.angle_align = true;
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// calculate initial earth magnetic field states
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matrix::Dcm<float> R_to_earth(euler_init);
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_state.mag_I = R_to_earth * mag_init;
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// calculate the averaged barometer reading
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_baro_at_alignment = _baro_sum / (float)_baro_counter;
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// set the velocity to the GPS measurement (by definition, the initial position and height is at the origin)
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resetVelocity();
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// initialise the state covariance matrix
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initialiseCovariance();
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return true;
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}
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}
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void Ekf::predictState()
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{
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if (!_earth_rate_initialised) {
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if (_NED_origin_initialised) {
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calcEarthRateNED(_earth_rate_NED, _pos_ref.lat_rad);
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_earth_rate_initialised = true;
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}
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}
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// attitude error state prediciton
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matrix::Dcm<float> R_to_earth(_state.quat_nominal); // transformation matrix from body to world frame
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Vector3f corrected_delta_ang = _imu_sample_delayed.delta_ang - _R_prev * _earth_rate_NED *
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_imu_sample_delayed.delta_ang_dt;
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Quaternion dq; // delta quaternion since last update
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dq.from_axis_angle(corrected_delta_ang);
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_state.quat_nominal = dq * _state.quat_nominal;
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_state.quat_nominal.normalize();
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_R_prev = R_to_earth.transpose();
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Vector3f vel_last = _state.vel;
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// predict velocity states
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_state.vel += R_to_earth * _imu_sample_delayed.delta_vel;
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_state.vel(2) += 9.81f * _imu_sample_delayed.delta_vel_dt;
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// predict position states via trapezoidal integration of velocity
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_state.pos += (vel_last + _state.vel) * _imu_sample_delayed.delta_vel_dt * 0.5f;
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constrainStates();
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}
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bool Ekf::collect_imu(imuSample &imu)
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{
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imu.delta_ang(0) = imu.delta_ang(0) * _state.gyro_scale(0);
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imu.delta_ang(1) = imu.delta_ang(1) * _state.gyro_scale(1);
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imu.delta_ang(2) = imu.delta_ang(2) * _state.gyro_scale(2);
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imu.delta_ang -= _state.gyro_bias * imu.delta_ang_dt / (_dt_imu_avg > 0 ? _dt_imu_avg : 0.01f);
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imu.delta_vel(2) -= _state.accel_z_bias * imu.delta_vel_dt / (_dt_imu_avg > 0 ? _dt_imu_avg : 0.01f);;
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// store the new sample for the complementary filter prediciton
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_imu_sample_new = {
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.delta_ang = imu.delta_ang,
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.delta_vel = imu.delta_vel,
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.delta_ang_dt = imu.delta_ang_dt,
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.delta_vel_dt = imu.delta_vel_dt,
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.time_us = imu.time_us
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};
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_imu_down_sampled.delta_ang_dt += imu.delta_ang_dt;
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_imu_down_sampled.delta_vel_dt += imu.delta_vel_dt;
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Quaternion delta_q;
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delta_q.rotate(imu.delta_ang);
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_q_down_sampled = _q_down_sampled * delta_q;
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_q_down_sampled.normalize();
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matrix::Dcm<float> delta_R(delta_q.inversed());
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_imu_down_sampled.delta_vel = delta_R * _imu_down_sampled.delta_vel;
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_imu_down_sampled.delta_vel += imu.delta_vel;
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if ((_dt_imu_avg * _imu_ticks >= (float)(FILTER_UPDATE_PERRIOD_MS) / 1000) ||
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_dt_imu_avg * _imu_ticks >= 0.02f) {
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imu = {
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.delta_ang = _q_down_sampled.to_axis_angle(),
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.delta_vel = _imu_down_sampled.delta_vel,
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.delta_ang_dt = _imu_down_sampled.delta_ang_dt,
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.delta_vel_dt = _imu_down_sampled.delta_vel_dt,
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.time_us = imu.time_us
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};
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_imu_down_sampled.delta_ang.setZero();
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_imu_down_sampled.delta_vel.setZero();
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_imu_down_sampled.delta_ang_dt = 0.0f;
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_imu_down_sampled.delta_vel_dt = 0.0f;
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_q_down_sampled(0) = 1.0f;
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_q_down_sampled(1) = _q_down_sampled(2) = _q_down_sampled(3) = 0.0f;
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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 Ekf::calculateOutputStates()
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{
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imuSample imu_new = _imu_sample_new;
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Vector3f delta_angle;
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// Note: We do no not need to consider any bias or scale correction here
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// since the base class has already corrected the imu sample
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delta_angle(0) = imu_new.delta_ang(0);
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delta_angle(1) = imu_new.delta_ang(1);
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delta_angle(2) = imu_new.delta_ang(2);
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Vector3f delta_vel = imu_new.delta_vel;
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delta_angle += _delta_angle_corr;
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Quaternion dq;
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dq.from_axis_angle(delta_angle);
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_output_new.time_us = imu_new.time_us;
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_output_new.quat_nominal = dq * _output_new.quat_nominal;
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_output_new.quat_nominal.normalize();
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matrix::Dcm<float> R_to_earth(_output_new.quat_nominal);
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Vector3f delta_vel_NED = R_to_earth * delta_vel + _delta_vel_corr;
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delta_vel_NED(2) += 9.81f * imu_new.delta_vel_dt;
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Vector3f vel_last = _output_new.vel;
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_output_new.vel += delta_vel_NED;
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_output_new.pos += (_output_new.vel + vel_last) * (imu_new.delta_vel_dt * 0.5f) + _vel_corr * imu_new.delta_vel_dt;
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if (_imu_updated) {
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_output_buffer.push(_output_new);
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_imu_updated = false;
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}
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_output_sample_delayed = _output_buffer.get_oldest();
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Quaternion quat_inv = _state.quat_nominal.inversed();
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Quaternion q_error = _output_sample_delayed.quat_nominal * quat_inv;
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q_error.normalize();
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Vector3f delta_ang_error;
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float scalar;
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if (q_error(0) >= 0.0f) {
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scalar = -2.0f;
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} else {
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scalar = 2.0f;
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}
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delta_ang_error(0) = scalar * q_error(1);
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delta_ang_error(1) = scalar * q_error(2);
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delta_ang_error(2) = scalar * q_error(3);
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_delta_angle_corr = delta_ang_error * imu_new.delta_ang_dt;
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_delta_vel_corr = (_state.vel - _output_sample_delayed.vel) * imu_new.delta_vel_dt;
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_vel_corr = (_state.pos - _output_sample_delayed.pos);
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}
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void Ekf::fuseAirspeed()
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{
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}
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void Ekf::fuseRange()
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{
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}
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void Ekf::printStates()
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{
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static int counter = 0;
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if (counter % 50 == 0) {
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printf("quaternion\n");
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for (int i = 0; i < 4; i++) {
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printf("quat %i %.5f\n", i, (double)_state.quat_nominal(i));
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}
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matrix::Euler<float> euler(_state.quat_nominal);
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printf("yaw pitch roll %.5f %.5f %.5f\n", (double)euler(2), (double)euler(1), (double)euler(0));
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printf("vel\n");
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for (int i = 0; i < 3; i++) {
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printf("v %i %.5f\n", i, (double)_state.vel(i));
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}
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printf("pos\n");
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for (int i = 0; i < 3; i++) {
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printf("p %i %.5f\n", i, (double)_state.pos(i));
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}
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printf("gyro_scale\n");
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for (int i = 0; i < 3; i++) {
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|
printf("gs %i %.5f\n", i, (double)_state.gyro_scale(i));
|
|
}
|
|
|
|
printf("mag earth\n");
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
printf("mI %i %.5f\n", i, (double)_state.mag_I(i));
|
|
}
|
|
|
|
printf("mag bias\n");
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
printf("mB %i %.5f\n", i, (double)_state.mag_B(i));
|
|
}
|
|
|
|
counter = 0;
|
|
}
|
|
|
|
counter++;
|
|
|
|
}
|
|
|
|
void Ekf::printStatesFast()
|
|
{
|
|
static int counter_fast = 0;
|
|
|
|
if (counter_fast % 50 == 0) {
|
|
printf("quaternion\n");
|
|
|
|
for (int i = 0; i < 4; i++) {
|
|
printf("quat %i %.5f\n", i, (double)_output_new.quat_nominal(i));
|
|
}
|
|
|
|
printf("vel\n");
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
printf("v %i %.5f\n", i, (double)_output_new.vel(i));
|
|
}
|
|
|
|
printf("pos\n");
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
printf("p %i %.5f\n", i, (double)_output_new.pos(i));
|
|
}
|
|
|
|
counter_fast = 0;
|
|
}
|
|
|
|
counter_fast++;
|
|
}
|