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px4-firmware/EKF/estimator_interface.cpp

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/****************************************************************************
*
* Copyright (c) 2013 Estimation and Control Library (ECL). All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
* 3. Neither the name ECL nor the names of its contributors may be
* used to endorse or promote products derived from this software
* without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*
****************************************************************************/
/**
* @file estimator_interface.cpp
* Definition of base class for attitude estimators
*
* @author Roman Bast <bapstroman@gmail.com>
* @author Paul Riseborough <p_riseborough@live.com.au>
* @author Siddharth B Purohit <siddharthbharatpurohit@gmail.com>
*/
#include <inttypes.h>
#include <math.h>
#include "../ecl.h"
#include "estimator_interface.h"
#include "mathlib.h"
EstimatorInterface::EstimatorInterface():
_obs_buffer_length(10),
_imu_buffer_length(30),
_min_obs_interval_us(0),
_dt_imu_avg(0.0f),
_mag_sample_delayed{},
_baro_sample_delayed{},
_gps_sample_delayed{},
_range_sample_delayed{},
_airspeed_sample_delayed{},
_flow_sample_delayed{},
_ev_sample_delayed{},
_imu_ticks(0),
_imu_updated(false),
_initialised(false),
_NED_origin_initialised(false),
_gps_speed_valid(false),
_gps_origin_eph(0.0f),
_gps_origin_epv(0.0f),
_pos_ref{},
_yaw_test_ratio(0.0f),
_mag_test_ratio{},
_vel_pos_test_ratio{},
_tas_test_ratio(0.0f),
_terr_test_ratio(0.0f),
_beta_test_ratio(0.0f),
_vibe_metrics{},
_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_ext_vision(0),
_time_last_optflow(0),
_mag_declination_gps(0.0f),
_mag_declination_to_save_deg(0.0f)
{
_delta_ang_prev.setZero();
_delta_vel_prev.setZero();
}
// Accumulate imu data and store to buffer at desired rate
void EstimatorInterface::setIMUData(uint64_t time_usec, uint64_t delta_ang_dt, uint64_t delta_vel_dt, float (&delta_ang)[3],
float (&delta_vel)[3])
{
if (!_initialised) {
init(time_usec);
_initialised = true;
}
float dt = (float)(time_usec - _time_last_imu) / 1000 / 1000;
dt = math::max(dt, 1.0e-4f);
dt = math::min(dt, 0.02f);
_time_last_imu = time_usec;
if (_time_last_imu > 0) {
_dt_imu_avg = 0.8f * _dt_imu_avg + 0.2f * dt;
}
// copy data
imuSample imu_sample_new = {};
memcpy(&imu_sample_new.delta_ang._data[0], &delta_ang[0], sizeof(imu_sample_new.delta_ang._data));
memcpy(&imu_sample_new.delta_vel._data[0], &delta_vel[0], sizeof(imu_sample_new.delta_vel._data));
// convert time from us to secs
imu_sample_new.delta_ang_dt = delta_ang_dt / 1e6f;
imu_sample_new.delta_vel_dt = delta_vel_dt / 1e6f;
imu_sample_new.time_us = time_usec;
_imu_ticks++;
// calculate a metric which indicates the amount of coning vibration
Vector3f temp = cross_product(imu_sample_new.delta_ang , _delta_ang_prev);
_vibe_metrics[0] = 0.99f * _vibe_metrics[0] + 0.01f * temp.norm();
// calculate a metric which indiates the amount of high frequency gyro vibration
temp = imu_sample_new.delta_ang - _delta_ang_prev;
_delta_ang_prev = imu_sample_new.delta_ang;
_vibe_metrics[1] = 0.99f * _vibe_metrics[1] + 0.01f * temp.norm();
// calculate a metric which indicates the amount of high fequency accelerometer vibration
temp = imu_sample_new.delta_vel - _delta_vel_prev;
_delta_vel_prev = imu_sample_new.delta_vel;
_vibe_metrics[2] = 0.99f * _vibe_metrics[2] + 0.01f * temp.norm();
// accumulate and down-sample imu data and push to the buffer when new downsampled data becomes available
if (collect_imu(imu_sample_new)) {
_imu_buffer.push(imu_sample_new);
_imu_ticks = 0;
_imu_updated = true;
// get the oldest data from the buffer
_imu_sample_delayed = _imu_buffer.get_oldest();
// calculate the minimum interval between observations required to guarantee no loss of data
// this will occur if data is overwritten before its time stamp falls behind the fusion time horizon
_min_obs_interval_us = (_imu_sample_new.time_us - _imu_sample_delayed.time_us)/(_obs_buffer_length - 1);
} else {
_imu_updated = false;
}
}
void EstimatorInterface::setMagData(uint64_t time_usec, float (&data)[3])
{
// limit data rate to prevent data being lost
if (time_usec - _time_last_mag > _min_obs_interval_us) {
magSample mag_sample_new = {};
mag_sample_new.time_us = time_usec - _params.mag_delay_ms * 1000;
mag_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
_time_last_mag = time_usec;
memcpy(&mag_sample_new.mag._data[0], data, sizeof(mag_sample_new.mag._data));
_mag_buffer.push(mag_sample_new);
}
}
void EstimatorInterface::setGpsData(uint64_t time_usec, struct gps_message *gps)
{
if (!_initialised) {
return;
}
// limit data rate to prevent data being lost
bool need_gps = (_params.fusion_mode & MASK_USE_GPS) || (_params.vdist_sensor_type == VDIST_SENSOR_GPS);
if (((time_usec - _time_last_gps) > _min_obs_interval_us) && need_gps) {
gpsSample gps_sample_new = {};
gps_sample_new.time_us = gps->time_usec - _params.gps_delay_ms * 1000;
gps_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
_time_last_gps = time_usec;
gps_sample_new.time_us = math::max(gps_sample_new.time_us, _imu_sample_delayed.time_us);
memcpy(&gps_sample_new.vel._data[0], gps->vel_ned, sizeof(gps_sample_new.vel._data));
_gps_speed_valid = gps->vel_ned_valid;
gps_sample_new.sacc = gps->sacc;
gps_sample_new.hacc = gps->eph;
gps_sample_new.vacc = gps->epv;
gps_sample_new.hgt = (float)gps->alt * 1e-3f;
// Only calculate the relative position if the WGS-84 location of the origin is set
if (collect_gps(time_usec, gps)) {
float lpos_x = 0.0f;
float lpos_y = 0.0f;
map_projection_project(&_pos_ref, (gps->lat / 1.0e7), (gps->lon / 1.0e7), &lpos_x, &lpos_y);
gps_sample_new.pos(0) = lpos_x;
gps_sample_new.pos(1) = lpos_y;
} else {
gps_sample_new.pos(0) = 0.0f;
gps_sample_new.pos(1) = 0.0f;
}
_gps_buffer.push(gps_sample_new);
}
}
void EstimatorInterface::setBaroData(uint64_t time_usec, float data)
{
if (!_initialised) {
return;
}
// limit data rate to prevent data being lost
if (time_usec - _time_last_baro > _min_obs_interval_us) {
baroSample baro_sample_new{};
baro_sample_new.hgt = data;
baro_sample_new.time_us = time_usec - _params.baro_delay_ms * 1000;
baro_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2;
_time_last_baro = time_usec;
baro_sample_new.time_us = math::max(baro_sample_new.time_us, _imu_sample_delayed.time_us);
_baro_buffer.push(baro_sample_new);
}
}
void EstimatorInterface::setAirspeedData(uint64_t time_usec, float true_airspeed, float eas2tas)
{
if (!_initialised) {
return;
}
// limit data rate to prevent data being lost
if (time_usec - _time_last_airspeed > _min_obs_interval_us) {
airspeedSample airspeed_sample_new{};
airspeed_sample_new.true_airspeed = true_airspeed;
airspeed_sample_new.eas2tas = eas2tas;
airspeed_sample_new.time_us = time_usec - _params.airspeed_delay_ms * 1000;
airspeed_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; //typo PeRRiod
_time_last_airspeed = time_usec;
_airspeed_buffer.push(airspeed_sample_new);
}
}
static float rng;
// set range data
void EstimatorInterface::setRangeData(uint64_t time_usec, float data)
{
if (!_initialised) {
return;
}
// limit data rate to prevent data being lost
if (time_usec - _time_last_range > _min_obs_interval_us) {
rangeSample range_sample_new = {};
range_sample_new.rng = data;
rng = data;
range_sample_new.time_us = time_usec - _params.range_delay_ms * 1000;
_time_last_range = time_usec;
_range_buffer.push(range_sample_new);
}
}
// set optical flow data
void EstimatorInterface::setOpticalFlowData(uint64_t time_usec, flow_message *flow)
{
if (!_initialised) {
return;
}
// limit data rate to prevent data being lost
if (time_usec - _time_last_optflow > _min_obs_interval_us) {
// check if enough integration time and fail if integration time is less than 50%
// of min arrival interval because too much data is being lost
float delta_time = 1e-6f * (float)flow->dt;
bool delta_time_good = (delta_time >= 5e-7f * (float)_min_obs_interval_us);
// check magnitude is within sensor limits
float flow_rate_magnitude;
bool flow_magnitude_good = false;
if (delta_time_good) {
flow_rate_magnitude = flow->flowdata.norm() / delta_time;
flow_magnitude_good = (flow_rate_magnitude <= _params.flow_rate_max);
}
// check quality metric
bool flow_quality_good = (flow->quality >= _params.flow_qual_min);
if (delta_time_good && flow_magnitude_good && (flow_quality_good || !_control_status.flags.in_air)) {
flowSample optflow_sample_new;
// calculate the system time-stamp for the mid point of the integration period
optflow_sample_new.time_us = time_usec - _params.flow_delay_ms * 1000 - flow->dt / 2;
// copy the quality metric returned by the PX4Flow sensor
optflow_sample_new.quality = flow->quality;
// 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.
// copy the optical and gyro measured delta angles
optflow_sample_new.gyroXYZ = - flow->gyrodata;
if (flow_quality_good) {
optflow_sample_new.flowRadXY = - flow->flowdata;
} else {
// when on the ground with poor flow quality, assume zero ground relative velocity
optflow_sample_new.flowRadXY(0) = + flow->gyrodata(0);
optflow_sample_new.flowRadXY(1) = + flow->gyrodata(1);
}
// compensate for body motion to give a LOS rate
optflow_sample_new.flowRadXYcomp(0) = optflow_sample_new.flowRadXY(0) - optflow_sample_new.gyroXYZ(0);
optflow_sample_new.flowRadXYcomp(1) = optflow_sample_new.flowRadXY(1) - optflow_sample_new.gyroXYZ(1);
// convert integration interval to seconds
optflow_sample_new.dt = 1e-6f * (float)flow->dt;
_time_last_optflow = time_usec;
// push to buffer
_flow_buffer.push(optflow_sample_new);
}
}
}
// set attitude and position data derived from an external vision system
void EstimatorInterface::setExtVisionData(uint64_t time_usec, ext_vision_message *evdata)
{
if (!_initialised) {
return;
}
// limit data rate to prevent data being lost
if (time_usec - _time_last_ext_vision > _min_obs_interval_us) {
extVisionSample ev_sample_new;
// calculate the system time-stamp for the mid point of the integration period
ev_sample_new.time_us = time_usec - _params.ev_delay_ms * 1000;
// copy required data
ev_sample_new.angErr = evdata->angErr;
ev_sample_new.posErr = evdata->posErr;
ev_sample_new.quat = evdata->quat;
ev_sample_new.posNED = evdata->posNED;
// record time for comparison next measurement
_time_last_ext_vision = time_usec;
// push to buffer
_ext_vision_buffer.push(ev_sample_new);
}
}
bool EstimatorInterface::initialise_interface(uint64_t timestamp)
{
// find the maximum time delay required to compensate for
uint16_t max_time_delay_ms = math::max(_params.mag_delay_ms,
math::max(_params.range_delay_ms,
math::max(_params.gps_delay_ms,
math::max(_params.flow_delay_ms,
math::max(_params.ev_delay_ms,
math::max(_params.airspeed_delay_ms, _params.baro_delay_ms))))));
// calculate the IMU buffer length required to accomodate the maximum delay with some allowance for jitter
_imu_buffer_length = (max_time_delay_ms / FILTER_UPDATE_PERIOD_MS) + 1;
// set the observaton buffer length to handle the minimum time of arrival between observations in combination
// with the worst case delay from current time to ekf fusion time
// allow for worst case 50% extension of the ekf fusion time horizon delay due to timing jitter
uint16_t ekf_delay_ms = max_time_delay_ms + (int)(ceilf((float)max_time_delay_ms * 0.5f));
_obs_buffer_length = (ekf_delay_ms / _params.sensor_interval_min_ms) + 1;
// limit to be no longer than the IMU buffer (we can't process data faster than the EKF prediction rate)
_obs_buffer_length = math::min(_obs_buffer_length,_imu_buffer_length);
if (!(_imu_buffer.allocate(_imu_buffer_length) &&
_gps_buffer.allocate(_obs_buffer_length) &&
_mag_buffer.allocate(_obs_buffer_length) &&
_baro_buffer.allocate(_obs_buffer_length) &&
_range_buffer.allocate(_obs_buffer_length) &&
_airspeed_buffer.allocate(_obs_buffer_length) &&
_flow_buffer.allocate(_obs_buffer_length) &&
_ext_vision_buffer.allocate(_obs_buffer_length) &&
_output_buffer.allocate(_imu_buffer_length))) {
ECL_ERR("EKF buffer allocation failed!");
unallocate_buffers();
return false;
}
// zero the data in the observation buffers
for (int index=0; index < _obs_buffer_length; index++) {
gpsSample gps_sample_init = {};
_gps_buffer.push(gps_sample_init);
magSample mag_sample_init = {};
_mag_buffer.push(mag_sample_init);
baroSample baro_sample_init = {};
_baro_buffer.push(baro_sample_init);
rangeSample range_sample_init = {};
_range_buffer.push(range_sample_init);
airspeedSample airspeed_sample_init = {};
_airspeed_buffer.push(airspeed_sample_init);
flowSample flow_sample_init = {};
_flow_buffer.push(flow_sample_init);
extVisionSample ext_vision_sample_init = {};
_ext_vision_buffer.push(ext_vision_sample_init);
}
// zero the data in the imu data and output observer state buffers
for (int index=0; index < _imu_buffer_length; index++) {
imuSample imu_sample_init = {};
_imu_buffer.push(imu_sample_init);
outputSample output_sample_init = {};
_output_buffer.push(output_sample_init);
}
_dt_imu_avg = 0.0f;
_imu_sample_delayed.delta_ang.setZero();
_imu_sample_delayed.delta_vel.setZero();
_imu_sample_delayed.delta_ang_dt = 0.0f;
_imu_sample_delayed.delta_vel_dt = 0.0f;
_imu_sample_delayed.time_us = timestamp;
_imu_ticks = 0;
_initialised = false;
_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;
memset(&_fault_status.flags, 0, sizeof(_fault_status.flags));
_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();
}
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();
}
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