/** ****************************************************************************** * @addtogroup AHRS AHRS * @brief The AHRS Modules perform * * @{ * @addtogroup AHRS_Main * @brief Main function which does the hardware dependent stuff * @{ * * * @file ahrs.c * @author The OpenPilot Team, http://www.openpilot.org Copyright (C) 2010. * @brief INSGPS Test Program * @see The GNU Public License (GPL) Version 3 * *****************************************************************************/ /* * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * for more details. * * You should have received a copy of the GNU General Public License along * with this program; if not, write to the Free Software Foundation, Inc., * 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA */ /* OpenPilot Includes */ #include "ahrs.h" #include "ahrs_adc.h" #include "ahrs_timer.h" #include "ahrs_spi_comm.h" #include "insgps.h" #include "CoordinateConversions.h" #define MAX_OVERSAMPLING 50 /* cannot have more than 50 samples */ #define INSGPS_GPS_TIMEOUT 2 /* 2 seconds triggers reinit of position */ #define INSGPS_GPS_MINSAT 6 /* 2 seconds triggers reinit of position */ #define INSGPS_GPS_MINPDOP 3.5 /* minimum PDOP for postition updates */ #define INSGPS_MAGLEN 1000 #define INSGPS_MAGTOL 0.5 /* error in magnetic vector length to use */ // For debugging the raw sensors //#define DUMP_RAW //#define DUMP_FRIENDLY #define DUMP_EKF volatile int8_t ahrs_algorithm; /* INS functions */ void ins_outdoor_update(); void ins_indoor_update(); void simple_update(); /* Data accessors */ void downsample_data(void); void process_mag_data(); void reset_values(); void calibrate_sensors(void); /* Communication functions */ void send_calibration(void); void send_attitude(void); void send_velocity(void); void send_position(void); void homelocation_callback(AhrsObjHandle obj); void altitude_callback(AhrsObjHandle obj); void calibration_callback(AhrsObjHandle obj); void gps_callback(AhrsObjHandle obj); void settings_callback(AhrsObjHandle obj); /** * @addtogroup AHRS_Global_Data AHRS Global Data * @{ * Public data. Used by both EKF and the sender */ //! Filter coefficients used in decimation. Limited order so filter can't run between samples int16_t fir_coeffs[MAX_OVERSAMPLING]; //! Contains the data from the mag sensor chip struct mag_sensor mag_data; //! Contains the data from the accelerometer struct accel_sensor accel_data; //! Contains the data from the gyro struct gyro_sensor gyro_data; //! Conains the current estimate of the attitude struct attitude_solution attitude_data; //! Contains data from the altitude sensor struct altitude_sensor altitude_data; //! Contains data from the GPS (via the SPI link) struct gps_sensor gps_data; //! The oversampling rate, ekf is 2k / this static uint8_t adc_oversampling = 20; //! Offset correction of barometric alt, to match gps data static float baro_offset = 0; /** * @} */ /* INS functions */ /** * @brief Update the EKF when in outdoor mode. The primary difference is using the GPS values. */ void ins_outdoor_update() { float gyro[3], accel[3], vel[3]; static uint32_t last_gps_time = 0; uint16_t sensors; // format data for INS algo gyro[0] = gyro_data.filtered.x; gyro[1] = gyro_data.filtered.y; gyro[2] = gyro_data.filtered.z; accel[0] = accel_data.filtered.x, accel[1] = accel_data.filtered.y, accel[2] = accel_data.filtered.z, INSStatePrediction(gyro, accel, 1 / (float)EKF_RATE); attitude_data.quaternion.q1 = Nav.q[0]; attitude_data.quaternion.q2 = Nav.q[1]; attitude_data.quaternion.q3 = Nav.q[2]; attitude_data.quaternion.q4 = Nav.q[3]; send_attitude(); // get message out quickly send_velocity(); send_position(); INSCovariancePrediction(1 / (float)EKF_RATE); sensors = 0; /* * Detect if greater than certain time since last gps update and if so * reset EKF to that position since probably drifted too far for safe * update */ uint32_t this_gps_time = timer_count(); float gps_delay; if (this_gps_time < last_gps_time) gps_delay = ((0xFFFF - last_gps_time) - this_gps_time) / timer_rate(); else gps_delay = (this_gps_time - last_gps_time) / timer_rate(); last_gps_time = this_gps_time; if (gps_data.updated) { vel[0] = gps_data.groundspeed * cos(gps_data.heading * M_PI / 180); vel[1] = gps_data.groundspeed * sin(gps_data.heading * M_PI / 180); vel[2] = 0; if(gps_delay > INSGPS_GPS_TIMEOUT) INSPosVelReset(gps_data.NED,vel); // position stale, reset else { sensors |= HORIZ_SENSORS | POS_SENSORS; } /* When doing outdoor update grab this variance */ AHRSCalibrationData cal; AHRSCalibrationGet(&cal); INSSetPosVelVar(cal.pos_var, cal.vel_var); /* * When using gps need to make sure that barometer is brought into NED frame * we should try and see if the altitude from the home location is good enough * to use for the offset but for now starting with this conservative filter */ if(fabs(gps_data.NED[2] + (altitude_data.altitude - baro_offset)) > 10) { baro_offset = gps_data.NED[2] + altitude_data.altitude; } else { /* IIR filter with 100 second or so tau to keep them crudely in the same frame */ baro_offset = baro_offset * 0.999 + (gps_data.NED[2] + altitude_data.altitude) * 0.001; } gps_data.updated = false; } else if (gps_delay > INSGPS_GPS_TIMEOUT) { vel[0] = 0; vel[1] = 0; vel[2] = 0; sensors |= VERT_SENSORS | HORIZ_SENSORS; } if(mag_data.updated) { sensors |= MAG_SENSORS; mag_data.updated = false; } if(altitude_data.updated) { sensors |= BARO_SENSOR; altitude_data.updated = false; } /* * TODO: Need to add a general sanity check for all the inputs to make sure their kosher * although probably should occur within INS itself */ INSCorrection(mag_data.scaled.axis, gps_data.NED, vel, altitude_data.altitude - baro_offset, sensors); } /** * @brief Update the EKF when in indoor mode */ void ins_indoor_update() { float gyro[3], accel[3], vel[3]; static uint32_t last_indoor_time = 0; uint16_t sensors = 0; // format data for INS algo gyro[0] = gyro_data.filtered.x; gyro[1] = gyro_data.filtered.y; gyro[2] = gyro_data.filtered.z; accel[0] = accel_data.filtered.x, accel[1] = accel_data.filtered.y, accel[2] = accel_data.filtered.z, INSStatePrediction(gyro, accel, 1 / (float)EKF_RATE); attitude_data.quaternion.q1 = Nav.q[0]; attitude_data.quaternion.q2 = Nav.q[1]; attitude_data.quaternion.q3 = Nav.q[2]; attitude_data.quaternion.q4 = Nav.q[3]; send_attitude(); // get message out quickly send_velocity(); send_position(); INSCovariancePrediction(1 / (float)EKF_RATE); /* Indoors, update with zero position and velocity and high covariance */ vel[0] = 0; vel[1] = 0; vel[2] = 0; uint32_t this_indoor_time = timer_count(); float indoor_delay; /* * Detect if greater than certain time since last gps update and if so * reset EKF to that position since probably drifted too far for safe * update */ if (this_indoor_time < last_indoor_time) indoor_delay = ((0xFFFF - last_indoor_time) - this_indoor_time) / timer_rate(); else indoor_delay = (this_indoor_time - last_indoor_time) / timer_rate(); last_indoor_time = this_indoor_time; if(indoor_delay > INSGPS_GPS_TIMEOUT) INSPosVelReset(vel,vel); else sensors = HORIZ_SENSORS | VERT_SENSORS | POS_SENSORS; AHRSCalibrationData cal; AHRSCalibrationGet(&cal); INSSetPosVelVar(10, cal.vel_var); if(mag_data.updated && (ahrs_algorithm == AHRSSETTINGS_ALGORITHM_INSGPS_INDOOR)) { sensors |= MAG_SENSORS; mag_data.updated = false; } if(altitude_data.updated) { sensors |= BARO_SENSOR; altitude_data.updated = false; } /* * TODO: Need to add a general sanity check for all the inputs to make sure their kosher * although probably should occur within INS itself */ INSCorrection(mag_data.scaled.axis, vel, vel, altitude_data.altitude, sensors | HORIZ_SENSORS | VERT_SENSORS); } /** * @brief Initialize the EKF assuming stationary */ void ins_init_algorithm() { float Rbe[3][3], q[4], accels[3], rpy[3], mag; float ge[3]={0,0,-9.81}, zeros[3]={0,0,0}, Pdiag[13]={25,25,25,5,5,5,1e-5,1e-5,1e-5,1e-5,1e-5,1e-5,1e-5}; bool using_mags, using_gps; INSGPSInit(); HomeLocationData home; HomeLocationGet(&home); accels[0]=accel_data.filtered.x; accels[1]=accel_data.filtered.y; accels[2]=accel_data.filtered.z; using_mags = (ahrs_algorithm == AHRSSETTINGS_ALGORITHM_INSGPS_OUTDOOR) || (ahrs_algorithm == AHRSSETTINGS_ALGORITHM_INSGPS_INDOOR); using_mags &= (home.Be[0] != 0) || (home.Be[1] != 0) || (home.Be[2] != 0); /* only use mags when valid home location */ using_gps = (ahrs_algorithm == AHRSSETTINGS_ALGORITHM_INSGPS_OUTDOOR) && (gps_data.quality != 0); if (using_mags){ RotFrom2Vectors(accels, ge, mag_data.scaled.axis, home.Be, Rbe); R2Quaternion(Rbe,q); if (using_gps) INSSetState(gps_data.NED, zeros, q, zeros); else INSSetState(zeros, zeros, q, zeros); } else{ // assume yaw = 0 mag = VectorMagnitude(accels); rpy[1] = asinf(-accels[0]/mag); rpy[0] = atan2(accels[1]/mag,accels[2]/mag); rpy[2] = 0; RPY2Quaternion(rpy,q); if (using_gps) INSSetState(gps_data.NED, zeros, q, zeros); else INSSetState(zeros, zeros, q, zeros); } INSResetP(Pdiag); // TODO: include initial estimate of gyro bias? } /** * @brief Simple update using just mag and accel. Yaw biased and big attitude changes. */ void simple_update() { float q[4]; float rpy[3]; /***************** SIMPLE ATTITUDE FROM NORTH AND ACCEL ************/ /* Very simple computation of the heading and attitude from accel. */ rpy[2] = atan2((mag_data.raw.axis[0]), (-1 * mag_data.raw.axis[1])) * 180 / M_PI; rpy[1] = atan2(accel_data.filtered.x, accel_data.filtered.z) * 180 / M_PI; rpy[0] = atan2(accel_data.filtered.y, accel_data.filtered.z) * 180 / M_PI; RPY2Quaternion(rpy, q); attitude_data.quaternion.q1 = q[0]; attitude_data.quaternion.q2 = q[1]; attitude_data.quaternion.q3 = q[2]; attitude_data.quaternion.q4 = q[3]; send_attitude(); } /** * @brief Output all the important inputs and states of the ekf through serial port */ #ifdef DUMP_EKF #define NUMX 13 // number of states, X is the state vector #define NUMW 9 // number of plant noise inputs, w is disturbance noise vector #define NUMV 10 // number of measurements, v is the measurement noise vector #define NUMU 7 // number of deterministic inputs, U is the input vector extern float F[NUMX][NUMX], G[NUMX][NUMW], H[NUMV][NUMX]; // linearized system matrices extern float P[NUMX][NUMX], X[NUMX]; // covariance matrix and state vector extern float Q[NUMW], R[NUMV]; // input noise and measurement noise variances extern float K[NUMX][NUMV]; // feedback gain matrix void print_ekf_binary() { uint8_t framing[16] = { 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0 }; // Dump raw buffer PIOS_COM_SendBuffer(PIOS_COM_AUX, &framing[0], 16); // framing header (1:16) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & total_conversion_blocks, sizeof(total_conversion_blocks)); // dump block number (17:20) PIOS_COM_SendBufferNonBlocking(PIOS_COM_AUX, (uint8_t *) & accel_data.filtered.x, 4*3); // accel data (21:32) PIOS_COM_SendBufferNonBlocking(PIOS_COM_AUX, (uint8_t *) & gyro_data.filtered.x, 4*3); // gyro data (33:44) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & mag_data.updated, 1); // mag update (45) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & mag_data.scaled.axis, 3*4); // mag data (46:57) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & gps_data, sizeof(gps_data)); // gps data (58:85) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & X, 4 * NUMX); // X (86:137) for(uint8_t i = 0; i < NUMX; i++) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) &(P[i][i]), 4); // diag(P) (138:189) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & altitude_data.altitude, 4); // BaroAlt (190:193) PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & baro_offset, 4); // baro_offset (194:198) } #else void print_ekf_binary() {} #endif /** * @brief Debugging function to output all the ADC samples */ void print_ahrs_raw() { int result; static int previous_conversion = 0; uint8_t framing[16] = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 }; while (ahrs_state != AHRS_DATA_READY) ; ahrs_state = AHRS_PROCESSING; if (total_conversion_blocks != previous_conversion + 1) PIOS_LED_On(LED1); // not keeping up else PIOS_LED_Off(LED1); previous_conversion = total_conversion_blocks; downsample_data(); ahrs_state = AHRS_IDLE;; // Dump raw buffer result = PIOS_COM_SendBuffer(PIOS_COM_AUX, &framing[0], 16); // framing header result += PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & total_conversion_blocks, sizeof(total_conversion_blocks)); // dump block number result += PIOS_COM_SendBuffer(PIOS_COM_AUX, (uint8_t *) & valid_data_buffer[0], adc_oversampling * PIOS_ADC_NUM_PINS * sizeof(valid_data_buffer[0])); if (result == 0) PIOS_LED_Off(LED1); else { PIOS_LED_On(LED1); } } /** * @brief AHRS Main function */ int main() { gps_data.quality = -1; uint32_t up_time_real = 0; uint32_t up_time = 0; uint32_t last_up_time = 0; static int8_t last_ahrs_algorithm; uint32_t last_counter_idle_start = 0; uint32_t last_counter_idle_end = 0; uint32_t idle_counts = 0; uint32_t running_counts = 0; uint32_t counter_val = 0; ahrs_algorithm = AHRSSETTINGS_ALGORITHM_SIMPLE; /* Brings up System using CMSIS functions, enables the LEDs. */ PIOS_SYS_Init(); /* Delay system */ PIOS_DELAY_Init(); /* Communication system */ PIOS_COM_Init(); /* ADC system */ AHRS_ADC_Config(adc_oversampling); /* Setup the Accelerometer FS (Full-Scale) GPIO */ PIOS_GPIO_Enable(0); SET_ACCEL_6G; #if defined(PIOS_INCLUDE_HMC5843) && defined(PIOS_INCLUDE_I2C) /* Magnetic sensor system */ PIOS_I2C_Init(); PIOS_HMC5843_Init(); // Get 3 ID bytes strcpy((char *)mag_data.id, "ZZZ"); PIOS_HMC5843_ReadID(mag_data.id); #endif reset_values(); ahrs_state = AHRS_IDLE; AhrsInitComms(); ahrs_state = AHRS_IDLE; while(!AhrsLinkReady()) { AhrsPoll(); while(ahrs_state != AHRS_DATA_READY) ; ahrs_state = AHRS_PROCESSING; downsample_data(); ahrs_state = AHRS_IDLE; if((total_conversion_blocks % 10) == 0) PIOS_LED_Toggle(LED1); } /* we didn't connect the callbacks before because we have to wait for all data to be up to date before doing anything*/ AHRSCalibrationConnectCallback(calibration_callback); GPSPositionConnectCallback(gps_callback); BaroAltitudeConnectCallback(altitude_callback); AHRSSettingsConnectCallback(settings_callback); HomeLocationConnectCallback(homelocation_callback); calibration_callback(AHRSCalibrationHandle()); //force an update /* Use simple averaging filter for now */ for (int i = 0; i < adc_oversampling; i++) fir_coeffs[i] = 1; fir_coeffs[adc_oversampling] = adc_oversampling; #ifdef DUMP_RAW while (1) { AhrsPoll(); print_ahrs_raw(); } #endif timer_start(); /******************* Main EKF loop ****************************/ while(1) { AhrsPoll(); AhrsStatusData status; AhrsStatusGet(&status); status.CPULoad = ((float)running_counts / (float)(idle_counts + running_counts)) * 100; status.IdleTimePerCyle = idle_counts / (timer_rate() / 10000); status.RunningTimePerCyle = running_counts / (timer_rate() / 10000); status.DroppedUpdates = ekf_too_slow; up_time = timer_count(); if(up_time >= last_up_time) // normal condition up_time_real += ((up_time - last_up_time) * 1000) / timer_rate(); else up_time_real += ((0xFFFF - last_up_time + up_time) * 1000) / timer_rate(); last_up_time = up_time; status.RunningTime = up_time_real; AhrsStatusSet(&status); // Alive signal if ((total_conversion_blocks % 100) == 0) PIOS_LED_Toggle(LED1); // Delay for valid data counter_val = timer_count(); running_counts = counter_val - last_counter_idle_end; last_counter_idle_start = counter_val; while (ahrs_state != AHRS_DATA_READY); ahrs_state = AHRS_PROCESSING; counter_val = timer_count(); idle_counts = counter_val - last_counter_idle_start; last_counter_idle_end = counter_val; downsample_data(); process_mag_data(); print_ekf_binary(); /* If algorithm changed reinit. This could go in callback but wouldn't be synchronous */ if (ahrs_algorithm != last_ahrs_algorithm) ins_init_algorithm(); last_ahrs_algorithm = ahrs_algorithm; switch(ahrs_algorithm) { case AHRSSETTINGS_ALGORITHM_SIMPLE: simple_update(); break; case AHRSSETTINGS_ALGORITHM_INSGPS_OUTDOOR: ins_outdoor_update(); break; case AHRSSETTINGS_ALGORITHM_INSGPS_INDOOR: case AHRSSETTINGS_ALGORITHM_INSGPS_INDOOR_NOMAG: ins_indoor_update(); break; } ahrs_state = AHRS_IDLE; } return 0; } /** * @brief Downsample the analog data * @return none * * Tried to make as much of the filtering fixed point when possible. Need to account * for offset for each sample before the multiplication if filter not a boxcar. Could * precompute fixed offset as sum[fir_coeffs[i]] * ACCEL_OFFSET. Puts data into global * data structures @ref accel_data and @ref gyro_data. * * The accel_data values are converted into a coordinate system where X is forwards along * the fuselage, Y is along right the wing, and Z is down. */ void downsample_data() { uint16_t i; // Get the Y data. Third byte in. Convert to m/s accel_data.filtered.y = 0; for (i = 0; i < adc_oversampling; i++) accel_data.filtered.y += valid_data_buffer[0 + i * PIOS_ADC_NUM_PINS] * fir_coeffs[i]; accel_data.filtered.y /= (float) fir_coeffs[adc_oversampling]; accel_data.filtered.y = (accel_data.filtered.y * accel_data.calibration.scale[1]) + accel_data.calibration.bias[1]; // Get the X data which projects forward/backwards. Fifth byte in. Convert to m/s accel_data.filtered.x = 0; for (i = 0; i < adc_oversampling; i++) accel_data.filtered.x += valid_data_buffer[2 + i * PIOS_ADC_NUM_PINS] * fir_coeffs[i]; accel_data.filtered.x /= (float) fir_coeffs[adc_oversampling]; accel_data.filtered.x = (accel_data.filtered.x * accel_data.calibration.scale[0]) + accel_data.calibration.bias[0]; // Get the Z data. Third byte in. Convert to m/s accel_data.filtered.z = 0; for (i = 0; i < adc_oversampling; i++) accel_data.filtered.z += valid_data_buffer[4 + i * PIOS_ADC_NUM_PINS] * fir_coeffs[i]; accel_data.filtered.z /= (float) fir_coeffs[adc_oversampling]; accel_data.filtered.z = (accel_data.filtered.z * accel_data.calibration.scale[2]) + accel_data.calibration.bias[2]; // Get the X gyro data. Seventh byte in. Convert to deg/s. gyro_data.filtered.x = 0; for (i = 0; i < adc_oversampling; i++) gyro_data.filtered.x += valid_data_buffer[1 + i * PIOS_ADC_NUM_PINS] * fir_coeffs[i]; gyro_data.filtered.x /= fir_coeffs[adc_oversampling]; gyro_data.filtered.x = (gyro_data.filtered.x * gyro_data.calibration.scale[0]) + gyro_data.calibration.bias[0]; // Get the Y gyro data. Second byte in. Convert to deg/s. gyro_data.filtered.y = 0; for (i = 0; i < adc_oversampling; i++) gyro_data.filtered.y += valid_data_buffer[3 + i * PIOS_ADC_NUM_PINS] * fir_coeffs[i]; gyro_data.filtered.y /= fir_coeffs[adc_oversampling]; gyro_data.filtered.y = (gyro_data.filtered.y * gyro_data.calibration.scale[1]) + gyro_data.calibration.bias[1]; // Get the Z gyro data. Fifth byte in. Convert to deg/s. gyro_data.filtered.z = 0; for (i = 0; i < adc_oversampling; i++) gyro_data.filtered.z += valid_data_buffer[5 + i * PIOS_ADC_NUM_PINS] * fir_coeffs[i]; gyro_data.filtered.z /= fir_coeffs[adc_oversampling]; gyro_data.filtered.z = (gyro_data.filtered.z * gyro_data.calibration.scale[2]) + gyro_data.calibration.bias[2]; AttitudeRawData raw; raw.gyros[0] = valid_data_buffer[1]; raw.gyros[1] = valid_data_buffer[3]; raw.gyros[2] = valid_data_buffer[5]; raw.gyrotemp[0] = valid_data_buffer[6]; raw.gyrotemp[1] = valid_data_buffer[7]; raw.gyros_filtered[0] = (gyro_data.filtered.x - Nav.gyro_bias[0]) * 180 / M_PI; raw.gyros_filtered[1] = (gyro_data.filtered.y - Nav.gyro_bias[1]) * 180 / M_PI; raw.gyros_filtered[2] = (gyro_data.filtered.z - Nav.gyro_bias[2]) * 180 / M_PI; raw.accels[0] = valid_data_buffer[2]; raw.accels[1] = valid_data_buffer[0]; raw.accels[2] = valid_data_buffer[4]; raw.accels_filtered[0] = accel_data.filtered.x; raw.accels_filtered[1] = accel_data.filtered.y; raw.accels_filtered[2] = accel_data.filtered.z; raw.magnetometers[0] = mag_data.scaled.axis[0]; raw.magnetometers[1] = mag_data.scaled.axis[1]; raw.magnetometers[2] = mag_data.scaled.axis[2]; AttitudeRawSet(&raw); } #if defined(PIOS_INCLUDE_HMC5843) && defined(PIOS_INCLUDE_I2C) /** * @brief Get the mag data from the I2C sensor and load into structure * @return none * * This function also considers if the home location is set and has a valid * magnetic field before updating the mag data to prevent data being used that * cannot be interpreted. In addition the mag data is not used for the first * five seconds to allow the filter to start to converge */ void process_mag_data() { // Get magnetic readings // For now don't use mags until the magnetic field is set AND until 5 seconds // after initialization otherwise it seems to have problems // TODO: Follow up this initialization issue HomeLocationData home; HomeLocationGet(&home); if (PIOS_HMC5843_NewDataAvailable() && (home.Set == HOMELOCATION_SET_TRUE) && ((home.Be[0] != 0) || (home.Be[1] != 0) || (home.Be[2] != 0))) { PIOS_HMC5843_ReadMag(mag_data.raw.axis); // Swap the axis here to acount for orientation of mag chip (notice 0 and 1 swapped in raw) mag_data.scaled.axis[0] = (mag_data.raw.axis[1] * mag_data.calibration.scale[0]) + mag_data.calibration.bias[0]; mag_data.scaled.axis[1] = (mag_data.raw.axis[0] * mag_data.calibration.scale[1]) + mag_data.calibration.bias[1]; mag_data.scaled.axis[2] = (mag_data.raw.axis[2] * mag_data.calibration.scale[2]) + mag_data.calibration.bias[2]; // Only use if magnetic length reasonable float Blen = sqrt(pow(mag_data.scaled.axis[0],2) + pow(mag_data.scaled.axis[1],2) + pow(mag_data.scaled.axis[2],2)); if((Blen < INSGPS_MAGLEN * (1 + INSGPS_MAGTOL)) && (Blen > INSGPS_MAGLEN * (1 - INSGPS_MAGTOL))) mag_data.updated = 1; } } #else void process_mag_data() { } #endif /** * @brief Assumes board is not moving computes biases and variances of sensors * @returns None * * All data is stored in global structures. This function should be called from OP when * aircraft is in stable state and then the data stored to SD card. * * After this function the bias for each sensor will be the mean value. This doesn't make * sense for the z accel so make sure 6 point calibration is also run and those values set * after these read. */ #define NBIAS 100 #define NVAR 500 void calibrate_sensors() { int i,j; float accel_bias[3] = {0, 0, 0}; float gyro_bias[3] = {0, 0, 0}; float mag_bias[3] = {0, 0, 0}; for (i = 0, j = 0; i < NBIAS; i++) { while (ahrs_state != AHRS_DATA_READY) ; ahrs_state = AHRS_PROCESSING; downsample_data(); gyro_bias[0] += gyro_data.filtered.x / NBIAS; gyro_bias[1] += gyro_data.filtered.y / NBIAS; gyro_bias[2] += gyro_data.filtered.z / NBIAS; accel_bias[0] += accel_data.filtered.x / NBIAS; accel_bias[1] += accel_data.filtered.y / NBIAS; accel_bias[2] += accel_data.filtered.z / NBIAS; ahrs_state = AHRS_IDLE; #if defined(PIOS_INCLUDE_HMC5843) && defined(PIOS_INCLUDE_I2C) if(PIOS_HMC5843_NewDataAvailable()) { j ++; PIOS_HMC5843_ReadMag(mag_data.raw.axis); mag_data.scaled.axis[0] = (mag_data.raw.axis[0] * mag_data.calibration.scale[0]) + mag_data.calibration.bias[0]; mag_data.scaled.axis[1] = (mag_data.raw.axis[1] * mag_data.calibration.scale[1]) + mag_data.calibration.bias[1]; mag_data.scaled.axis[2] = (mag_data.raw.axis[2] * mag_data.calibration.scale[2]) + mag_data.calibration.bias[2]; mag_bias[0] += mag_data.scaled.axis[0]; mag_bias[1] += mag_data.scaled.axis[1]; mag_bias[2] += mag_data.scaled.axis[2]; } #endif } mag_bias[0] /= j; mag_bias[1] /= j; mag_bias[2] /= j; gyro_data.calibration.variance[0] = 0; gyro_data.calibration.variance[1] = 0; gyro_data.calibration.variance[2] = 0; mag_data.calibration.variance[0] = 0; mag_data.calibration.variance[1] = 0; mag_data.calibration.variance[2] = 0; accel_data.calibration.variance[0] = 0; accel_data.calibration.variance[1] = 0; accel_data.calibration.variance[2] = 0; for (i = 0, j = 0; j < NVAR; j++) { while (ahrs_state != AHRS_DATA_READY) ; ahrs_state = AHRS_PROCESSING; downsample_data(); gyro_data.calibration.variance[0] += pow(gyro_data.filtered.x-gyro_bias[0],2) / NVAR; gyro_data.calibration.variance[1] += pow(gyro_data.filtered.y-gyro_bias[1],2) / NVAR; gyro_data.calibration.variance[2] += pow(gyro_data.filtered.z-gyro_bias[2],2) / NVAR; accel_data.calibration.variance[0] += pow(accel_data.filtered.x-accel_bias[0],2) / NVAR; accel_data.calibration.variance[1] += pow(accel_data.filtered.y-accel_bias[1],2) / NVAR; accel_data.calibration.variance[2] += pow(accel_data.filtered.z-accel_bias[2],2) / NVAR; ahrs_state = AHRS_IDLE; #if defined(PIOS_INCLUDE_HMC5843) && defined(PIOS_INCLUDE_I2C) if(PIOS_HMC5843_NewDataAvailable()) { j ++; PIOS_HMC5843_ReadMag(mag_data.raw.axis); mag_data.scaled.axis[0] = (mag_data.raw.axis[0] * mag_data.calibration.scale[0]) + mag_data.calibration.bias[0]; mag_data.scaled.axis[1] = (mag_data.raw.axis[1] * mag_data.calibration.scale[1]) + mag_data.calibration.bias[1]; mag_data.scaled.axis[2] = (mag_data.raw.axis[2] * mag_data.calibration.scale[2]) + mag_data.calibration.bias[2]; mag_data.calibration.variance[0] += pow(mag_data.scaled.axis[0]-mag_bias[0],2); mag_data.calibration.variance[1] += pow(mag_data.scaled.axis[1]-mag_bias[1],2); mag_data.calibration.variance[2] += pow(mag_data.scaled.axis[2]-mag_bias[2],2); } #endif } mag_data.calibration.variance[0] /= j; mag_data.calibration.variance[1] /= j; mag_data.calibration.variance[2] /= j; gyro_data.calibration.bias[0] -= gyro_bias[0]; gyro_data.calibration.bias[1] -= gyro_bias[1]; gyro_data.calibration.bias[2] -= gyro_bias[2]; } /** * @brief Populate fields with initial values */ void reset_values() { accel_data.calibration.scale[0] = 0.012; accel_data.calibration.scale[1] = 0.012; accel_data.calibration.scale[2] = -0.012; accel_data.calibration.bias[0] = 24; accel_data.calibration.bias[1] = 24; accel_data.calibration.bias[2] = -24; accel_data.calibration.variance[0] = 1e-4; accel_data.calibration.variance[1] = 1e-4; accel_data.calibration.variance[2] = 1e-4; gyro_data.calibration.scale[0] = -0.014; gyro_data.calibration.scale[1] = 0.014; gyro_data.calibration.scale[2] = -0.014; gyro_data.calibration.bias[0] = -24; gyro_data.calibration.bias[1] = -24; gyro_data.calibration.bias[2] = -24; gyro_data.calibration.variance[0] = 1; gyro_data.calibration.variance[1] = 1; gyro_data.calibration.variance[2] = 1; mag_data.calibration.scale[0] = 1; mag_data.calibration.scale[1] = 1; mag_data.calibration.scale[2] = 1; mag_data.calibration.bias[0] = 0; mag_data.calibration.bias[1] = 0; mag_data.calibration.bias[2] = 0; mag_data.calibration.variance[0] = 1; mag_data.calibration.variance[1] = 1; mag_data.calibration.variance[2] = 1; } void send_attitude(void) { AttitudeActualData attitude; AHRSSettingsData settings; AHRSSettingsGet(&settings); attitude.q1 = attitude_data.quaternion.q1; attitude.q2 = attitude_data.quaternion.q2; attitude.q3 = attitude_data.quaternion.q3; attitude.q4 = attitude_data.quaternion.q4; float rpy[3]; Quaternion2RPY(&attitude_data.quaternion.q1, rpy); attitude.Roll = rpy[0] + settings.RollBias; attitude.Pitch = rpy[1] + settings.PitchBias; attitude.Yaw = rpy[2] + settings.YawBias; if(attitude.Yaw > 360) attitude.Yaw -= 360; AttitudeActualSet(&attitude); } void send_velocity(void) { VelocityActualData velocityActual; VelocityActualGet(&velocityActual); // convert into cm velocityActual.North = Nav.Vel[0] * 100; velocityActual.East = Nav.Vel[1] * 100; velocityActual.Down = Nav.Vel[2] * 100; VelocityActualSet(&velocityActual); } void send_position(void) { PositionActualData positionActual; PositionActualGet(&positionActual); // convert into cm positionActual.North = Nav.Pos[0] * 100; positionActual.East = Nav.Pos[1] * 100; positionActual.Down = Nav.Pos[2] * 100; PositionActualSet(&positionActual); } void send_calibration(void) { AHRSCalibrationData cal; AHRSCalibrationGet(&cal); for(int ct=0; ct<3; ct++) { cal.accel_var[ct] = accel_data.calibration.variance[ct]; cal.gyro_bias[ct] = gyro_data.calibration.bias[ct]; cal.gyro_var[ct] = gyro_data.calibration.variance[ct]; cal.mag_var[ct] = mag_data.calibration.variance[ct]; } cal.measure_var = AHRSCALIBRATION_MEASURE_VAR_SET; AHRSCalibrationSet(&cal); } /** * @brief AHRS calibration callback * * Called when the OP board sets the calibration */ void calibration_callback(AhrsObjHandle obj) { AHRSCalibrationData cal; AHRSCalibrationGet(&cal); if(cal.measure_var == AHRSCALIBRATION_MEASURE_VAR_SET){ for(int ct=0; ct<3; ct++) { accel_data.calibration.scale[ct] = cal.accel_scale[ct]; accel_data.calibration.bias[ct] = cal.accel_bias[ct]; accel_data.calibration.variance[ct] = cal.accel_var[ct]; gyro_data.calibration.scale[ct] = cal.gyro_scale[ct]; gyro_data.calibration.bias[ct] = cal.gyro_bias[ct]; gyro_data.calibration.variance[ct] = cal.gyro_var[ct]; mag_data.calibration.bias[ct] = cal.mag_bias[ct]; mag_data.calibration.scale[ct] = cal.mag_scale[ct]; mag_data.calibration.variance[ct] = cal.mag_var[ct]; } // Note: We need the divided by 1000^2 since we scale mags to have a norm of 1000 and they are scaled to // one in code float mag_var[3] = {mag_data.calibration.variance[0] / INSGPS_MAGLEN / INSGPS_MAGLEN, mag_data.calibration.variance[1] / INSGPS_MAGLEN / INSGPS_MAGLEN, mag_data.calibration.variance[2] / INSGPS_MAGLEN / INSGPS_MAGLEN}; INSSetMagVar(mag_var); INSSetAccelVar(accel_data.calibration.variance); INSSetGyroVar(gyro_data.calibration.variance); }else if(cal.measure_var == AHRSCALIBRATION_MEASURE_VAR_MEASURE){ calibrate_sensors(); send_calibration(); } INSSetPosVelVar(cal.pos_var, cal.vel_var); } void gps_callback(AhrsObjHandle obj) { GPSPositionData pos; GPSPositionGet(&pos); HomeLocationData home; HomeLocationGet(&home); // convert from cm back to meters double LLA[3] = {(double) pos.Latitude / 1e7, (double) pos.Longitude / 1e7, (double) (pos.GeoidSeparation + pos.Altitude)}; // put in local NED frame double ECEF[3] = {(double) (home.ECEF[0] / 100), (double) (home.ECEF[1] / 100), (double) (home.ECEF[2] / 100)}; LLA2Base(LLA, ECEF, (float (*)[3]) home.RNE, gps_data.NED); gps_data.heading = pos.Heading; gps_data.groundspeed = pos.Groundspeed; gps_data.quality = 1; /* currently unused */ gps_data.updated = true; // if poor don't use this update if((ahrs_algorithm != AHRSSETTINGS_ALGORITHM_INSGPS_OUTDOOR) || (pos.Satellites < INSGPS_GPS_MINSAT) || (pos.PDOP >= INSGPS_GPS_MINPDOP) || (home.Set == FALSE) || ((home.ECEF[0] == 0) && (home.ECEF[1] == 0) && (home.ECEF[2] == 0))) { gps_data.quality = 0; gps_data.updated = false; } } void altitude_callback(AhrsObjHandle obj) { BaroAltitudeData alt; BaroAltitudeGet(&alt); altitude_data.altitude = alt.Altitude; altitude_data.updated = true; } void settings_callback(AhrsObjHandle obj) { AHRSSettingsData settings; AHRSSettingsGet(&settings); ahrs_algorithm = settings.Algorithm; if(settings.Downsampling != adc_oversampling) { adc_oversampling = settings.Downsampling; if(adc_oversampling > MAX_OVERSAMPLING) { adc_oversampling = MAX_OVERSAMPLING; settings.Downsampling = MAX_OVERSAMPLING; AHRSSettingsSet(&settings); } AHRS_ADC_Config(adc_oversampling); /* Use simple averaging filter for now */ for (int i = 0; i < adc_oversampling; i++) fir_coeffs[i] = 1; fir_coeffs[adc_oversampling] = adc_oversampling; } } void homelocation_callback(AhrsObjHandle obj) { HomeLocationData data; HomeLocationGet(&data); float Bmag = sqrt(pow(data.Be[0],2) + pow(data.Be[1],2) + pow(data.Be[2],2)); float Be[3] = {data.Be[0] / Bmag, data.Be[1] / Bmag, data.Be[2] / Bmag}; INSSetMagNorth(Be); } /** * @} */