2021-02-23 12:57:40 -05:00

515 lines
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C++

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