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ardupilot/libraries/AP_InertialSensor/AP_InertialSensor.cpp

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/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*-
#include <AP_Progmem.h>
#include "AP_InertialSensor.h"
#include <AP_Common.h>
#include <AP_HAL.h>
extern const AP_HAL::HAL& hal;
#define FLASH_LEDS(on) do { if (flash_leds_cb != NULL) flash_leds_cb(on); } while (0)
#define SAMPLE_UNIT 1
// Class level parameters
const AP_Param::GroupInfo AP_InertialSensor::var_info[] PROGMEM = {
// @Param: PRODUCT_ID
// @DisplayName: IMU Product ID
// @Description: Which type of IMU is installed (read-only)
// @User: Standard
AP_GROUPINFO("PRODUCT_ID", 0, AP_InertialSensor, _product_id, 0),
// @Param: ACCSCAL
// @DisplayName: Acceleration Scaling
// @Description: Calibration scaling of x/y/z acceleration axes. This is setup using the acceleration calibration
// @User: Advanced
AP_GROUPINFO("ACCSCAL", 1, AP_InertialSensor, _accel_scale, 0),
// @Param: ACCOFFS
// @DisplayName: Acceleration Offsets
// @Description: Calibration offsets of x/y/z acceleration axes. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @User: Advanced
AP_GROUPINFO("ACCOFFS", 2, AP_InertialSensor, _accel_offset, 0),
// @Param: GYROFFS
// @DisplayName: Gyro offsets
// @Description: Calibration offsets of x/y/z gyroscope axes. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
AP_GROUPINFO("GYROFFS", 3, AP_InertialSensor, _gyro_offset, 0),
// @Param: MPU6K_FILTER
// @DisplayName: MPU6000 filter frequency
// @Description: Filter frequency to ask the MPU6000 to apply to samples. This can be set to a lower value to try to cope with very high vibration levels in aircraft. The default value on ArduPlane and APMrover2 is 20Hz. The default value on ArduCopter is 42Hz. This option takes effect on the next reboot or gyro initialisation
// @Units: Hz
// @Values: 0:Default,5:5Hz,10:10Hz,20:20Hz,42:42Hz,98:98Hz
// @User: Advanced
AP_GROUPINFO("MPU6K_FILTER", 4, AP_InertialSensor, _mpu6000_filter, 0),
AP_GROUPEND
};
void
AP_InertialSensor::init( Start_style style,
Sample_rate sample_rate,
void (*flash_leds_cb)(bool on))
{
_product_id = _init_sensor(sample_rate);
// check scaling
Vector3f accel_scale = _accel_scale.get();
if( accel_scale.x == 0 && accel_scale.y == 0 && accel_scale.z == 0 ) {
accel_scale.x = accel_scale.y = accel_scale.z = 1.0;
_accel_scale.set(accel_scale);
}
if (WARM_START != style) {
// do cold-start calibration for gyro only
_init_gyro(flash_leds_cb);
}
}
// save parameters to eeprom
void AP_InertialSensor::_save_parameters()
{
_product_id.save();
_accel_scale.save();
_accel_offset.save();
_gyro_offset.save();
}
void
AP_InertialSensor::init_gyro(void (*flash_leds_cb)(bool on))
{
_init_gyro(flash_leds_cb);
// save calibration
_save_parameters();
}
void
AP_InertialSensor::_init_gyro(void (*flash_leds_cb)(bool on))
{
Vector3f last_average, best_avg;
Vector3f ins_gyro;
float best_diff = 0;
// cold start
hal.scheduler->delay(100);
hal.console->printf_P(PSTR("Init Gyro"));
// remove existing gyro offsets
_gyro_offset = Vector3f(0,0,0);
for(int8_t c = 0; c < 25; c++) {
// Mostly we are just flashing the LED's here
// to tell the user to keep the IMU still
FLASH_LEDS(true);
hal.scheduler->delay(20);
update();
ins_gyro = get_gyro();
FLASH_LEDS(false);
hal.scheduler->delay(20);
}
// the strategy is to average 200 points over 1 second, then do it
// again and see if the 2nd average is within a small margin of
// the first
last_average.zero();
// we try to get a good calibration estimate for up to 10 seconds
// if the gyros are stable, we should get it in 2 seconds
for (int16_t j = 0; j <= 10; j++) {
Vector3f gyro_sum, gyro_avg, gyro_diff;
float diff_norm;
uint8_t i;
hal.console->printf_P(PSTR("*"));
gyro_sum.zero();
for (i=0; i<200; i++) {
update();
ins_gyro = get_gyro();
gyro_sum += ins_gyro;
if (i % 40 == 20) {
FLASH_LEDS(true);
} else if (i % 40 == 0) {
FLASH_LEDS(false);
}
hal.scheduler->delay(5);
}
gyro_avg = gyro_sum / i;
gyro_diff = last_average - gyro_avg;
diff_norm = gyro_diff.length();
if (j == 0) {
best_diff = diff_norm;
best_avg = gyro_avg;
} else if (gyro_diff.length() < ToRad(0.04)) {
// we want the average to be within 0.1 bit, which is 0.04 degrees/s
last_average = (gyro_avg * 0.5) + (last_average * 0.5);
_gyro_offset = last_average;
// all done
return;
} else if (diff_norm < best_diff) {
best_diff = diff_norm;
best_avg = (gyro_avg * 0.5) + (last_average * 0.5);
}
last_average = gyro_avg;
}
// we've kept the user waiting long enough - use the best pair we
// found so far
hal.console->printf_P(PSTR("\ngyro did not converge: diff=%f dps\n"), ToDeg(best_diff));
_gyro_offset = best_avg;
}
void
AP_InertialSensor::init_accel(void (*flash_leds_cb)(bool on))
{
_init_accel(flash_leds_cb);
// save calibration
_save_parameters();
}
void
AP_InertialSensor::_init_accel(void (*flash_leds_cb)(bool on))
{
int8_t flashcount = 0;
Vector3f ins_accel;
Vector3f prev;
Vector3f accel_offset;
float total_change;
float max_offset;
// cold start
hal.scheduler->delay(100);
hal.console->printf_P(PSTR("Init Accel"));
// clear accelerometer offsets and scaling
_accel_offset = Vector3f(0,0,0);
_accel_scale = Vector3f(1,1,1);
// initialise accel offsets to a large value the first time
// this will force us to calibrate accels at least twice
accel_offset = Vector3f(500, 500, 500);
// loop until we calculate acceptable offsets
do {
// get latest accelerometer values
update();
ins_accel = get_accel();
// store old offsets
prev = accel_offset;
// get new offsets
accel_offset = ins_accel;
// We take some readings...
for(int8_t i = 0; i < 50; i++) {
hal.scheduler->delay(20);
update();
ins_accel = get_accel();
// low pass filter the offsets
accel_offset = accel_offset * 0.9 + ins_accel * 0.1;
// display some output to the user
if(flashcount == 5) {
hal.console->printf_P(PSTR("*"));
FLASH_LEDS(true);
}
if(flashcount >= 10) {
flashcount = 0;
FLASH_LEDS(false);
}
flashcount++;
}
// null gravity from the Z accel
// TO-DO: replace with gravity #define form location.cpp
accel_offset.z += GRAVITY;
total_change = fabs(prev.x - accel_offset.x) + fabs(prev.y - accel_offset.y) + fabs(prev.z - accel_offset.z);
max_offset = (accel_offset.x > accel_offset.y) ? accel_offset.x : accel_offset.y;
max_offset = (max_offset > accel_offset.z) ? max_offset : accel_offset.z;
hal.scheduler->delay(500);
} while ( total_change > AP_INERTIAL_SENSOR_ACCEL_TOT_MAX_OFFSET_CHANGE || max_offset > AP_INERTIAL_SENSOR_ACCEL_MAX_OFFSET);
// set the global accel offsets
_accel_offset = accel_offset;
hal.console->printf_P(PSTR(" "));
}
#if !defined( __AVR_ATmega1280__ )
// calibrate_accel - perform accelerometer calibration including providing user
// instructions and feedback Gauss-Newton accel calibration routines borrowed
// from Rolfe Schmidt blog post describing the method:
// http://chionophilous.wordpress.com/2011/10/24/accelerometer-calibration-iv-1-implementing-gauss-newton-on-an-atmega/
// original sketch available at
// http://rolfeschmidt.com/mathtools/skimetrics/adxl_gn_calibration.pde
bool AP_InertialSensor::calibrate_accel(void (*flash_leds_cb)(bool on),
AP_HAL::BetterStream* c)
{
Vector3f samples[6];
Vector3f new_offsets;
Vector3f new_scaling;
Vector3f orig_offset;
Vector3f orig_scale;
// backup original offsets and scaling
orig_offset = _accel_offset.get();
orig_scale = _accel_scale.get();
// clear accelerometer offsets and scaling
_accel_offset = Vector3f(0,0,0);
_accel_scale = Vector3f(1,1,1);
// capture data from 6 positions
for (int8_t i=0; i<6; i++) {
const prog_char_t *msg;
// display message to user
switch ( i ) {
case 0:
msg = PSTR("level");
break;
case 1:
msg = PSTR("on it's left side");
break;
case 2:
msg = PSTR("on it's right side");
break;
case 3:
msg = PSTR("nose down");
break;
case 4:
msg = PSTR("nose up");
break;
case 5:
msg = PSTR("on it's back");
break;
}
c->printf_P(PSTR("USER: Place APM %S and press any key.\n"), msg);
// wait for user input
while (!c->available()) {
hal.scheduler->delay(20);
}
// clear input buffer
while( c->available() ) {
c->read();
}
// clear out any existing samples from ins
update();
// wait until we have 32 samples
while( num_samples_available() < 32 * SAMPLE_UNIT ) {
hal.scheduler->delay(10);
}
// read samples from ins
update();
// capture sample
samples[i] = get_accel();
}
// run the calibration routine
if( _calibrate_accel(samples, new_offsets, new_scaling) ) {
c->printf_P(PSTR("Calibration successful\n"));
// set and save calibration
_accel_offset.set(new_offsets);
_accel_scale.set(new_scaling);
_save_parameters();
return true;
}
c->printf_P(PSTR("Calibration failed (%.1f %.1f %.1f %.1f %.1f %.1f)\n"),
new_offsets.x, new_offsets.y, new_offsets.z,
new_scaling.x, new_scaling.y, new_scaling.z);
// restore original scaling and offsets
_accel_offset.set(orig_offset);
_accel_scale.set(orig_scale);
return false;
}
// _calibrate_model - perform low level accel calibration
// accel_sample are accelerometer samples collected in 6 different positions
// accel_offsets are output from the calibration routine
// accel_scale are output from the calibration routine
// returns true if successful
bool AP_InertialSensor::_calibrate_accel( Vector3f accel_sample[6],
Vector3f& accel_offsets, Vector3f& accel_scale )
{
int16_t i;
int16_t num_iterations = 0;
float eps = 0.000000001;
float change = 100.0;
float data[3];
float beta[6];
float delta[6];
float ds[6];
float JS[6][6];
bool success = true;
// reset
beta[0] = beta[1] = beta[2] = 0;
beta[3] = beta[4] = beta[5] = 1.0/GRAVITY;
while( num_iterations < 20 && change > eps ) {
num_iterations++;
_calibrate_reset_matrices(ds, JS);
for( i=0; i<6; i++ ) {
data[0] = accel_sample[i].x;
data[1] = accel_sample[i].y;
data[2] = accel_sample[i].z;
_calibrate_update_matrices(ds, JS, beta, data);
}
_calibrate_find_delta(ds, JS, delta);
change = delta[0]*delta[0] +
delta[0]*delta[0] +
delta[1]*delta[1] +
delta[2]*delta[2] +
delta[3]*delta[3] / (beta[3]*beta[3]) +
delta[4]*delta[4] / (beta[4]*beta[4]) +
delta[5]*delta[5] / (beta[5]*beta[5]);
for( i=0; i<6; i++ ) {
beta[i] -= delta[i];
}
}
// copy results out
accel_scale.x = beta[3] * GRAVITY;
accel_scale.y = beta[4] * GRAVITY;
accel_scale.z = beta[5] * GRAVITY;
accel_offsets.x = beta[0] * accel_scale.x;
accel_offsets.y = beta[1] * accel_scale.y;
accel_offsets.z = beta[2] * accel_scale.z;
// sanity check scale
if( accel_scale.is_nan() || fabs(accel_scale.x-1.0) > 0.1 || fabs(accel_scale.y-1.0) > 0.1 || fabs(accel_scale.z-1.0) > 0.1 ) {
success = false;
}
// sanity check offsets (2.0 is roughly 2/10th of a G, 5.0 is roughly half a G)
if( accel_offsets.is_nan() || fabs(accel_offsets.x) > 2.0 || fabs(accel_offsets.y) > 2.0 || fabs(accel_offsets.z) > 3.0 ) {
success = false;
}
// return success or failure
return success;
}
void AP_InertialSensor::_calibrate_update_matrices(float dS[6], float JS[6][6],
float beta[6], float data[3])
{
int16_t j, k;
float dx, b;
float residual = 1.0;
float jacobian[6];
for( j=0; j<3; j++ ) {
b = beta[3+j];
dx = (float)data[j] - beta[j];
residual -= b*b*dx*dx;
jacobian[j] = 2.0*b*b*dx;
jacobian[3+j] = -2.0*b*dx*dx;
}
for( j=0; j<6; j++ ) {
dS[j] += jacobian[j]*residual;
for( k=0; k<6; k++ ) {
JS[j][k] += jacobian[j]*jacobian[k];
}
}
}
// _calibrate_reset_matrices - clears matrices
void AP_InertialSensor::_calibrate_reset_matrices(float dS[6], float JS[6][6])
{
int16_t j,k;
for( j=0; j<6; j++ ) {
dS[j] = 0.0;
for( k=0; k<6; k++ ) {
JS[j][k] = 0.0;
}
}
}
void AP_InertialSensor::_calibrate_find_delta(float dS[6], float JS[6][6], float delta[6])
{
//Solve 6-d matrix equation JS*x = dS
//first put in upper triangular form
int16_t i,j,k;
float mu;
//make upper triangular
for( i=0; i<6; i++ ) {
//eliminate all nonzero entries below JS[i][i]
for( j=i+1; j<6; j++ ) {
mu = JS[i][j]/JS[i][i];
if( mu != 0.0 ) {
dS[j] -= mu*dS[i];
for( k=j; k<6; k++ ) {
JS[k][j] -= mu*JS[k][i];
}
}
}
}
//back-substitute
for( i=5; i>=0; i-- ) {
dS[i] /= JS[i][i];
JS[i][i] = 1.0;
for( j=0; j<i; j++ ) {
mu = JS[i][j];
dS[j] -= mu*dS[i];
JS[i][j] = 0.0;
}
}
for( i=0; i<6; i++ ) {
delta[i] = dS[i];
}
}
#endif // __AVR_ATmega1280__
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