fly316/PX4-Autopilot
7
0
Fork 0
mirror of https://gitee.com/mirrors_PX4/PX4-Autopilot.git synced 2026-04-14 10:07:39 +08:00
Code Issues Packages Projects Releases Wiki Activity
PX4-Autopilot/src/modules/ekf2/ekf2_main.cpp
priseborough fb6e050b06 ekf2: Improve error reporting 
Add missing velocity accuracy reporting
Add missing dead reckoning reporting
2017-05-03 08:37:14 +02:00

1282 lines
48 KiB
C++
Raw Blame History

/****************************************************************************
*
* Copyright (c) 2015 PX4 Development Team. 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 PX4 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 ekf2_main.cpp
* Implementation of the attitude and position estimator.
*
* @author Roman Bapst
*/
#include <px4_config.h>
#include <px4_defines.h>
#include <px4_tasks.h>
#include <px4_posix.h>
#include <px4_time.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include <fcntl.h>
#include <errno.h>
#include <math.h>
#include <poll.h>
#include <time.h>
#include <float.h>
#include <arch/board/board.h>
#include <systemlib/param/param.h>
#include <systemlib/err.h>
#include <systemlib/systemlib.h>
#include <mathlib/mathlib.h>
#include <mathlib/math/filter/LowPassFilter2p.hpp>
#include <platforms/px4_defines.h>
#include <drivers/drv_hrt.h>
#include <controllib/uorb/blocks.hpp>
#include <uORB/topics/sensor_combined.h>
#include <uORB/topics/vehicle_gps_position.h>
#include <uORB/topics/airspeed.h>
#include <uORB/topics/vehicle_attitude.h>
#include <uORB/topics/vehicle_local_position.h>
#include <uORB/topics/control_state.h>
#include <uORB/topics/vehicle_global_position.h>
#include <uORB/topics/wind_estimate.h>
#include <uORB/topics/estimator_status.h>
#include <uORB/topics/ekf2_innovations.h>
#include <uORB/topics/ekf2_replay.h>
#include <uORB/topics/ekf2_timestamps.h>
#include <uORB/topics/optical_flow.h>
#include <uORB/topics/distance_sensor.h>
#include <uORB/topics/vehicle_land_detected.h>
#include <uORB/topics/vehicle_status.h>
#include <ecl/EKF/ekf.h>
extern "C" __EXPORT int ekf2_main(int argc, char *argv[]);
class Ekf2;
namespace ekf2
{
Ekf2 *instance = nullptr;
}
class Ekf2 : public control::SuperBlock
{
public:
/**
* Constructor
*/
Ekf2();
/**
* Destructor, also kills task.
*/
~Ekf2();
/**
* Start task.
*
* @return OK on success.
*/
int start();
void set_replay_mode(bool replay) {_replay_mode = replay;};
static void task_main_trampoline(int argc, char *argv[]);
void task_main();
void print_status();
void exit() { _task_should_exit = true; }
private:
static constexpr float _dt_max = 0.02;
bool _task_should_exit = false;
int _control_task = -1; // task handle for task
bool _replay_mode; // should we use replay data from a log
int _publish_replay_mode; // defines if we should publish replay messages
float _default_ev_pos_noise = 0.05f; // external vision position noise used when an invalid value is supplied
float _default_ev_ang_noise = 0.05f; // external vision angle noise used when an invalid value is supplied
// Initialise time stamps used to send sensor data to the EKF and for logging
uint64_t _timestamp_mag_us = 0;
uint64_t _timestamp_balt_us = 0;
// Used to down sample magnetometer data
float _mag_data_sum[3]; // summed magnetometer readings (Ga)
uint64_t _mag_time_sum_ms; // summed magnetoemter time stamps (msec)
uint8_t _mag_sample_count = 0; // number of magnetometer measurements summed
uint32_t _mag_time_ms_last_used = 0; // time stamp in msec of the last averaged magnetometer measurement used by the EKF
// Used to down sample barometer data
float _balt_data_sum; // summed barometric altitude readings (m)
uint64_t _balt_time_sum_ms; // summed barometric altitude time stamps (msec)
uint8_t _balt_sample_count = 0; // number of barometric altitude measurements summed
uint32_t _balt_time_ms_last_used =
0; // time stamp in msec of the last averaged barometric altitude measurement used by the EKF
bool _prev_landed = true; // landed status from the previous frame
float _acc_hor_filt = 0.0f; // low-pass filtered horizontal acceleration
orb_advert_t _att_pub;
orb_advert_t _lpos_pub;
orb_advert_t _control_state_pub;
orb_advert_t _vehicle_global_position_pub;
orb_advert_t _wind_pub;
orb_advert_t _estimator_status_pub;
orb_advert_t _estimator_innovations_pub;
orb_advert_t _replay_pub;
orb_advert_t _ekf2_timestamps_pub;
/* Low pass filter for attitude rates */
math::LowPassFilter2p _lp_roll_rate;
math::LowPassFilter2p _lp_pitch_rate;
math::LowPassFilter2p _lp_yaw_rate;
Ekf _ekf;
parameters *_params; // pointer to ekf parameter struct (located in _ekf class instance)
control::BlockParamExtInt _obs_dt_min_ms;
control::BlockParamExtFloat _mag_delay_ms;
control::BlockParamExtFloat _baro_delay_ms;
control::BlockParamExtFloat _gps_delay_ms;
control::BlockParamExtFloat _flow_delay_ms;
control::BlockParamExtFloat _rng_delay_ms;
control::BlockParamExtFloat _airspeed_delay_ms;
control::BlockParamExtFloat _ev_delay_ms;
control::BlockParamExtFloat _gyro_noise;
control::BlockParamExtFloat _accel_noise;
// process noise
control::BlockParamExtFloat _gyro_bias_p_noise;
control::BlockParamExtFloat _accel_bias_p_noise;
control::BlockParamExtFloat _mage_p_noise;
control::BlockParamExtFloat _magb_p_noise;
control::BlockParamExtFloat _wind_vel_p_noise;
control::BlockParamExtFloat _terrain_p_noise; // terrain offset state random walk (m/s)
control::BlockParamExtFloat _terrain_gradient; // magnitude of terrain gradient (m/m)
control::BlockParamExtFloat _gps_vel_noise;
control::BlockParamExtFloat _gps_pos_noise;
control::BlockParamExtFloat _pos_noaid_noise;
control::BlockParamExtFloat _baro_noise;
control::BlockParamExtFloat _baro_innov_gate; // innovation gate for barometric height innovation test (std dev)
control::BlockParamExtFloat
_posNE_innov_gate; // innovation gate for GPS horizontal position innovation test (std dev)
control::BlockParamExtFloat _vel_innov_gate; // innovation gate for GPS velocity innovation test (std dev)
control::BlockParamExtFloat _tas_innov_gate; // innovation gate for tas innovation test (std dev)
control::BlockParamExtFloat _mag_heading_noise; // measurement noise used for simple heading fusion
control::BlockParamExtFloat _mag_noise; // measurement noise used for 3-axis magnetoemter fusion (Gauss)
control::BlockParamExtFloat _eas_noise; // measurement noise used for airspeed fusion (std m/s)
control::BlockParamExtFloat _beta_noise; // synthetic sideslip noise (m/s)
control::BlockParamExtFloat _mag_declination_deg;// magnetic declination in degrees
control::BlockParamExtFloat _heading_innov_gate;// innovation gate for heading innovation test
control::BlockParamExtFloat _mag_innov_gate; // innovation gate for magnetometer innovation test
control::BlockParamExtInt
_mag_decl_source; // bitmasked integer used to control the handling of magnetic declination
control::BlockParamExtInt _mag_fuse_type; // integer ued to control the type of magnetometer fusion used
control::BlockParamExtInt _gps_check_mask; // bitmasked integer used to activate the different GPS quality checks
control::BlockParamExtFloat _requiredEph; // maximum acceptable horiz position error (m)
control::BlockParamExtFloat _requiredEpv; // maximum acceptable vert position error (m)
control::BlockParamExtFloat _requiredSacc; // maximum acceptable speed error (m/s)
control::BlockParamExtInt _requiredNsats; // minimum acceptable satellite count
control::BlockParamExtFloat _requiredGDoP; // maximum acceptable geometric dilution of precision
control::BlockParamExtFloat _requiredHdrift; // maximum acceptable horizontal drift speed (m/s)
control::BlockParamExtFloat _requiredVdrift; // maximum acceptable vertical drift speed (m/s)
control::BlockParamExtInt _param_record_replay_msg;// indicates if we want to record ekf2 replay messages
// measurement source control
control::BlockParamExtInt
_fusion_mode; // bitmasked integer that selects which of the GPS and optical flow aiding sources will be used
control::BlockParamExtInt _vdist_sensor_type; // selects the primary source for height data
// range finder fusion
control::BlockParamExtFloat _range_noise; // observation noise for range finder measurements (m)
control::BlockParamExtFloat _range_innov_gate; // range finder fusion innovation consistency gate size (STD)
control::BlockParamExtFloat _rng_gnd_clearance; // minimum valid value for range when on ground (m)
control::BlockParamExtFloat _rng_pitch_offset; // range sensor pitch offset (rad)
// vision estimate fusion
control::BlockParamExtFloat _ev_pos_noise; // default position observation noise for exernal vision measurements (m)
control::BlockParamExtFloat _ev_ang_noise; // default angular observation noise for exernal vision measurements (rad)
control::BlockParamExtFloat _ev_innov_gate; // external vision position innovation consistency gate size (STD)
// optical flow fusion
control::BlockParamExtFloat
_flow_noise; // best quality observation noise for optical flow LOS rate measurements (rad/sec)
control::BlockParamExtFloat
_flow_noise_qual_min; // worst quality observation noise for optical flow LOS rate measurements (rad/sec)
control::BlockParamExtInt _flow_qual_min; // minimum acceptable quality integer from the flow sensor
control::BlockParamExtFloat _flow_innov_gate; // optical flow fusion innovation consistency gate size (STD)
control::BlockParamExtFloat _flow_rate_max; // maximum valid optical flow rate (rad/sec)
// sensor positions in body frame
control::BlockParamExtFloat _imu_pos_x; // X position of IMU in body frame (m)
control::BlockParamExtFloat _imu_pos_y; // Y position of IMU in body frame (m)
control::BlockParamExtFloat _imu_pos_z; // Z position of IMU in body frame (m)
control::BlockParamExtFloat _gps_pos_x; // X position of GPS antenna in body frame (m)
control::BlockParamExtFloat _gps_pos_y; // Y position of GPS antenna in body frame (m)
control::BlockParamExtFloat _gps_pos_z; // Z position of GPS antenna in body frame (m)
control::BlockParamExtFloat _rng_pos_x; // X position of range finder in body frame (m)
control::BlockParamExtFloat _rng_pos_y; // Y position of range finder in body frame (m)
control::BlockParamExtFloat _rng_pos_z; // Z position of range finder in body frame (m)
control::BlockParamExtFloat _flow_pos_x; // X position of optical flow sensor focal point in body frame (m)
control::BlockParamExtFloat _flow_pos_y; // Y position of optical flow sensor focal point in body frame (m)
control::BlockParamExtFloat _flow_pos_z; // Z position of optical flow sensor focal point in body frame (m)
control::BlockParamExtFloat _ev_pos_x; // X position of VI sensor focal point in body frame (m)
control::BlockParamExtFloat _ev_pos_y; // Y position of VI sensor focal point in body frame (m)
control::BlockParamExtFloat _ev_pos_z; // Z position of VI sensor focal point in body frame (m)
// control of airspeed and sideslip fusion
control::BlockParamFloat
_arspFusionThreshold; // a value of zero will disabled airspeed fusion. Any another positive value will determine
// the minimum airspeed which will still be fused
control::BlockParamInt _fuseBeta; // 0 disables synthetic sideslip fusion, 1 activates it
// output predictor filter time constants
control::BlockParamExtFloat _tau_vel; // time constant used by the output velocity complementary filter (s)
control::BlockParamExtFloat _tau_pos; // time constant used by the output position complementary filter (s)
// IMU switch on bias paameters
control::BlockParamExtFloat _gyr_bias_init; // 1-sigma gyro bias uncertainty at switch-on (rad/sec)
control::BlockParamExtFloat _acc_bias_init; // 1-sigma accelerometer bias uncertainty at switch-on (m/s**2)
control::BlockParamExtFloat _ang_err_init; // 1-sigma uncertainty in tilt angle after gravity vector alignment (rad)
// airspeed mode parameter
control::BlockParamInt _airspeed_mode;
int update_subscriptions();
};
Ekf2::Ekf2():
SuperBlock(nullptr, "EKF"),
_replay_mode(false),
_publish_replay_mode(0),
_att_pub(nullptr),
_lpos_pub(nullptr),
_control_state_pub(nullptr),
_vehicle_global_position_pub(nullptr),
_wind_pub(nullptr),
_estimator_status_pub(nullptr),
_estimator_innovations_pub(nullptr),
_replay_pub(nullptr),
_ekf2_timestamps_pub(nullptr),
_lp_roll_rate(250.0f, 30.0f),
_lp_pitch_rate(250.0f, 30.0f),
_lp_yaw_rate(250.0f, 20.0f),
_ekf(),
_params(_ekf.getParamHandle()),
_obs_dt_min_ms(this, "EKF2_MIN_OBS_DT", false, _params->sensor_interval_min_ms),
_mag_delay_ms(this, "EKF2_MAG_DELAY", false, _params->mag_delay_ms),
_baro_delay_ms(this, "EKF2_BARO_DELAY", false, _params->baro_delay_ms),
_gps_delay_ms(this, "EKF2_GPS_DELAY", false, _params->gps_delay_ms),
_flow_delay_ms(this, "EKF2_OF_DELAY", false, _params->flow_delay_ms),
_rng_delay_ms(this, "EKF2_RNG_DELAY", false, _params->range_delay_ms),
_airspeed_delay_ms(this, "EKF2_ASP_DELAY", false, _params->airspeed_delay_ms),
_ev_delay_ms(this, "EKF2_EV_DELAY", false, _params->ev_delay_ms),
_gyro_noise(this, "EKF2_GYR_NOISE", false, _params->gyro_noise),
_accel_noise(this, "EKF2_ACC_NOISE", false, _params->accel_noise),
_gyro_bias_p_noise(this, "EKF2_GYR_B_NOISE", false, _params->gyro_bias_p_noise),
_accel_bias_p_noise(this, "EKF2_ACC_B_NOISE", false, _params->accel_bias_p_noise),
_mage_p_noise(this, "EKF2_MAG_E_NOISE", false, _params->mage_p_noise),
_magb_p_noise(this, "EKF2_MAG_B_NOISE", false, _params->magb_p_noise),
_wind_vel_p_noise(this, "EKF2_WIND_NOISE", false, _params->wind_vel_p_noise),
_terrain_p_noise(this, "EKF2_TERR_NOISE", false, _params->terrain_p_noise),
_terrain_gradient(this, "EKF2_TERR_GRAD", false, _params->terrain_gradient),
_gps_vel_noise(this, "EKF2_GPS_V_NOISE", false, _params->gps_vel_noise),
_gps_pos_noise(this, "EKF2_GPS_P_NOISE", false, _params->gps_pos_noise),
_pos_noaid_noise(this, "EKF2_NOAID_NOISE", false, _params->pos_noaid_noise),
_baro_noise(this, "EKF2_BARO_NOISE", false, _params->baro_noise),
_baro_innov_gate(this, "EKF2_BARO_GATE", false, _params->baro_innov_gate),
_posNE_innov_gate(this, "EKF2_GPS_P_GATE", false, _params->posNE_innov_gate),
_vel_innov_gate(this, "EKF2_GPS_V_GATE", false, _params->vel_innov_gate),
_tas_innov_gate(this, "EKF2_TAS_GATE", false, _params->tas_innov_gate),
_mag_heading_noise(this, "EKF2_HEAD_NOISE", false, _params->mag_heading_noise),
_mag_noise(this, "EKF2_MAG_NOISE", false, _params->mag_noise),
_eas_noise(this, "EKF2_EAS_NOISE", false, _params->eas_noise),
_beta_noise(this, "EKF2_BETA_NOISE", false, _params->beta_noise),
_mag_declination_deg(this, "EKF2_MAG_DECL", false, _params->mag_declination_deg),
_heading_innov_gate(this, "EKF2_HDG_GATE", false, _params->heading_innov_gate),
_mag_innov_gate(this, "EKF2_MAG_GATE", false, _params->mag_innov_gate),
_mag_decl_source(this, "EKF2_DECL_TYPE", false, _params->mag_declination_source),
_mag_fuse_type(this, "EKF2_MAG_TYPE", false, _params->mag_fusion_type),
_gps_check_mask(this, "EKF2_GPS_CHECK", false, _params->gps_check_mask),
_requiredEph(this, "EKF2_REQ_EPH", false, _params->req_hacc),
_requiredEpv(this, "EKF2_REQ_EPV", false, _params->req_vacc),
_requiredSacc(this, "EKF2_REQ_SACC", false, _params->req_sacc),
_requiredNsats(this, "EKF2_REQ_NSATS", false, _params->req_nsats),
_requiredGDoP(this, "EKF2_REQ_GDOP", false, _params->req_gdop),
_requiredHdrift(this, "EKF2_REQ_HDRIFT", false, _params->req_hdrift),
_requiredVdrift(this, "EKF2_REQ_VDRIFT", false, _params->req_vdrift),
_param_record_replay_msg(this, "EKF2_REC_RPL", false, _publish_replay_mode),
_fusion_mode(this, "EKF2_AID_MASK", false, _params->fusion_mode),
_vdist_sensor_type(this, "EKF2_HGT_MODE", false, _params->vdist_sensor_type),
_range_noise(this, "EKF2_RNG_NOISE", false, _params->range_noise),
_range_innov_gate(this, "EKF2_RNG_GATE", false, _params->range_innov_gate),
_rng_gnd_clearance(this, "EKF2_MIN_RNG", false, _params->rng_gnd_clearance),
_rng_pitch_offset(this, "EKF2_RNG_PITCH", false, _params->rng_sens_pitch),
_ev_pos_noise(this, "EKF2_EVP_NOISE", false, _default_ev_pos_noise),
_ev_ang_noise(this, "EKF2_EVA_NOISE", false, _default_ev_ang_noise),
_ev_innov_gate(this, "EKF2_EV_GATE", false, _params->ev_innov_gate),
_flow_noise(this, "EKF2_OF_N_MIN", false, _params->flow_noise),
_flow_noise_qual_min(this, "EKF2_OF_N_MAX", false, _params->flow_noise_qual_min),
_flow_qual_min(this, "EKF2_OF_QMIN", false, _params->flow_qual_min),
_flow_innov_gate(this, "EKF2_OF_GATE", false, _params->flow_innov_gate),
_flow_rate_max(this, "EKF2_OF_RMAX", false, _params->flow_rate_max),
_imu_pos_x(this, "EKF2_IMU_POS_X", false, _params->imu_pos_body(0)),
_imu_pos_y(this, "EKF2_IMU_POS_Y", false, _params->imu_pos_body(1)),
_imu_pos_z(this, "EKF2_IMU_POS_Z", false, _params->imu_pos_body(2)),
_gps_pos_x(this, "EKF2_GPS_POS_X", false, _params->gps_pos_body(0)),
_gps_pos_y(this, "EKF2_GPS_POS_Y", false, _params->gps_pos_body(1)),
_gps_pos_z(this, "EKF2_GPS_POS_Z", false, _params->gps_pos_body(2)),
_rng_pos_x(this, "EKF2_RNG_POS_X", false, _params->rng_pos_body(0)),
_rng_pos_y(this, "EKF2_RNG_POS_Y", false, _params->rng_pos_body(1)),
_rng_pos_z(this, "EKF2_RNG_POS_Z", false, _params->rng_pos_body(2)),
_flow_pos_x(this, "EKF2_OF_POS_X", false, _params->flow_pos_body(0)),
_flow_pos_y(this, "EKF2_OF_POS_Y", false, _params->flow_pos_body(1)),
_flow_pos_z(this, "EKF2_OF_POS_Z", false, _params->flow_pos_body(2)),
_ev_pos_x(this, "EKF2_EV_POS_X", false, _params->ev_pos_body(0)),
_ev_pos_y(this, "EKF2_EV_POS_Y", false, _params->ev_pos_body(1)),
_ev_pos_z(this, "EKF2_EV_POS_Z", false, _params->ev_pos_body(2)),
_arspFusionThreshold(this, "EKF2_ARSP_THR", false),
_fuseBeta(this, "EKF2_FUSE_BETA", false),
_tau_vel(this, "EKF2_TAU_VEL", false, _params->vel_Tau),
_tau_pos(this, "EKF2_TAU_POS", false, _params->pos_Tau),
_gyr_bias_init(this, "EKF2_GBIAS_INIT", false, _params->switch_on_gyro_bias),
_acc_bias_init(this, "EKF2_ABIAS_INIT", false, _params->switch_on_accel_bias),
_ang_err_init(this, "EKF2_ANGERR_INIT", false, _params->initial_tilt_err),
_airspeed_mode(this, "FW_ARSP_MODE", false)
{
}
Ekf2::~Ekf2()
{
}
void Ekf2::print_status()
{
warnx("local position OK %s", (_ekf.local_position_is_valid()) ? "[YES]" : "[NO]");
warnx("global position OK %s", (_ekf.global_position_is_valid()) ? "[YES]" : "[NO]");
}
void Ekf2::task_main()
{
// subscribe to relevant topics
int sensors_sub = orb_subscribe(ORB_ID(sensor_combined));
int gps_sub = orb_subscribe(ORB_ID(vehicle_gps_position));
int airspeed_sub = orb_subscribe(ORB_ID(airspeed));
int params_sub = orb_subscribe(ORB_ID(parameter_update));
int optical_flow_sub = orb_subscribe(ORB_ID(optical_flow));
int range_finder_sub = orb_subscribe(ORB_ID(distance_sensor));
int ev_pos_sub = orb_subscribe(ORB_ID(vehicle_vision_position));
int ev_att_sub = orb_subscribe(ORB_ID(vehicle_vision_attitude));
int vehicle_land_detected_sub = orb_subscribe(ORB_ID(vehicle_land_detected));
int status_sub = orb_subscribe(ORB_ID(vehicle_status));
px4_pollfd_struct_t fds[2] = {};
fds[0].fd = sensors_sub;
fds[0].events = POLLIN;
fds[1].fd = params_sub;
fds[1].events = POLLIN;
// initialise parameter cache
updateParams();
// initialize data structures outside of loop
// because they will else not always be
// properly populated
sensor_combined_s sensors = {};
vehicle_gps_position_s gps = {};
airspeed_s airspeed = {};
optical_flow_s optical_flow = {};
distance_sensor_s range_finder = {};
vehicle_land_detected_s vehicle_land_detected = {};
vehicle_local_position_s ev_pos = {};
vehicle_attitude_s ev_att = {};
vehicle_status_s vehicle_status = {};
while (!_task_should_exit) {
int ret = px4_poll(fds, sizeof(fds) / sizeof(fds[0]), 1000);
if (ret < 0) {
// Poll error, sleep and try again
usleep(10000);
continue;
} else if (ret == 0) {
// Poll timeout or no new data, do nothing
continue;
}
if (fds[1].revents & POLLIN) {
// read from param to clear updated flag
struct parameter_update_s update;
orb_copy(ORB_ID(parameter_update), params_sub, &update);
updateParams();
// fetch sensor data in next loop
continue;
} else if (!(fds[0].revents & POLLIN)) {
// no new data
continue;
}
bool gps_updated = false;
bool airspeed_updated = false;
bool optical_flow_updated = false;
bool range_finder_updated = false;
bool vehicle_land_detected_updated = false;
bool vision_position_updated = false;
bool vision_attitude_updated = false;
bool vehicle_status_updated = false;
orb_copy(ORB_ID(sensor_combined), sensors_sub, &sensors);
// update all other topics if they have new data
orb_check(status_sub, &vehicle_status_updated);
if (vehicle_status_updated) {
orb_copy(ORB_ID(vehicle_status), status_sub, &vehicle_status);
}
orb_check(gps_sub, &gps_updated);
if (gps_updated) {
orb_copy(ORB_ID(vehicle_gps_position), gps_sub, &gps);
}
orb_check(airspeed_sub, &airspeed_updated);
if (airspeed_updated) {
orb_copy(ORB_ID(airspeed), airspeed_sub, &airspeed);
}
orb_check(optical_flow_sub, &optical_flow_updated);
if (optical_flow_updated) {
orb_copy(ORB_ID(optical_flow), optical_flow_sub, &optical_flow);
}
orb_check(range_finder_sub, &range_finder_updated);
if (range_finder_updated) {
orb_copy(ORB_ID(distance_sensor), range_finder_sub, &range_finder);
if (range_finder.min_distance > range_finder.current_distance
|| range_finder.max_distance < range_finder.current_distance) {
range_finder_updated = false;
}
}
orb_check(ev_pos_sub, &vision_position_updated);
if (vision_position_updated) {
orb_copy(ORB_ID(vehicle_vision_position), ev_pos_sub, &ev_pos);
}
orb_check(ev_att_sub, &vision_attitude_updated);
if (vision_attitude_updated) {
orb_copy(ORB_ID(vehicle_vision_attitude), ev_att_sub, &ev_att);
}
// in replay mode we are getting the actual timestamp from the sensor topic
hrt_abstime now = 0;
if (_replay_mode) {
now = sensors.timestamp;
} else {
now = hrt_absolute_time();
}
// push imu data into estimator
float gyro_integral[3];
gyro_integral[0] = sensors.gyro_rad[0] * sensors.gyro_integral_dt;
gyro_integral[1] = sensors.gyro_rad[1] * sensors.gyro_integral_dt;
gyro_integral[2] = sensors.gyro_rad[2] * sensors.gyro_integral_dt;
float accel_integral[3];
accel_integral[0] = sensors.accelerometer_m_s2[0] * sensors.accelerometer_integral_dt;
accel_integral[1] = sensors.accelerometer_m_s2[1] * sensors.accelerometer_integral_dt;
accel_integral[2] = sensors.accelerometer_m_s2[2] * sensors.accelerometer_integral_dt;
_ekf.setIMUData(now, sensors.gyro_integral_dt * 1.e6f, sensors.accelerometer_integral_dt * 1.e6f,
gyro_integral, accel_integral);
// read mag data
if (sensors.magnetometer_timestamp_relative == sensor_combined_s::RELATIVE_TIMESTAMP_INVALID) {
// set a zero timestamp to let the ekf replay program know that this data is not valid
_timestamp_mag_us = 0;
} else {
if ((sensors.timestamp + sensors.magnetometer_timestamp_relative) != _timestamp_mag_us) {
_timestamp_mag_us = sensors.timestamp + sensors.magnetometer_timestamp_relative;
// If the time last used by the EKF is less than specified, then accumulate the
// data and push the average when the 50msec is reached.
_mag_time_sum_ms += _timestamp_mag_us / 1000;
_mag_sample_count++;
_mag_data_sum[0] += sensors.magnetometer_ga[0];
_mag_data_sum[1] += sensors.magnetometer_ga[1];
_mag_data_sum[2] += sensors.magnetometer_ga[2];
uint32_t mag_time_ms = _mag_time_sum_ms / _mag_sample_count;
if (mag_time_ms - _mag_time_ms_last_used > _params->sensor_interval_min_ms) {
float mag_sample_count_inv = 1.0f / (float)_mag_sample_count;
float mag_data_avg_ga[3] = {_mag_data_sum[0] *mag_sample_count_inv, _mag_data_sum[1] *mag_sample_count_inv, _mag_data_sum[2] *mag_sample_count_inv};
_ekf.setMagData(1000 * (uint64_t)mag_time_ms, mag_data_avg_ga);
_mag_time_ms_last_used = mag_time_ms;
_mag_time_sum_ms = 0;
_mag_sample_count = 0;
_mag_data_sum[0] = 0.0f;
_mag_data_sum[1] = 0.0f;
_mag_data_sum[2] = 0.0f;
}
}
}
// read baro data
if (sensors.baro_timestamp_relative == sensor_combined_s::RELATIVE_TIMESTAMP_INVALID) {
// set a zero timestamp to let the ekf replay program know that this data is not valid
_timestamp_balt_us = 0;
} else {
if ((sensors.timestamp + sensors.baro_timestamp_relative) != _timestamp_balt_us) {
_timestamp_balt_us = sensors.timestamp + sensors.baro_timestamp_relative;
// If the time last used by the EKF is less than specified, then accumulate the
// data and push the average when the 50msec is reached.
_balt_time_sum_ms += _timestamp_balt_us / 1000;
_balt_sample_count++;
_balt_data_sum += sensors.baro_alt_meter;
uint32_t balt_time_ms = _balt_time_sum_ms / _balt_sample_count;
if (balt_time_ms - _balt_time_ms_last_used > (uint32_t)_params->sensor_interval_min_ms) {
float balt_data_avg = _balt_data_sum / (float)_balt_sample_count;
_ekf.setBaroData(1000 * (uint64_t)balt_time_ms, balt_data_avg);
_balt_time_ms_last_used = balt_time_ms;
_balt_time_sum_ms = 0;
_balt_sample_count = 0;
_balt_data_sum = 0.0f;
}
}
}
// read gps data if available
if (gps_updated) {
struct gps_message gps_msg = {};
gps_msg.time_usec = gps.timestamp;
gps_msg.lat = gps.lat;
gps_msg.lon = gps.lon;
gps_msg.alt = gps.alt;
gps_msg.fix_type = gps.fix_type;
gps_msg.eph = gps.eph;
gps_msg.epv = gps.epv;
gps_msg.sacc = gps.s_variance_m_s;
gps_msg.vel_m_s = gps.vel_m_s;
gps_msg.vel_ned[0] = gps.vel_n_m_s;
gps_msg.vel_ned[1] = gps.vel_e_m_s;
gps_msg.vel_ned[2] = gps.vel_d_m_s;
gps_msg.vel_ned_valid = gps.vel_ned_valid;
gps_msg.nsats = gps.satellites_used;
//TODO add gdop to gps topic
gps_msg.gdop = 0.0f;
_ekf.setGpsData(gps.timestamp, &gps_msg);
}
// only set airspeed data if condition for airspeed fusion are met
bool fuse_airspeed = airspeed_updated && !vehicle_status.is_rotary_wing
&& _arspFusionThreshold.get() <= airspeed.true_airspeed_m_s && _arspFusionThreshold.get() >= 0.1f;
if (fuse_airspeed) {
float eas2tas = airspeed.true_airspeed_m_s / airspeed.indicated_airspeed_m_s;
_ekf.setAirspeedData(airspeed.timestamp, airspeed.true_airspeed_m_s, eas2tas);
}
// only fuse synthetic sideslip measurements if conditions are met
bool fuse_beta = !vehicle_status.is_rotary_wing && _fuseBeta.get();
_ekf.set_fuse_beta_flag(fuse_beta);
if (optical_flow_updated) {
flow_message flow;
flow.flowdata(0) = optical_flow.pixel_flow_x_integral;
flow.flowdata(1) = optical_flow.pixel_flow_y_integral;
flow.quality = optical_flow.quality;
flow.gyrodata(0) = optical_flow.gyro_x_rate_integral;
flow.gyrodata(1) = optical_flow.gyro_y_rate_integral;
flow.gyrodata(2) = optical_flow.gyro_z_rate_integral;
flow.dt = optical_flow.integration_timespan;
if (PX4_ISFINITE(optical_flow.pixel_flow_y_integral) &&
PX4_ISFINITE(optical_flow.pixel_flow_x_integral)) {
_ekf.setOpticalFlowData(optical_flow.timestamp, &flow);
}
}
if (range_finder_updated) {
_ekf.setRangeData(range_finder.timestamp, range_finder.current_distance);
}
// get external vision data
// if error estimates are unavailable, use parameter defined defaults
if (vision_position_updated || vision_attitude_updated) {
ext_vision_message ev_data;
ev_data.posNED(0) = ev_pos.x;
ev_data.posNED(1) = ev_pos.y;
ev_data.posNED(2) = ev_pos.z;
Quaternion q(ev_att.q);
ev_data.quat = q;
// position measurement error from parameters. TODO : use covariances from topic
ev_data.posErr = _default_ev_pos_noise;
ev_data.angErr = _default_ev_ang_noise;
// use timestamp from external computer, clocks are synchronized when using MAVROS
_ekf.setExtVisionData(vision_position_updated ? ev_pos.timestamp : ev_att.timestamp, &ev_data);
}
orb_check(vehicle_land_detected_sub, &vehicle_land_detected_updated);
if (vehicle_land_detected_updated) {
orb_copy(ORB_ID(vehicle_land_detected), vehicle_land_detected_sub, &vehicle_land_detected);
_ekf.set_in_air_status(!vehicle_land_detected.landed);
}
// run the EKF update and output
if (_ekf.update()) {
matrix::Quaternion<float> q;
_ekf.copy_quaternion(q.data());
float velocity[3];
_ekf.get_velocity(velocity);
float gyro_rad[3];
{
// generate control state data
control_state_s ctrl_state = {};
float gyro_bias[3] = {};
_ekf.get_gyro_bias(gyro_bias);
ctrl_state.timestamp = _replay_mode ? now : hrt_absolute_time();
gyro_rad[0] = sensors.gyro_rad[0] - gyro_bias[0];
gyro_rad[1] = sensors.gyro_rad[1] - gyro_bias[1];
gyro_rad[2] = sensors.gyro_rad[2] - gyro_bias[2];
ctrl_state.roll_rate = _lp_roll_rate.apply(gyro_rad[0]);
ctrl_state.pitch_rate = _lp_pitch_rate.apply(gyro_rad[1]);
ctrl_state.yaw_rate = _lp_yaw_rate.apply(gyro_rad[2]);
ctrl_state.roll_rate_bias = gyro_bias[0];
ctrl_state.pitch_rate_bias = gyro_bias[1];
ctrl_state.yaw_rate_bias = gyro_bias[2];
// Velocity in body frame
Vector3f v_n(velocity);
matrix::Dcm<float> R_to_body(q.inversed());
Vector3f v_b = R_to_body * v_n;
ctrl_state.x_vel = v_b(0);
ctrl_state.y_vel = v_b(1);
ctrl_state.z_vel = v_b(2);
// Local Position NED
float position[3];
_ekf.get_position(position);
ctrl_state.x_pos = position[0];
ctrl_state.y_pos = position[1];
ctrl_state.z_pos = position[2];
// Attitude quaternion
q.copyTo(ctrl_state.q);
_ekf.get_quat_reset(&ctrl_state.delta_q_reset[0], &ctrl_state.quat_reset_counter);
// Acceleration data
matrix::Vector<float, 3> acceleration(sensors.accelerometer_m_s2);
float accel_bias[3];
_ekf.get_accel_bias(accel_bias);
ctrl_state.x_acc = acceleration(0) - accel_bias[0];
ctrl_state.y_acc = acceleration(1) - accel_bias[1];
ctrl_state.z_acc = acceleration(2) - accel_bias[2];
// compute lowpass filtered horizontal acceleration
acceleration = R_to_body.transpose() * acceleration;
_acc_hor_filt = 0.95f * _acc_hor_filt + 0.05f * sqrtf(acceleration(0) * acceleration(0) +
acceleration(1) * acceleration(1));
ctrl_state.horz_acc_mag = _acc_hor_filt;
ctrl_state.airspeed_valid = false;
// use estimated velocity for airspeed estimate
if (_airspeed_mode.get() == control_state_s::AIRSPD_MODE_MEAS) {
// use measured airspeed
if (PX4_ISFINITE(airspeed.indicated_airspeed_m_s) && hrt_absolute_time() - airspeed.timestamp < 1e6
&& airspeed.timestamp > 0) {
ctrl_state.airspeed = airspeed.indicated_airspeed_m_s;
ctrl_state.airspeed_valid = true;
}
} else if (_airspeed_mode.get() == control_state_s::AIRSPD_MODE_EST) {
if (_ekf.local_position_is_valid()) {
ctrl_state.airspeed = sqrtf(velocity[0] * velocity[0] + velocity[1] * velocity[1] + velocity[2] * velocity[2]);
ctrl_state.airspeed_valid = true;
}
} else if (_airspeed_mode.get() == control_state_s::AIRSPD_MODE_DISABLED) {
// do nothing, airspeed has been declared as non-valid above, controllers
// will handle this assuming always trim airspeed
}
// publish control state data
if (_control_state_pub == nullptr) {
_control_state_pub = orb_advertise(ORB_ID(control_state), &ctrl_state);
} else {
orb_publish(ORB_ID(control_state), _control_state_pub, &ctrl_state);
}
}
{
// generate vehicle attitude quaternion data
struct vehicle_attitude_s att = {};
att.timestamp = _replay_mode ? now : hrt_absolute_time();
q.copyTo(att.q);
att.rollspeed = gyro_rad[0];
att.pitchspeed = gyro_rad[1];
att.yawspeed = gyro_rad[2];
// publish vehicle attitude data
if (_att_pub == nullptr) {
_att_pub = orb_advertise(ORB_ID(vehicle_attitude), &att);
} else {
orb_publish(ORB_ID(vehicle_attitude), _att_pub, &att);
}
}
// generate vehicle local position data
struct vehicle_local_position_s lpos = {};
float pos[3] = {};
lpos.timestamp = _replay_mode ? now : hrt_absolute_time();
// Position of body origin in local NED frame
_ekf.get_position(pos);
lpos.x = (_ekf.local_position_is_valid()) ? pos[0] : 0.0f;
lpos.y = (_ekf.local_position_is_valid()) ? pos[1] : 0.0f;
lpos.z = pos[2];
// Velocity of body origin in local NED frame (m/s)
lpos.vx = velocity[0];
lpos.vy = velocity[1];
lpos.vz = velocity[2];
// TODO: better status reporting
lpos.xy_valid = _ekf.local_position_is_valid();
lpos.z_valid = true;
lpos.v_xy_valid = _ekf.local_position_is_valid();
lpos.v_z_valid = true;
// Position of local NED origin in GPS / WGS84 frame
struct map_projection_reference_s ekf_origin = {};
// true if position (x,y,z) has a valid WGS-84 global reference (ref_lat, ref_lon, alt)
lpos.xy_global = lpos.z_global = _ekf.get_ekf_origin(&lpos.ref_timestamp, &ekf_origin, &lpos.ref_alt);
lpos.ref_lat = ekf_origin.lat_rad * 180.0 / M_PI; // Reference point latitude in degrees
lpos.ref_lon = ekf_origin.lon_rad * 180.0 / M_PI; // Reference point longitude in degrees
// The rotation of the tangent plane vs. geographical north
matrix::Eulerf euler(q);
lpos.yaw = euler.psi();
float terrain_vpos;
lpos.dist_bottom_valid = _ekf.get_terrain_vert_pos(&terrain_vpos);
lpos.dist_bottom = terrain_vpos - pos[2]; // Distance to bottom surface (ground) in meters
lpos.dist_bottom_rate = -velocity[2]; // Distance to bottom surface (ground) change rate
lpos.surface_bottom_timestamp = hrt_absolute_time(); // Time when new bottom surface found
bool dead_reckoning;
_ekf.get_ekf_lpos_accuracy(&lpos.eph, &lpos.epv, &dead_reckoning);
_ekf.get_ekf_vel_accuracy(&lpos.evh, &lpos.evv, &dead_reckoning);
// get state reset information of position and velocity
_ekf.get_posD_reset(&lpos.delta_z, &lpos.z_reset_counter);
_ekf.get_velD_reset(&lpos.delta_vz, &lpos.vz_reset_counter);
_ekf.get_posNE_reset(&lpos.delta_xy[0], &lpos.xy_reset_counter);
_ekf.get_velNE_reset(&lpos.delta_vxy[0], &lpos.vxy_reset_counter);
// publish vehicle local position data
if (_lpos_pub == nullptr) {
_lpos_pub = orb_advertise(ORB_ID(vehicle_local_position), &lpos);
} else {
orb_publish(ORB_ID(vehicle_local_position), _lpos_pub, &lpos);
}
if (_ekf.global_position_is_valid()) {
// generate and publish global position data
struct vehicle_global_position_s global_pos = {};
global_pos.timestamp = _replay_mode ? now : hrt_absolute_time();
global_pos.time_utc_usec = gps.time_utc_usec; // GPS UTC timestamp in microseconds
double est_lat, est_lon, lat_pre_reset, lon_pre_reset;
map_projection_reproject(&ekf_origin, lpos.x, lpos.y, &est_lat, &est_lon);
global_pos.lat = est_lat; // Latitude in degrees
global_pos.lon = est_lon; // Longitude in degrees
map_projection_reproject(&ekf_origin, lpos.x - lpos.delta_xy[0], lpos.y - lpos.delta_xy[1], &lat_pre_reset,
&lon_pre_reset);
global_pos.delta_lat_lon[0] = est_lat - lat_pre_reset;
global_pos.delta_lat_lon[1] = est_lon - lon_pre_reset;
global_pos.lat_lon_reset_counter = lpos.xy_reset_counter;
global_pos.alt = -pos[2] + lpos.ref_alt; // Altitude AMSL in meters
_ekf.get_posD_reset(&global_pos.delta_alt, &global_pos.alt_reset_counter);
// global altitude has opposite sign of local down position
global_pos.delta_alt *= -1.0f;
global_pos.vel_n = velocity[0]; // Ground north velocity, m/s
global_pos.vel_e = velocity[1]; // Ground east velocity, m/s
global_pos.vel_d = velocity[2]; // Ground downside velocity, m/s
global_pos.yaw = euler.psi(); // Yaw in radians -PI..+PI.
_ekf.get_ekf_gpos_accuracy(&global_pos.eph, &global_pos.epv, &global_pos.dead_reckoning);
global_pos.evh = lpos.evh;
global_pos.evv = lpos.evv;
if (lpos.dist_bottom_valid) {
global_pos.terrain_alt = lpos.ref_alt - terrain_vpos; // Terrain altitude in m, WGS84
global_pos.terrain_alt_valid = true; // Terrain altitude estimate is valid
} else {
global_pos.terrain_alt = 0.0f; // Terrain altitude in m, WGS84
global_pos.terrain_alt_valid = false; // Terrain altitude estimate is valid
}
global_pos.dead_reckoning = _ekf.inertial_dead_reckoning(); // True if this position is estimated through dead-reckoning
global_pos.pressure_alt = sensors.baro_alt_meter; // Pressure altitude AMSL (m)
if (_vehicle_global_position_pub == nullptr) {
_vehicle_global_position_pub = orb_advertise(ORB_ID(vehicle_global_position), &global_pos);
} else {
orb_publish(ORB_ID(vehicle_global_position), _vehicle_global_position_pub, &global_pos);
}
}
} else if (_replay_mode) {
// in replay mode we have to tell the replay module not to wait for an update
// we do this by publishing an attitude with zero timestamp
struct vehicle_attitude_s att = {};
att.timestamp = now;
if (_att_pub == nullptr) {
_att_pub = orb_advertise(ORB_ID(vehicle_attitude), &att);
} else {
orb_publish(ORB_ID(vehicle_attitude), _att_pub, &att);
}
}
// publish estimator status
struct estimator_status_s status = {};
status.timestamp = _replay_mode ? now : hrt_absolute_time();
_ekf.get_state_delayed(status.states);
_ekf.get_covariances(status.covariances);
_ekf.get_gps_check_status(&status.gps_check_fail_flags);
_ekf.get_control_mode(&status.control_mode_flags);
_ekf.get_filter_fault_status(&status.filter_fault_flags);
_ekf.get_innovation_test_status(&status.innovation_check_flags, &status.mag_test_ratio,
&status.vel_test_ratio, &status.pos_test_ratio,
&status.hgt_test_ratio, &status.tas_test_ratio,
&status.hagl_test_ratio);
bool dead_reckoning;
_ekf.get_ekf_lpos_accuracy(&status.pos_horiz_accuracy, &status.pos_vert_accuracy, &dead_reckoning);
_ekf.get_ekf_soln_status(&status.solution_status_flags);
_ekf.get_imu_vibe_metrics(status.vibe);
if (_estimator_status_pub == nullptr) {
_estimator_status_pub = orb_advertise(ORB_ID(estimator_status), &status);
} else {
orb_publish(ORB_ID(estimator_status), _estimator_status_pub, &status);
}
// Publish wind estimate
struct wind_estimate_s wind_estimate = {};
wind_estimate.timestamp = _replay_mode ? now : hrt_absolute_time();
wind_estimate.windspeed_north = status.states[22];
wind_estimate.windspeed_east = status.states[23];
wind_estimate.covariance_north = status.covariances[22];
wind_estimate.covariance_east = status.covariances[23];
if (_wind_pub == nullptr) {
_wind_pub = orb_advertise(ORB_ID(wind_estimate), &wind_estimate);
} else {
orb_publish(ORB_ID(wind_estimate), _wind_pub, &wind_estimate);
}
// publish estimator innovation data
{
struct ekf2_innovations_s innovations = {};
innovations.timestamp = _replay_mode ? now : hrt_absolute_time();
_ekf.get_vel_pos_innov(&innovations.vel_pos_innov[0]);
_ekf.get_mag_innov(&innovations.mag_innov[0]);
_ekf.get_heading_innov(&innovations.heading_innov);
_ekf.get_airspeed_innov(&innovations.airspeed_innov);
_ekf.get_beta_innov(&innovations.beta_innov);
_ekf.get_flow_innov(&innovations.flow_innov[0]);
_ekf.get_hagl_innov(&innovations.hagl_innov);
_ekf.get_vel_pos_innov_var(&innovations.vel_pos_innov_var[0]);
_ekf.get_mag_innov_var(&innovations.mag_innov_var[0]);
_ekf.get_heading_innov_var(&innovations.heading_innov_var);
_ekf.get_airspeed_innov_var(&innovations.airspeed_innov_var);
_ekf.get_beta_innov_var(&innovations.beta_innov_var);
_ekf.get_flow_innov_var(&innovations.flow_innov_var[0]);
_ekf.get_hagl_innov_var(&innovations.hagl_innov_var);
_ekf.get_output_tracking_error(&innovations.output_tracking_error[0]);
if (_estimator_innovations_pub == nullptr) {
_estimator_innovations_pub = orb_advertise(ORB_ID(ekf2_innovations), &innovations);
} else {
orb_publish(ORB_ID(ekf2_innovations), _estimator_innovations_pub, &innovations);
}
}
// save the declination to the EKF2_MAG_DECL parameter when a land event is detected
if ((_params->mag_declination_source & (1 << 1)) && !_prev_landed && vehicle_land_detected.landed) {
float decl_deg;
_ekf.copy_mag_decl_deg(&decl_deg);
_mag_declination_deg.set(decl_deg);
}
_prev_landed = vehicle_land_detected.landed;
// publish ekf2_timestamps (using 0.1 ms relative timestamps)
{
ekf2_timestamps_s ekf2_timestamps;
ekf2_timestamps.timestamp = sensors.timestamp;
if (gps_updated) {
// divide individually to get consistent rounding behavior
ekf2_timestamps.gps_timestamp_rel = (int16_t)((int64_t)gps.timestamp / 100 - (int64_t)ekf2_timestamps.timestamp / 100);
} else {
ekf2_timestamps.gps_timestamp_rel = ekf2_timestamps_s::RELATIVE_TIMESTAMP_INVALID;
}
if (optical_flow_updated) {
ekf2_timestamps.optical_flow_timestamp_rel = (int16_t)((int64_t)optical_flow.timestamp / 100 -
(int64_t)ekf2_timestamps.timestamp / 100);
} else {
ekf2_timestamps.optical_flow_timestamp_rel = ekf2_timestamps_s::RELATIVE_TIMESTAMP_INVALID;
}
if (range_finder_updated) {
ekf2_timestamps.distance_sensor_timestamp_rel = (int16_t)((int64_t)range_finder.timestamp / 100 -
(int64_t)ekf2_timestamps.timestamp / 100);
} else {
ekf2_timestamps.distance_sensor_timestamp_rel = ekf2_timestamps_s::RELATIVE_TIMESTAMP_INVALID;
}
if (airspeed_updated) {
ekf2_timestamps.airspeed_timestamp_rel = (int16_t)((int64_t)airspeed.timestamp / 100 -
(int64_t)ekf2_timestamps.timestamp / 100);
} else {
ekf2_timestamps.airspeed_timestamp_rel = ekf2_timestamps_s::RELATIVE_TIMESTAMP_INVALID;
}
if (vision_position_updated) {
ekf2_timestamps.vision_position_timestamp_rel = (int16_t)((int64_t)ev_pos.timestamp / 100 -
(int64_t)ekf2_timestamps.timestamp / 100);
} else {
ekf2_timestamps.vision_position_timestamp_rel = ekf2_timestamps_s::RELATIVE_TIMESTAMP_INVALID;
}
if (vision_attitude_updated) {
ekf2_timestamps.vision_attitude_timestamp_rel = (int16_t)((int64_t)ev_att.timestamp / 100 -
(int64_t)ekf2_timestamps.timestamp / 100);
} else {
ekf2_timestamps.vision_attitude_timestamp_rel = ekf2_timestamps_s::RELATIVE_TIMESTAMP_INVALID;
}
if (_ekf2_timestamps_pub == nullptr) {
_ekf2_timestamps_pub = orb_advertise(ORB_ID(ekf2_timestamps), &ekf2_timestamps);
} else {
orb_publish(ORB_ID(ekf2_timestamps), _ekf2_timestamps_pub, &ekf2_timestamps);
}
}
// publish replay message if in replay mode
bool publish_replay_message = (bool)_param_record_replay_msg.get();
if (publish_replay_message) {
struct ekf2_replay_s replay = {};
replay.timestamp = now;
replay.gyro_integral_dt = sensors.gyro_integral_dt;
replay.accelerometer_integral_dt = sensors.accelerometer_integral_dt;
replay.magnetometer_timestamp = _timestamp_mag_us;
replay.baro_timestamp = _timestamp_balt_us;
memcpy(replay.gyro_rad, sensors.gyro_rad, sizeof(replay.gyro_rad));
memcpy(replay.accelerometer_m_s2, sensors.accelerometer_m_s2, sizeof(replay.accelerometer_m_s2));
memcpy(replay.magnetometer_ga, sensors.magnetometer_ga, sizeof(replay.magnetometer_ga));
replay.baro_alt_meter = sensors.baro_alt_meter;
// only write gps data if we had a gps update.
if (gps_updated) {
replay.time_usec = gps.timestamp;
replay.lat = gps.lat;
replay.lon = gps.lon;
replay.alt = gps.alt;
replay.fix_type = gps.fix_type;
replay.nsats = gps.satellites_used;
replay.eph = gps.eph;
replay.epv = gps.epv;
replay.sacc = gps.s_variance_m_s;
replay.vel_m_s = gps.vel_m_s;
replay.vel_n_m_s = gps.vel_n_m_s;
replay.vel_e_m_s = gps.vel_e_m_s;
replay.vel_d_m_s = gps.vel_d_m_s;
replay.vel_ned_valid = gps.vel_ned_valid;
} else {
// this will tell the logging app not to bother logging any gps replay data
replay.time_usec = 0;
}
if (optical_flow_updated) {
replay.flow_timestamp = optical_flow.timestamp;
replay.flow_pixel_integral[0] = optical_flow.pixel_flow_x_integral;
replay.flow_pixel_integral[1] = optical_flow.pixel_flow_y_integral;
replay.flow_gyro_integral[0] = optical_flow.gyro_x_rate_integral;
replay.flow_gyro_integral[1] = optical_flow.gyro_y_rate_integral;
replay.flow_time_integral = optical_flow.integration_timespan;
replay.flow_quality = optical_flow.quality;
} else {
replay.flow_timestamp = 0;
}
if (range_finder_updated) {
replay.rng_timestamp = range_finder.timestamp;
replay.range_to_ground = range_finder.current_distance;
} else {
replay.rng_timestamp = 0;
}
if (airspeed_updated) {
replay.asp_timestamp = airspeed.timestamp;
replay.indicated_airspeed_m_s = airspeed.indicated_airspeed_m_s;
replay.true_airspeed_m_s = airspeed.true_airspeed_m_s;
} else {
replay.asp_timestamp = 0;
}
if (vision_position_updated || vision_attitude_updated) {
replay.ev_timestamp = vision_position_updated ? ev_pos.timestamp : ev_att.timestamp;
replay.pos_ev[0] = ev_pos.x;
replay.pos_ev[1] = ev_pos.y;
replay.pos_ev[2] = ev_pos.z;
replay.quat_ev[0] = ev_att.q[0];
replay.quat_ev[1] = ev_att.q[1];
replay.quat_ev[2] = ev_att.q[2];
replay.quat_ev[3] = ev_att.q[3];
// TODO : switch to covariances from topic later
replay.pos_err = _default_ev_pos_noise;
replay.ang_err = _default_ev_ang_noise;
} else {
replay.ev_timestamp = 0;
}
if (_replay_pub == nullptr) {
_replay_pub = orb_advertise(ORB_ID(ekf2_replay), &replay);
} else {
orb_publish(ORB_ID(ekf2_replay), _replay_pub, &replay);
}
}
}
orb_unsubscribe(sensors_sub);
orb_unsubscribe(gps_sub);
orb_unsubscribe(airspeed_sub);
orb_unsubscribe(params_sub);
orb_unsubscribe(optical_flow_sub);
orb_unsubscribe(range_finder_sub);
orb_unsubscribe(ev_pos_sub);
orb_unsubscribe(vehicle_land_detected_sub);
orb_unsubscribe(status_sub);
delete ekf2::instance;
ekf2::instance = nullptr;
}
void Ekf2::task_main_trampoline(int argc, char *argv[])
{
ekf2::instance->task_main();
}
int Ekf2::start()
{
ASSERT(_control_task == -1);
/* start the task */
_control_task = px4_task_spawn_cmd("ekf2",
SCHED_DEFAULT,
SCHED_PRIORITY_MAX - 5,
5800,
(px4_main_t)&Ekf2::task_main_trampoline,
nullptr);
if (_control_task < 0) {
PX4_WARN("task start failed");
return -errno;
}
return OK;
}
int ekf2_main(int argc, char *argv[])
{
if (argc < 2) {
PX4_WARN("usage: ekf2 {start|stop|status}");
return 1;
}
if (!strcmp(argv[1], "start")) {
if (ekf2::instance != nullptr) {
PX4_WARN("already running");
return 1;
}
ekf2::instance = new Ekf2();
if (ekf2::instance == nullptr) {
PX4_WARN("alloc failed");
return 1;
}
if (argc >= 3) {
if (!strcmp(argv[2], "--replay")) {
ekf2::instance->set_replay_mode(true);
}
}
if (OK != ekf2::instance->start()) {
delete ekf2::instance;
ekf2::instance = nullptr;
PX4_WARN("start failed");
return 1;
}
return 0;
}
if (!strcmp(argv[1], "stop")) {
if (ekf2::instance == nullptr) {
PX4_WARN("not running");
return 1;
}
ekf2::instance->exit();
// wait for the destruction of the instance
while (ekf2::instance != nullptr) {
usleep(50000);
}
return 0;
}
if (!strcmp(argv[1], "print")) {
if (ekf2::instance != nullptr) {
return 0;
}
return 1;
}
if (!strcmp(argv[1], "status")) {
if (ekf2::instance) {
PX4_WARN("running");
ekf2::instance->print_status();
return 0;
} else {
PX4_WARN("not running");
return 1;
}
}
PX4_WARN("unrecognized command");
return 1;
}
Reference in New Issue View Git Blame Copy Permalink