forked from Archive/PX4-Autopilot
466 lines
16 KiB
C++
466 lines
16 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2013 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 estimator_interface.cpp
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* Definition of base class for attitude estimators
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*
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* @author Roman Bast <bapstroman@gmail.com>
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* @author Paul Riseborough <p_riseborough@live.com.au>
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* @author Siddharth B Purohit <siddharthbharatpurohit@gmail.com>
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*/
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#include "estimator_interface.h"
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#include "../ecl.h"
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#include <math.h>
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#include "mathlib.h"
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// Accumulate imu data and store to buffer at desired rate
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void EstimatorInterface::setIMUData(uint64_t time_usec, uint64_t delta_ang_dt, uint64_t delta_vel_dt,
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float (&delta_ang)[3], float (&delta_vel)[3])
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{
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if (!_initialised) {
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init(time_usec);
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_initialised = true;
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}
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float dt = (float)(time_usec - _time_last_imu) / 1000 / 1000;
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dt = math::max(dt, 1.0e-4f);
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dt = math::min(dt, 0.02f);
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_time_last_imu = time_usec;
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if (_time_last_imu > 0) {
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_dt_imu_avg = 0.8f * _dt_imu_avg + 0.2f * dt;
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}
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// copy data
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imuSample imu_sample_new = {};
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imu_sample_new.delta_ang = Vector3f(delta_ang);
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imu_sample_new.delta_vel = Vector3f(delta_vel);
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// convert time from us to secs
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imu_sample_new.delta_ang_dt = delta_ang_dt / 1e6f;
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imu_sample_new.delta_vel_dt = delta_vel_dt / 1e6f;
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imu_sample_new.time_us = time_usec;
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_imu_ticks++;
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// calculate a metric which indicates the amount of coning vibration
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Vector3f temp = cross_product(imu_sample_new.delta_ang, _delta_ang_prev);
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_vibe_metrics[0] = 0.99f * _vibe_metrics[0] + 0.01f * temp.norm();
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// calculate a metric which indiates the amount of high frequency gyro vibration
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temp = imu_sample_new.delta_ang - _delta_ang_prev;
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_delta_ang_prev = imu_sample_new.delta_ang;
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_vibe_metrics[1] = 0.99f * _vibe_metrics[1] + 0.01f * temp.norm();
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// calculate a metric which indicates the amount of high fequency accelerometer vibration
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temp = imu_sample_new.delta_vel - _delta_vel_prev;
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_delta_vel_prev = imu_sample_new.delta_vel;
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_vibe_metrics[2] = 0.99f * _vibe_metrics[2] + 0.01f * temp.norm();
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// accumulate and down-sample imu data and push to the buffer when new downsampled data becomes available
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if (collect_imu(imu_sample_new)) {
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_imu_buffer.push(imu_sample_new);
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_imu_ticks = 0;
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_imu_updated = true;
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// down-sample the drag specific force data by accumulating and calculating the mean when
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// sufficient samples have been collected
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if (_params.fusion_mode & MASK_USE_DRAG) {
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_drag_sample_count ++;
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// note acceleration is accumulated as a delta velocity
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_drag_down_sampled.accelXY(0) += imu_sample_new.delta_vel(0);
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_drag_down_sampled.accelXY(1) += imu_sample_new.delta_vel(1);
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_drag_down_sampled.time_us += imu_sample_new.time_us;
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_drag_sample_time_dt += imu_sample_new.delta_vel_dt;
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// calculate the downsample ratio for drag specific force data
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uint8_t min_sample_ratio = (uint8_t) ceilf((float)_imu_buffer_length / _obs_buffer_length);
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if (min_sample_ratio < 5) {
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min_sample_ratio = 5;
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}
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// calculate and store means from accumulated values
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if (_drag_sample_count >= min_sample_ratio) {
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// note conversion from accumulated delta velocity to acceleration
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_drag_down_sampled.accelXY(0) /= _drag_sample_time_dt;
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_drag_down_sampled.accelXY(1) /= _drag_sample_time_dt;
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_drag_down_sampled.time_us /= _drag_sample_count;
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// write to buffer
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_drag_buffer.push(_drag_down_sampled);
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// reset accumulators
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_drag_sample_count = 0;
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_drag_down_sampled.accelXY.zero();
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_drag_down_sampled.time_us = 0;
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_drag_sample_time_dt = 0.0f;
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}
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}
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// get the oldest data from the buffer
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_imu_sample_delayed = _imu_buffer.get_oldest();
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// calculate the minimum interval between observations required to guarantee no loss of data
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// this will occur if data is overwritten before its time stamp falls behind the fusion time horizon
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_min_obs_interval_us = (_imu_sample_new.time_us - _imu_sample_delayed.time_us) / (_obs_buffer_length - 1);
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} else {
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_imu_updated = false;
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}
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}
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void EstimatorInterface::setMagData(uint64_t time_usec, float (&data)[3])
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{
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// limit data rate to prevent data being lost
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if (time_usec - _time_last_mag > _min_obs_interval_us) {
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magSample mag_sample_new = {};
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mag_sample_new.time_us = time_usec - _params.mag_delay_ms * 1000;
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mag_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
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_time_last_mag = time_usec;
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mag_sample_new.mag = Vector3f(data);
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_mag_buffer.push(mag_sample_new);
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}
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}
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void EstimatorInterface::setGpsData(uint64_t time_usec, struct gps_message *gps)
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{
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if (!_initialised) {
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return;
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}
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// limit data rate to prevent data being lost
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bool need_gps = (_params.fusion_mode & MASK_USE_GPS) || (_params.vdist_sensor_type == VDIST_SENSOR_GPS);
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if (((time_usec - _time_last_gps) > _min_obs_interval_us) && need_gps && gps->fix_type > 2) {
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gpsSample gps_sample_new = {};
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gps_sample_new.time_us = gps->time_usec - _params.gps_delay_ms * 1000;
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gps_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
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_time_last_gps = time_usec;
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gps_sample_new.time_us = math::max(gps_sample_new.time_us, _imu_sample_delayed.time_us);
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gps_sample_new.vel = Vector3f(gps->vel_ned);
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_gps_speed_valid = gps->vel_ned_valid;
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gps_sample_new.sacc = gps->sacc;
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gps_sample_new.hacc = gps->eph;
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gps_sample_new.vacc = gps->epv;
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gps_sample_new.hgt = (float)gps->alt * 1e-3f;
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// Only calculate the relative position if the WGS-84 location of the origin is set
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if (collect_gps(time_usec, gps)) {
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float lpos_x = 0.0f;
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float lpos_y = 0.0f;
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map_projection_project(&_pos_ref, (gps->lat / 1.0e7), (gps->lon / 1.0e7), &lpos_x, &lpos_y);
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gps_sample_new.pos(0) = lpos_x;
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gps_sample_new.pos(1) = lpos_y;
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} else {
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gps_sample_new.pos(0) = 0.0f;
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gps_sample_new.pos(1) = 0.0f;
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}
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_gps_buffer.push(gps_sample_new);
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}
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}
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void EstimatorInterface::setBaroData(uint64_t time_usec, float data)
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{
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if (!_initialised) {
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return;
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}
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// limit data rate to prevent data being lost
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if (time_usec - _time_last_baro > _min_obs_interval_us) {
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baroSample baro_sample_new{};
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baro_sample_new.hgt = data;
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baro_sample_new.time_us = time_usec - _params.baro_delay_ms * 1000;
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baro_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
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_time_last_baro = time_usec;
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baro_sample_new.time_us = math::max(baro_sample_new.time_us, _imu_sample_delayed.time_us);
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_baro_buffer.push(baro_sample_new);
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}
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}
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void EstimatorInterface::setAirspeedData(uint64_t time_usec, float true_airspeed, float eas2tas)
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{
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if (!_initialised) {
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return;
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}
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// limit data rate to prevent data being lost
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if (time_usec - _time_last_airspeed > _min_obs_interval_us) {
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airspeedSample airspeed_sample_new{};
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airspeed_sample_new.true_airspeed = true_airspeed;
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airspeed_sample_new.eas2tas = eas2tas;
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airspeed_sample_new.time_us = time_usec - _params.airspeed_delay_ms * 1000;
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airspeed_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; //typo PeRRiod
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_time_last_airspeed = time_usec;
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_airspeed_buffer.push(airspeed_sample_new);
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}
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}
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static float rng;
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// set range data
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void EstimatorInterface::setRangeData(uint64_t time_usec, float data)
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{
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if (!_initialised) {
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return;
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}
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// limit data rate to prevent data being lost
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if (time_usec - _time_last_range > _min_obs_interval_us) {
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rangeSample range_sample_new = {};
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range_sample_new.rng = data;
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rng = data;
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range_sample_new.time_us = time_usec - _params.range_delay_ms * 1000;
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_time_last_range = time_usec;
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_range_buffer.push(range_sample_new);
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}
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}
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// set optical flow data
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void EstimatorInterface::setOpticalFlowData(uint64_t time_usec, flow_message *flow)
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{
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if (!_initialised) {
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return;
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}
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// limit data rate to prevent data being lost
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if (time_usec - _time_last_optflow > _min_obs_interval_us) {
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// check if enough integration time and fail if integration time is less than 50%
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// of min arrival interval because too much data is being lost
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float delta_time = 1e-6f * (float)flow->dt;
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bool delta_time_good = (delta_time >= 5e-7f * (float)_min_obs_interval_us);
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// check magnitude is within sensor limits
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float flow_rate_magnitude;
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bool flow_magnitude_good = true;
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if (delta_time_good) {
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flow_rate_magnitude = flow->flowdata.norm() / delta_time;
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flow_magnitude_good = (flow_rate_magnitude <= _params.flow_rate_max);
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}
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// check quality metric
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bool flow_quality_good = (flow->quality >= _params.flow_qual_min);
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// Always use data when on ground to allow for bad quality due to unfocussed sensors and operator handling
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// If flow quality fails checks on ground, assume zero flow rate after body rate compensation
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if ((delta_time_good && flow_quality_good && flow_magnitude_good) || !_control_status.flags.in_air) {
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flowSample optflow_sample_new;
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// calculate the system time-stamp for the mid point of the integration period
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optflow_sample_new.time_us = time_usec - _params.flow_delay_ms * 1000 - flow->dt / 2;
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// copy the quality metric returned by the PX4Flow sensor
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optflow_sample_new.quality = flow->quality;
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// NOTE: the EKF uses the reverse sign convention to the flow sensor. EKF assumes positive LOS rate is produced by a RH rotation of the image about the sensor axis.
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// copy the optical and gyro measured delta angles
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optflow_sample_new.gyroXYZ = - flow->gyrodata;
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if (flow_quality_good) {
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optflow_sample_new.flowRadXY = - flow->flowdata;
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} else {
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// when on the ground with poor flow quality, assume zero ground relative velocity
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optflow_sample_new.flowRadXY(0) = - flow->gyrodata(0);
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optflow_sample_new.flowRadXY(1) = - flow->gyrodata(1);
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}
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// compensate for body motion to give a LOS rate
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optflow_sample_new.flowRadXYcomp(0) = optflow_sample_new.flowRadXY(0) - optflow_sample_new.gyroXYZ(0);
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optflow_sample_new.flowRadXYcomp(1) = optflow_sample_new.flowRadXY(1) - optflow_sample_new.gyroXYZ(1);
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// convert integration interval to seconds
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optflow_sample_new.dt = 1e-6f * (float)flow->dt;
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_time_last_optflow = time_usec;
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// push to buffer
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_flow_buffer.push(optflow_sample_new);
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}
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}
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}
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// set attitude and position data derived from an external vision system
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void EstimatorInterface::setExtVisionData(uint64_t time_usec, ext_vision_message *evdata)
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{
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if (!_initialised) {
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return;
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}
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// limit data rate to prevent data being lost
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if (time_usec - _time_last_ext_vision > _min_obs_interval_us) {
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extVisionSample ev_sample_new;
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// calculate the system time-stamp for the mid point of the integration period
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ev_sample_new.time_us = time_usec - _params.ev_delay_ms * 1000;
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// copy required data
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ev_sample_new.angErr = evdata->angErr;
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ev_sample_new.posErr = evdata->posErr;
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ev_sample_new.quat = evdata->quat;
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ev_sample_new.posNED = evdata->posNED;
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// record time for comparison next measurement
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_time_last_ext_vision = time_usec;
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// push to buffer
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_ext_vision_buffer.push(ev_sample_new);
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}
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}
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bool EstimatorInterface::initialise_interface(uint64_t timestamp)
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{
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// find the maximum time delay the buffers are required to handle
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uint16_t max_time_delay_ms = math::max(_params.mag_delay_ms,
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math::max(_params.range_delay_ms,
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math::max(_params.gps_delay_ms,
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math::max(_params.flow_delay_ms,
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math::max(_params.ev_delay_ms,
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math::max(_params.min_delay_ms,
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math::max(_params.airspeed_delay_ms, _params.baro_delay_ms)))))));
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// calculate the IMU buffer length required to accomodate the maximum delay with some allowance for jitter
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_imu_buffer_length = (max_time_delay_ms / FILTER_UPDATE_PERIOD_MS) + 1;
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// set the observaton buffer length to handle the minimum time of arrival between observations in combination
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// with the worst case delay from current time to ekf fusion time
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// allow for worst case 50% extension of the ekf fusion time horizon delay due to timing jitter
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uint16_t ekf_delay_ms = max_time_delay_ms + (int)(ceilf((float)max_time_delay_ms * 0.5f));
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_obs_buffer_length = (ekf_delay_ms / _params.sensor_interval_min_ms) + 1;
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// limit to be no longer than the IMU buffer (we can't process data faster than the EKF prediction rate)
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_obs_buffer_length = math::min(_obs_buffer_length, _imu_buffer_length);
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if (!(_imu_buffer.allocate(_imu_buffer_length) &&
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_gps_buffer.allocate(_obs_buffer_length) &&
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_mag_buffer.allocate(_obs_buffer_length) &&
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_baro_buffer.allocate(_obs_buffer_length) &&
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_range_buffer.allocate(_obs_buffer_length) &&
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_airspeed_buffer.allocate(_obs_buffer_length) &&
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_flow_buffer.allocate(_obs_buffer_length) &&
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_ext_vision_buffer.allocate(_obs_buffer_length) &&
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_drag_buffer.allocate(_obs_buffer_length) &&
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_output_buffer.allocate(_imu_buffer_length) &&
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_output_vert_buffer.allocate(_imu_buffer_length))) {
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ECL_ERR("EKF buffer allocation failed!");
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unallocate_buffers();
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return false;
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}
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// zero the data in the observation buffers
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for (int index = 0; index < _obs_buffer_length; index++) {
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gpsSample gps_sample_init = {};
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_gps_buffer.push(gps_sample_init);
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magSample mag_sample_init = {};
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_mag_buffer.push(mag_sample_init);
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baroSample baro_sample_init = {};
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_baro_buffer.push(baro_sample_init);
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rangeSample range_sample_init = {};
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_range_buffer.push(range_sample_init);
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airspeedSample airspeed_sample_init = {};
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_airspeed_buffer.push(airspeed_sample_init);
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flowSample flow_sample_init = {};
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_flow_buffer.push(flow_sample_init);
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extVisionSample ext_vision_sample_init = {};
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_ext_vision_buffer.push(ext_vision_sample_init);
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dragSample drag_sample_init = {};
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_drag_buffer.push(drag_sample_init);
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}
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// zero the data in the imu data and output observer state buffers
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for (int index = 0; index < _imu_buffer_length; index++) {
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imuSample imu_sample_init = {};
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_imu_buffer.push(imu_sample_init);
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outputSample output_sample_init = {};
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_output_buffer.push(output_sample_init);
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}
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_dt_imu_avg = 0.0f;
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_imu_sample_delayed.delta_ang.setZero();
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_imu_sample_delayed.delta_vel.setZero();
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_imu_sample_delayed.delta_ang_dt = 0.0f;
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_imu_sample_delayed.delta_vel_dt = 0.0f;
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_imu_sample_delayed.time_us = timestamp;
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_imu_ticks = 0;
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_initialised = false;
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_time_last_imu = 0;
|
|
_time_last_gps = 0;
|
|
_time_last_mag = 0;
|
|
_time_last_baro = 0;
|
|
_time_last_range = 0;
|
|
_time_last_airspeed = 0;
|
|
_time_last_optflow = 0;
|
|
_fault_status.value = 0;
|
|
_time_last_ext_vision = 0;
|
|
return true;
|
|
}
|
|
|
|
void EstimatorInterface::unallocate_buffers()
|
|
{
|
|
_imu_buffer.unallocate();
|
|
_gps_buffer.unallocate();
|
|
_mag_buffer.unallocate();
|
|
_baro_buffer.unallocate();
|
|
_range_buffer.unallocate();
|
|
_airspeed_buffer.unallocate();
|
|
_flow_buffer.unallocate();
|
|
_ext_vision_buffer.unallocate();
|
|
_output_buffer.unallocate();
|
|
_output_vert_buffer.unallocate();
|
|
|
|
}
|
|
|
|
bool EstimatorInterface::local_position_is_valid()
|
|
{
|
|
// return true if the position estimate is valid
|
|
return (((_time_last_imu - _time_last_optflow) < 5e6) && _control_status.flags.opt_flow) ||
|
|
(((_time_last_imu - _time_last_ext_vision) < 5e6) && _control_status.flags.ev_pos) ||
|
|
global_position_is_valid();
|
|
}
|