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515 lines
15 KiB
C++
515 lines
15 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2019-2020 PX4 Development Team. 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 PX4 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 sih.cpp
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* Simulator in Hardware
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*
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* @author Romain Chiappinelli <romain.chiap@gmail.com>
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*
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* Coriolis g Corporation - January 2019
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*/
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#include "sih.hpp"
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#include <px4_platform_common/getopt.h>
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#include <px4_platform_common/log.h>
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#include <drivers/drv_pwm_output.h> // to get PWM flags
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using namespace math;
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using namespace matrix;
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using namespace time_literals;
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Sih::Sih() :
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ModuleParams(nullptr),
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ScheduledWorkItem(MODULE_NAME, px4::wq_configurations::rate_ctrl)
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{
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_px4_accel.set_temperature(T1_C);
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_px4_gyro.set_temperature(T1_C);
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_px4_mag.set_temperature(T1_C);
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parameters_updated();
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init_variables();
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gps_no_fix();
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const hrt_abstime task_start = hrt_absolute_time();
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_last_run = task_start;
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_gps_time = task_start;
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_serial_time = task_start;
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_dist_snsr_time = task_start;
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}
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Sih::~Sih()
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{
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perf_free(_loop_perf);
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perf_free(_loop_interval_perf);
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}
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bool Sih::init()
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{
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int rate = _imu_gyro_ratemax.get();
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// default to 250 Hz (4000 us interval)
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if (rate <= 0) {
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rate = 250;
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}
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// 200 - 2000 Hz
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int interval_us = math::constrain(int(roundf(1e6f / rate)), 500, 5000);
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ScheduleOnInterval(interval_us);
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return true;
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}
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void Sih::Run()
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{
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perf_count(_loop_interval_perf);
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// check for parameter updates
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if (_parameter_update_sub.updated()) {
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// clear update
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parameter_update_s pupdate;
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_parameter_update_sub.copy(&pupdate);
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// update parameters from storage
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updateParams();
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parameters_updated();
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}
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perf_begin(_loop_perf);
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_now = hrt_absolute_time();
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_dt = (_now - _last_run) * 1e-6f;
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_last_run = _now;
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read_motors();
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generate_force_and_torques();
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equations_of_motion();
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reconstruct_sensors_signals();
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// update IMU every iteration
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_px4_accel.update(_now, _acc(0), _acc(1), _acc(2));
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_px4_gyro.update(_now, _gyro(0), _gyro(1), _gyro(2));
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// magnetometer published at 50 Hz
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if (_now - _mag_time >= 20_ms
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&& fabs(_mag_offset_x) < 10000
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&& fabs(_mag_offset_y) < 10000
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&& fabs(_mag_offset_z) < 10000) {
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_mag_time = _now;
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_px4_mag.update(_now, _mag(0), _mag(1), _mag(2));
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}
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// baro published at 20 Hz
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if (_now - _baro_time >= 50_ms
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&& fabs(_baro_offset_m) < 10000) {
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_baro_time = _now;
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_px4_baro.set_temperature(_baro_temp_c);
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_px4_baro.update(_now, _baro_p_mBar);
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}
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// gps published at 20Hz
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if (_now - _gps_time >= 50_ms) {
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_gps_time = _now;
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send_gps();
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}
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// distance sensor published at 50 Hz
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if (_now - _dist_snsr_time >= 20_ms) {
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_dist_snsr_time = _now;
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send_dist_snsr();
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}
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// send uart message every 40 ms
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if (_now - _serial_time >= 40_ms) {
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_serial_time = _now;
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publish_sih(); // publish _sih message for debug purpose
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}
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perf_end(_loop_perf);
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}
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// store the parameters in a more convenient form
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void Sih::parameters_updated()
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{
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_T_MAX = _sih_t_max.get();
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_Q_MAX = _sih_q_max.get();
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_L_ROLL = _sih_l_roll.get();
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_L_PITCH = _sih_l_pitch.get();
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_KDV = _sih_kdv.get();
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_KDW = _sih_kdw.get();
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_H0 = _sih_h0.get();
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_LAT0 = (double)_sih_lat0.get() * 1.0e-7;
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_LON0 = (double)_sih_lon0.get() * 1.0e-7;
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_COS_LAT0 = cosl((long double)radians(_LAT0));
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_MASS = _sih_mass.get();
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_W_I = Vector3f(0.0f, 0.0f, _MASS * CONSTANTS_ONE_G);
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_I = diag(Vector3f(_sih_ixx.get(), _sih_iyy.get(), _sih_izz.get()));
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_I(0, 1) = _I(1, 0) = _sih_ixy.get();
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_I(0, 2) = _I(2, 0) = _sih_ixz.get();
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_I(1, 2) = _I(2, 1) = _sih_iyz.get();
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_Im1 = inv(_I);
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_mu_I = Vector3f(_sih_mu_x.get(), _sih_mu_y.get(), _sih_mu_z.get());
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_gps_used = _sih_gps_used.get();
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_baro_offset_m = _sih_baro_offset.get();
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_mag_offset_x = _sih_mag_offset_x.get();
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_mag_offset_y = _sih_mag_offset_y.get();
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_mag_offset_z = _sih_mag_offset_z.get();
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_distance_snsr_min = _sih_distance_snsr_min.get();
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_distance_snsr_max = _sih_distance_snsr_max.get();
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}
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// initialization of the variables for the simulator
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void Sih::init_variables()
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{
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srand(1234); // initialize the random seed once before calling generate_wgn()
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_p_I = Vector3f(0.0f, 0.0f, 0.0f);
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_v_I = Vector3f(0.0f, 0.0f, 0.0f);
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_q = Quatf(1.0f, 0.0f, 0.0f, 0.0f);
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_w_B = Vector3f(0.0f, 0.0f, 0.0f);
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_u[0] = _u[1] = _u[2] = _u[3] = 0.0f;
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}
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void Sih::gps_fix()
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{
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_sensor_gps.fix_type = 3; // 3D fix
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_sensor_gps.satellites_used = _gps_used;
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_sensor_gps.heading = NAN;
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_sensor_gps.heading_offset = NAN;
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_sensor_gps.s_variance_m_s = 0.5f;
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_sensor_gps.c_variance_rad = 0.1f;
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_sensor_gps.eph = 0.9f;
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_sensor_gps.epv = 1.78f;
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_sensor_gps.hdop = 0.7f;
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_sensor_gps.vdop = 1.1f;
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}
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void Sih::gps_no_fix()
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{
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_sensor_gps.fix_type = 0; // 3D fix
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_sensor_gps.satellites_used = _gps_used;
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_sensor_gps.heading = NAN;
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_sensor_gps.heading_offset = NAN;
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_sensor_gps.s_variance_m_s = 100.f;
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_sensor_gps.c_variance_rad = 100.f;
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_sensor_gps.eph = 100.f;
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_sensor_gps.epv = 100.f;
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_sensor_gps.hdop = 100.f;
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_sensor_gps.vdop = 100.f;
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}
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// read the motor signals outputted from the mixer
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void Sih::read_motors()
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{
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actuator_outputs_s actuators_out;
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if (_actuator_out_sub.update(&actuators_out)) {
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for (int i = 0; i < NB_MOTORS; i++) { // saturate the motor signals
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_u[i] = constrain((actuators_out.output[i] - PWM_DEFAULT_MIN) / (PWM_DEFAULT_MAX - PWM_DEFAULT_MIN), 0.0f, 1.0f);
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}
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}
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}
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// generate the motors thrust and torque in the body frame
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void Sih::generate_force_and_torques()
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{
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_T_B = Vector3f(0.0f, 0.0f, -_T_MAX * (+_u[0] + _u[1] + _u[2] + _u[3]));
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_Mt_B = Vector3f(_L_ROLL * _T_MAX * (-_u[0] + _u[1] + _u[2] - _u[3]),
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_L_PITCH * _T_MAX * (+_u[0] - _u[1] + _u[2] - _u[3]),
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_Q_MAX * (+_u[0] + _u[1] - _u[2] - _u[3]));
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_Fa_I = -_KDV * _v_I; // first order drag to slow down the aircraft
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_Ma_B = -_KDW * _w_B; // first order angular damper
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}
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// apply the equations of motion of a rigid body and integrate one step
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void Sih::equations_of_motion()
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{
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_C_IB = matrix::Dcm<float>(_q); // body to inertial transformation
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// Equations of motion of a rigid body
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_p_I_dot = _v_I; // position differential
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_v_I_dot = (_W_I + _Fa_I + _C_IB * _T_B) / _MASS; // conservation of linear momentum
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_q_dot = _q.derivative1(_w_B); // attitude differential
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_w_B_dot = _Im1 * (_Mt_B + _Ma_B - _w_B.cross(_I * _w_B)); // conservation of angular momentum
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// fake ground, avoid free fall
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if (_p_I(2) > 0.0f && (_v_I_dot(2) > 0.0f || _v_I(2) > 0.0f)) {
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if (!_grounded) { // if we just hit the floor
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// for the accelerometer, compute the acceleration that will stop the vehicle in one time step
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_v_I_dot = -_v_I / _dt;
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} else {
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_v_I_dot.setZero();
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}
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_v_I.setZero();
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_w_B.setZero();
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_grounded = true;
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} else {
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// integration: Euler forward
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_p_I = _p_I + _p_I_dot * _dt;
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_v_I = _v_I + _v_I_dot * _dt;
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_q = _q + _q_dot * _dt; // as given in attitude_estimator_q_main.cpp
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_q.normalize();
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_w_B = _w_B + _w_B_dot * _dt;
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_grounded = false;
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}
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}
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// reconstruct the noisy sensor signals
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void Sih::reconstruct_sensors_signals()
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{
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// The sensor signals reconstruction and noise levels are from
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// Bulka, Eitan, and Meyer Nahon. "Autonomous fixed-wing aerobatics: from theory to flight."
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// In 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 6573-6580. IEEE, 2018.
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// IMU
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_acc = _C_IB.transpose() * (_v_I_dot - Vector3f(0.0f, 0.0f, CONSTANTS_ONE_G)) + noiseGauss3f(0.5f, 1.7f, 1.4f);
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_gyro = _w_B + noiseGauss3f(0.14f, 0.07f, 0.03f);
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_mag = _C_IB.transpose() * _mu_I + noiseGauss3f(0.02f, 0.02f, 0.03f);
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_mag(0) += _mag_offset_x;
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_mag(1) += _mag_offset_y;
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_mag(2) += _mag_offset_z;
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// barometer
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float altitude = (_H0 - _p_I(2)) + _baro_offset_m + generate_wgn() * 0.14f; // altitude with noise
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_baro_p_mBar = CONSTANTS_STD_PRESSURE_MBAR * // reconstructed pressure in mBar
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powf((1.0f + altitude * TEMP_GRADIENT / T1_K), -CONSTANTS_ONE_G / (TEMP_GRADIENT * CONSTANTS_AIR_GAS_CONST));
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_baro_temp_c = T1_K + CONSTANTS_ABSOLUTE_NULL_CELSIUS + TEMP_GRADIENT * altitude; // reconstructed temperture in celcius
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// GPS
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_gps_lat_noiseless = _LAT0 + degrees((double)_p_I(0) / CONSTANTS_RADIUS_OF_EARTH);
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_gps_lon_noiseless = _LON0 + degrees((double)_p_I(1) / CONSTANTS_RADIUS_OF_EARTH) / _COS_LAT0;
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_gps_alt_noiseless = _H0 - _p_I(2);
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_gps_lat = _gps_lat_noiseless + (double)(generate_wgn() * 7.2e-6f); // latitude in degrees
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_gps_lon = _gps_lon_noiseless + (double)(generate_wgn() * 1.75e-5f); // longitude in degrees
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_gps_alt = _gps_alt_noiseless + generate_wgn() * 1.78f;
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_gps_vel = _v_I + noiseGauss3f(0.06f, 0.077f, 0.158f);
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}
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void Sih::send_gps()
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{
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_sensor_gps.timestamp = _now;
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_sensor_gps.lat = (int32_t)(_gps_lat * 1e7); // Latitude in 1E-7 degrees
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_sensor_gps.lon = (int32_t)(_gps_lon * 1e7); // Longitude in 1E-7 degrees
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_sensor_gps.alt = (int32_t)(_gps_alt * 1000.0f); // Altitude in 1E-3 meters above MSL, (millimetres)
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_sensor_gps.alt_ellipsoid = (int32_t)(_gps_alt * 1000); // Altitude in 1E-3 meters bove Ellipsoid, (millimetres)
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_sensor_gps.vel_ned_valid = true; // True if NED velocity is valid
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_sensor_gps.vel_m_s = sqrtf(_gps_vel(0) * _gps_vel(0) + _gps_vel(1) * _gps_vel(
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1)); // GPS ground speed, (metres/sec)
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_sensor_gps.vel_n_m_s = _gps_vel(0); // GPS North velocity, (metres/sec)
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_sensor_gps.vel_e_m_s = _gps_vel(1); // GPS East velocity, (metres/sec)
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_sensor_gps.vel_d_m_s = _gps_vel(2); // GPS Down velocity, (metres/sec)
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_sensor_gps.cog_rad = atan2(_gps_vel(1),
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_gps_vel(0)); // Course over ground (NOT heading, but direction of movement), -PI..PI, (radians)
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if (_gps_used >= 4) {
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gps_fix();
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} else {
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gps_no_fix();
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}
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_sensor_gps_pub.publish(_sensor_gps);
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}
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void Sih::send_dist_snsr()
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{
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_distance_snsr.timestamp = _now;
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_distance_snsr.type = distance_sensor_s::MAV_DISTANCE_SENSOR_LASER;
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_distance_snsr.orientation = distance_sensor_s::ROTATION_DOWNWARD_FACING;
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_distance_snsr.min_distance = _distance_snsr_min;
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_distance_snsr.max_distance = _distance_snsr_max;
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_distance_snsr.signal_quality = -1;
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_distance_snsr.device_id = 0;
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_distance_snsr.current_distance = -_p_I(2) / _C_IB(2, 2);
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if (_distance_snsr.current_distance > _distance_snsr_max) {
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// this is based on lightware lw20 behavior
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_distance_snsr.current_distance = UINT16_MAX / 100.f;
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}
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_distance_snsr_pub.publish(_distance_snsr);
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}
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void Sih::publish_sih()
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{
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// publish angular velocity groundtruth
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_vehicle_angular_velocity_gt.timestamp = hrt_absolute_time();
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_vehicle_angular_velocity_gt.xyz[0] = _w_B(0); // rollspeed;
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_vehicle_angular_velocity_gt.xyz[1] = _w_B(1); // pitchspeed;
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_vehicle_angular_velocity_gt.xyz[2] = _w_B(2); // yawspeed;
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_vehicle_angular_velocity_gt_pub.publish(_vehicle_angular_velocity_gt);
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// publish attitude groundtruth
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_att_gt.timestamp = hrt_absolute_time();
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_att_gt.q[0] = _q(0);
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_att_gt.q[1] = _q(1);
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_att_gt.q[2] = _q(2);
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_att_gt.q[3] = _q(3);
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_att_gt_pub.publish(_att_gt);
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_gpos_gt.timestamp = hrt_absolute_time();
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_gpos_gt.lat = _gps_lat_noiseless;
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_gpos_gt.lon = _gps_lon_noiseless;
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_gpos_gt.alt = _gps_alt_noiseless;
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_gpos_gt_pub.publish(_gpos_gt);
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}
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float Sih::generate_wgn() // generate white Gaussian noise sample with std=1
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{
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// algorithm 1:
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// float temp=((float)(rand()+1))/(((float)RAND_MAX+1.0f));
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// return sqrtf(-2.0f*logf(temp))*cosf(2.0f*M_PI_F*rand()/RAND_MAX);
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// algorithm 2: from BlockRandGauss.hpp
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static float V1, V2, S;
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static bool phase = true;
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float X;
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if (phase) {
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do {
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float U1 = (float)rand() / RAND_MAX;
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float U2 = (float)rand() / RAND_MAX;
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V1 = 2.0f * U1 - 1.0f;
|
|
V2 = 2.0f * U2 - 1.0f;
|
|
S = V1 * V1 + V2 * V2;
|
|
} while (S >= 1.0f || fabsf(S) < 1e-8f);
|
|
|
|
X = V1 * float(sqrtf(-2.0f * float(logf(S)) / S));
|
|
|
|
} else {
|
|
X = V2 * float(sqrtf(-2.0f * float(logf(S)) / S));
|
|
}
|
|
|
|
phase = !phase;
|
|
return X;
|
|
}
|
|
|
|
// generate white Gaussian noise sample vector with specified std
|
|
Vector3f Sih::noiseGauss3f(float stdx, float stdy, float stdz)
|
|
{
|
|
return Vector3f(generate_wgn() * stdx, generate_wgn() * stdy, generate_wgn() * stdz);
|
|
}
|
|
|
|
int Sih::task_spawn(int argc, char *argv[])
|
|
{
|
|
Sih *instance = new Sih();
|
|
|
|
if (instance) {
|
|
_object.store(instance);
|
|
_task_id = task_id_is_work_queue;
|
|
|
|
if (instance->init()) {
|
|
return PX4_OK;
|
|
}
|
|
|
|
} else {
|
|
PX4_ERR("alloc failed");
|
|
}
|
|
|
|
delete instance;
|
|
_object.store(nullptr);
|
|
_task_id = -1;
|
|
|
|
return PX4_ERROR;
|
|
}
|
|
|
|
int Sih::custom_command(int argc, char *argv[])
|
|
{
|
|
return print_usage("unknown command");
|
|
}
|
|
|
|
int Sih::print_usage(const char *reason)
|
|
{
|
|
if (reason) {
|
|
PX4_WARN("%s\n", reason);
|
|
}
|
|
|
|
PRINT_MODULE_DESCRIPTION(
|
|
R"DESCR_STR(
|
|
### Description
|
|
This module provide a simulator for quadrotors running fully
|
|
inside the hardware autopilot.
|
|
|
|
This simulator subscribes to "actuator_outputs" which are the actuator pwm
|
|
signals given by the mixer.
|
|
|
|
This simulator publishes the sensors signals corrupted with realistic noise
|
|
in order to incorporate the state estimator in the loop.
|
|
|
|
### Implementation
|
|
The simulator implements the equations of motion using matrix algebra.
|
|
Quaternion representation is used for the attitude.
|
|
Forward Euler is used for integration.
|
|
Most of the variables are declared global in the .hpp file to avoid stack overflow.
|
|
|
|
|
|
)DESCR_STR");
|
|
|
|
PRINT_MODULE_USAGE_NAME("sih", "simulation");
|
|
PRINT_MODULE_USAGE_COMMAND("start");
|
|
PRINT_MODULE_USAGE_DEFAULT_COMMANDS();
|
|
|
|
return 0;
|
|
}
|
|
|
|
extern "C" __EXPORT int sih_main(int argc, char *argv[])
|
|
{
|
|
return Sih::main(argc, argv);
|
|
}
|