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177 lines
4.5 KiB
177 lines
4.5 KiB
/**************************************************************************** |
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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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{ |
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} |
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Ekf::~Ekf() |
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{ |
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} |
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void Ekf::update() |
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{ |
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if (!_filter_initialised) { |
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_filter_initialised = initialiseFilter(); |
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} |
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// prediction |
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if (_imu_updated) { |
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predictState(); |
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predictCovariance(); |
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_imu_updated = false; |
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} |
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// measurement updates |
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if (_mag_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_mag_sample_delayed)) { |
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fuseMag(); |
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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 (_gps_buffer.pop_first_older_than(_imu_sample_delayed.time_us, &_gps_sample_delayed)) { |
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_fuse_pos = true; |
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_fuse_vel = true; |
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} |
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if (_fuse_height || _fuse_pos || _fuse_vel) { |
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fusePosVel(); |
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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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} |
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bool Ekf::initialiseFilter(void) |
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{ |
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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 attitude estimate from accel vector, assuming vehicle is static |
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Vector3f accel_init = _imu_down_sampled.delta_vel / _imu_down_sampled.delta_vel_dt; |
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float pitch = 0.0f; |
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float roll = 0.0f; |
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if (accel_init.norm() > 0.001f) { |
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accel_init.normalize(); |
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pitch = asinf(accel_init(0)); |
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roll = -asinf(accel_init(1) / cosf(pitch)); |
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} |
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matrix::Euler<float> euler_init(0, pitch, roll); |
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_state.quat_nominal = Quaternion(euler_init); |
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resetVelocity(); |
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resetPosition(); |
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initialiseCovariance(); |
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return true; |
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} |
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void Ekf::predictState() |
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{ |
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// compute transformation matrix from body to world frame |
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matrix::Dcm<float> R(_state.quat_nominal); |
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R.transpose(); |
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// attitude error state prediciton |
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Quaternion dq; |
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dq.from_axis_angle(_imu_sample_delayed.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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Vector3f vel_last = _state.vel; |
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// predict velocity states |
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_state.vel += R * _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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//matrix::Euler<float> euler(_state.quat_nominal); |
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//printf("roll pitch yaw %.5f %.5f %.5f\n", (double)euler(2), (double)euler(1), (double)euler(0)); |
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} |
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void Ekf::fusePosVel() |
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{ |
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} |
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void Ekf::fuseMag() |
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{ |
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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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