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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>
#include <AP_Notify.h>
#include <AP_Vehicle.h>
/*
enable TIMING_DEBUG to track down scheduling issues with the main
loop. Output is on the debug console
*/
#define TIMING_DEBUG 0
#if TIMING_DEBUG
#include <stdio.h>
#define timing_printf(fmt, args...) do { printf("[timing] " fmt, ##args); } while(0)
#else
#define timing_printf(fmt, args...)
#endif
extern const AP_HAL::HAL& hal;
#if APM_BUILD_TYPE(APM_BUILD_ArduCopter)
#define DEFAULT_GYRO_FILTER 20
#define DEFAULT_ACCEL_FILTER 20
#elif APM_BUILD_TYPE(APM_BUILD_APMrover2)
#define DEFAULT_GYRO_FILTER 10
#define DEFAULT_ACCEL_FILTER 10
#else
#define DEFAULT_GYRO_FILTER 20
#define DEFAULT_ACCEL_FILTER 20
#endif
#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: Advanced
// @Values: 0:Unknown,1:APM1-1280,2:APM1-2560,88:APM2,3:SITL,4:PX4v1,5:PX4v2,256:Flymaple,257:Linux
AP_GROUPINFO("PRODUCT_ID", 0, AP_InertialSensor, _product_id, 0),
/*
The following parameter indexes and reserved from previous use
as accel offsets and scaling from before the 16g change in the
PX4 backend:
ACCSCAL : 1
ACCOFFS : 2
MPU6K_FILTER: 4
ACC2SCAL : 5
ACC2OFFS : 6
ACC3SCAL : 8
ACC3OFFS : 9
CALSENSFRAME : 11
*/
// @Param: GYROFFS_X
// @DisplayName: Gyro offsets of X axis
// @Description: Gyro sensor offsets of X axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
// @Param: GYROFFS_Y
// @DisplayName: Gyro offsets of Y axis
// @Description: Gyro sensor offsets of Y axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
// @Param: GYROFFS_Z
// @DisplayName: Gyro offsets of Z axis
// @Description: Gyro sensor offsets of Z axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
AP_GROUPINFO("GYROFFS", 3, AP_InertialSensor, _gyro_offset[0], 0),
#if INS_MAX_INSTANCES > 1
// @Param: GYR2OFFS_X
// @DisplayName: Gyro2 offsets of X axis
// @Description: Gyro2 sensor offsets of X axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
// @Param: GYR2OFFS_Y
// @DisplayName: Gyro2 offsets of Y axis
// @Description: Gyro2 sensor offsets of Y axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
// @Param: GYR2OFFS_Z
// @DisplayName: Gyro2 offsets of Z axis
// @Description: Gyro2 sensor offsets of Z axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
AP_GROUPINFO("GYR2OFFS", 7, AP_InertialSensor, _gyro_offset[1], 0),
#endif
#if INS_MAX_INSTANCES > 2
// @Param: GYR3OFFS_X
// @DisplayName: Gyro3 offsets of X axis
// @Description: Gyro3 sensor offsets of X axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
// @Param: GYR3OFFS_Y
// @DisplayName: Gyro3 offsets of Y axis
// @Description: Gyro3 sensor offsets of Y axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
// @Param: GYR3OFFS_Z
// @DisplayName: Gyro3 offsets of Z axis
// @Description: Gyro3 sensor offsets of Z axis. This is setup on each boot during gyro calibrations
// @Units: rad/s
// @User: Advanced
AP_GROUPINFO("GYR3OFFS", 10, AP_InertialSensor, _gyro_offset[2], 0),
#endif
// @Param: ACCSCAL_X
// @DisplayName: Accelerometer scaling of X axis
// @Description: Accelerometer scaling of X axis. Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
// @Param: ACCSCAL_Y
// @DisplayName: Accelerometer scaling of Y axis
// @Description: Accelerometer scaling of Y axis Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
// @Param: ACCSCAL_Z
// @DisplayName: Accelerometer scaling of Z axis
// @Description: Accelerometer scaling of Z axis Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
AP_GROUPINFO("ACCSCAL", 12, AP_InertialSensor, _accel_scale[0], 0),
// @Param: ACCOFFS_X
// @DisplayName: Accelerometer offsets of X axis
// @Description: Accelerometer offsets of X axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
// @Param: ACCOFFS_Y
// @DisplayName: Accelerometer offsets of Y axis
// @Description: Accelerometer offsets of Y axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
// @Param: ACCOFFS_Z
// @DisplayName: Accelerometer offsets of Z axis
// @Description: Accelerometer offsets of Z axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
AP_GROUPINFO("ACCOFFS", 13, AP_InertialSensor, _accel_offset[0], 0),
#if INS_MAX_INSTANCES > 1
// @Param: ACC2SCAL_X
// @DisplayName: Accelerometer2 scaling of X axis
// @Description: Accelerometer2 scaling of X axis. Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
// @Param: ACC2SCAL_Y
// @DisplayName: Accelerometer2 scaling of Y axis
// @Description: Accelerometer2 scaling of Y axis Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
// @Param: ACC2SCAL_Z
// @DisplayName: Accelerometer2 scaling of Z axis
// @Description: Accelerometer2 scaling of Z axis Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
AP_GROUPINFO("ACC2SCAL", 14, AP_InertialSensor, _accel_scale[1], 0),
// @Param: ACC2OFFS_X
// @DisplayName: Accelerometer2 offsets of X axis
// @Description: Accelerometer2 offsets of X axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
// @Param: ACC2OFFS_Y
// @DisplayName: Accelerometer2 offsets of Y axis
// @Description: Accelerometer2 offsets of Y axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
// @Param: ACC2OFFS_Z
// @DisplayName: Accelerometer2 offsets of Z axis
// @Description: Accelerometer2 offsets of Z axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
AP_GROUPINFO("ACC2OFFS", 15, AP_InertialSensor, _accel_offset[1], 0),
#endif
#if INS_MAX_INSTANCES > 2
// @Param: ACC3SCAL_X
// @DisplayName: Accelerometer3 scaling of X axis
// @Description: Accelerometer3 scaling of X axis. Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
// @Param: ACC3SCAL_Y
// @DisplayName: Accelerometer3 scaling of Y axis
// @Description: Accelerometer3 scaling of Y axis Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
// @Param: ACC3SCAL_Z
// @DisplayName: Accelerometer3 scaling of Z axis
// @Description: Accelerometer3 scaling of Z axis Calculated during acceleration calibration routine
// @Range: 0.8 1.2
// @User: Advanced
AP_GROUPINFO("ACC3SCAL", 16, AP_InertialSensor, _accel_scale[2], 0),
// @Param: ACC3OFFS_X
// @DisplayName: Accelerometer3 offsets of X axis
// @Description: Accelerometer3 offsets of X axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
// @Param: ACC3OFFS_Y
// @DisplayName: Accelerometer3 offsets of Y axis
// @Description: Accelerometer3 offsets of Y axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
// @Param: ACC3OFFS_Z
// @DisplayName: Accelerometer3 offsets of Z axis
// @Description: Accelerometer3 offsets of Z axis. This is setup using the acceleration calibration or level operations
// @Units: m/s/s
// @Range: -300 300
// @User: Advanced
AP_GROUPINFO("ACC3OFFS", 17, AP_InertialSensor, _accel_offset[2], 0),
#endif
// @Param: GYRO_FILTER
// @DisplayName: Gyro filter cutoff frequency
// @Description: Filter cutoff frequency for gyroscopes. This can be set to a lower value to try to cope with very high vibration levels in aircraft. This option takes effect on the next reboot. A value of zero means no filtering (not recommended!)
// @Units: Hz
// @Range: 0 127
// @User: Advanced
AP_GROUPINFO("GYRO_FILTER", 18, AP_InertialSensor, _gyro_filter_cutoff, DEFAULT_GYRO_FILTER),
// @Param: ACCEL_FILTER
// @DisplayName: Accel filter cutoff frequency
// @Description: Filter cutoff frequency for accelerometers. This can be set to a lower value to try to cope with very high vibration levels in aircraft. This option takes effect on the next reboot. A value of zero means no filtering (not recommended!)
// @Units: Hz
// @Range: 0 127
// @User: Advanced
AP_GROUPINFO("ACCEL_FILTER", 19, AP_InertialSensor, _accel_filter_cutoff, DEFAULT_ACCEL_FILTER),
/*
NOTE: parameter indexes have gaps above. When adding new
parameters check for conflicts carefully
*/
AP_GROUPEND
};
AP_InertialSensor::AP_InertialSensor() :
_gyro_count(0),
_accel_count(0),
_backend_count(0),
_accel(),
_gyro(),
_board_orientation(ROTATION_NONE),
_hil_mode(false),
_have_3D_calibration(false),
_calibrating(false)
{
AP_Param::setup_object_defaults(this, var_info);
for (uint8_t i=0; i<INS_MAX_BACKENDS; i++) {
_backends[i] = NULL;
}
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
_accel_error_count[i] = 0;
_gyro_error_count[i] = 0;
}
memset(_delta_velocity_valid,0,sizeof(_delta_velocity_valid));
memset(_delta_angle_valid,0,sizeof(_delta_angle_valid));
}
/*
register a new gyro instance
*/
uint8_t AP_InertialSensor::register_gyro(void)
{
if (_gyro_count == INS_MAX_INSTANCES) {
hal.scheduler->panic(PSTR("Too many gyros"));
}
return _gyro_count++;
}
/*
register a new accel instance
*/
uint8_t AP_InertialSensor::register_accel(void)
{
if (_accel_count == INS_MAX_INSTANCES) {
hal.scheduler->panic(PSTR("Too many accels"));
}
return _accel_count++;
}
void
AP_InertialSensor::init( Start_style style,
Sample_rate sample_rate)
{
// remember the sample rate
_sample_rate = sample_rate;
if (_gyro_count == 0 && _accel_count == 0) {
// detect available backends. Only called once
_detect_backends();
}
// initialise accel scale if need be. This is needed as we can't
// give non-zero default values for vectors in AP_Param
for (uint8_t i=0; i<get_accel_count(); i++) {
if (_accel_scale[i].get().is_zero()) {
_accel_scale[i].set(Vector3f(1,1,1));
}
}
// remember whether we have 3D calibration so this can be used for
// AHRS health
check_3D_calibration();
if (WARM_START != style) {
// do cold-start calibration for gyro only
_init_gyro();
}
switch (sample_rate) {
case RATE_50HZ:
_sample_period_usec = 20000;
break;
case RATE_100HZ:
_sample_period_usec = 10000;
break;
case RATE_200HZ:
_sample_period_usec = 5000;
break;
case RATE_400HZ:
default:
_sample_period_usec = 2500;
break;
}
// establish the baseline time between samples
_delta_time = 0;
_next_sample_usec = 0;
_last_sample_usec = 0;
_have_sample = false;
}
/*
try to load a backend
*/
void AP_InertialSensor::_add_backend(AP_InertialSensor_Backend *(detect)(AP_InertialSensor &))
{
if (_backend_count == INS_MAX_BACKENDS) {
hal.scheduler->panic(PSTR("Too many INS backends"));
}
_backends[_backend_count] = detect(*this);
if (_backends[_backend_count] != NULL) {
_backend_count++;
}
}
/*
detect available backends for this board
*/
void
AP_InertialSensor::_detect_backends(void)
{
if (_hil_mode) {
_add_backend(AP_InertialSensor_HIL::detect);
return;
}
#if HAL_INS_DEFAULT == HAL_INS_HIL
_add_backend(AP_InertialSensor_HIL::detect);
#elif HAL_INS_DEFAULT == HAL_INS_MPU6000
_add_backend(AP_InertialSensor_MPU6000::detect);
#elif HAL_INS_DEFAULT == HAL_INS_PX4 || HAL_INS_DEFAULT == HAL_INS_VRBRAIN
_add_backend(AP_InertialSensor_PX4::detect);
#elif HAL_INS_DEFAULT == HAL_INS_OILPAN
_add_backend(AP_InertialSensor_Oilpan::detect);
#elif HAL_INS_DEFAULT == HAL_INS_MPU9250
_add_backend(AP_InertialSensor_MPU9250::detect);
#elif HAL_INS_DEFAULT == HAL_INS_FLYMAPLE
_add_backend(AP_InertialSensor_Flymaple::detect);
#else
#error Unrecognised HAL_INS_TYPE setting
#endif
#if 0 // disabled due to broken hardware on some PXF capes
#if CONFIG_HAL_BOARD_SUBTYPE == HAL_BOARD_SUBTYPE_LINUX_PXF
// the PXF also has a MPU6000
_add_backend(AP_InertialSensor_MPU6000::detect);
#endif
#endif
if (_backend_count == 0 ||
_gyro_count == 0 ||
_accel_count == 0) {
hal.scheduler->panic(PSTR("No INS backends available"));
}
// set the product ID to the ID of the first backend
_product_id.set(_backends[0]->product_id());
}
#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(AP_InertialSensor_UserInteract* interact,
float &trim_roll,
float &trim_pitch)
{
uint8_t num_accels = min(get_accel_count(), INS_MAX_INSTANCES);
Vector3f samples[INS_MAX_INSTANCES][6];
Vector3f new_offsets[INS_MAX_INSTANCES];
Vector3f new_scaling[INS_MAX_INSTANCES];
Vector3f orig_offset[INS_MAX_INSTANCES];
Vector3f orig_scale[INS_MAX_INSTANCES];
uint8_t num_ok = 0;
// exit immediately if calibration is already in progress
if (_calibrating) {
return false;
}
_calibrating = true;
/*
we do the accel calibration with no board rotation. This avoids
having to rotate readings during the calibration
*/
enum Rotation saved_orientation = _board_orientation;
_board_orientation = ROTATION_NONE;
for (uint8_t k=0; k<num_accels; k++) {
// backup original offsets and scaling
orig_offset[k] = _accel_offset[k].get();
orig_scale[k] = _accel_scale[k].get();
// clear accelerometer offsets and scaling
_accel_offset[k] = Vector3f(0,0,0);
_accel_scale[k] = Vector3f(1,1,1);
}
memset(samples, 0, sizeof(samples));
// capture data from 6 positions
for (uint8_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 its LEFT side");
break;
case 2:
msg = PSTR("on its RIGHT side");
break;
case 3:
msg = PSTR("nose DOWN");
break;
case 4:
msg = PSTR("nose UP");
break;
default: // default added to avoid compiler warning
case 5:
msg = PSTR("on its BACK");
break;
}
interact->printf_P(
PSTR("Place vehicle %S and press any key.\n"), msg);
// wait for user input
if (!interact->blocking_read()) {
//No need to use interact->printf_P for an error, blocking_read does this when it fails
goto failed;
}
const uint8_t update_dt_milliseconds = (uint8_t)(1000.0f/get_sample_rate()+0.5f);
// wait 100ms for ins filter to rise
for (uint8_t k=0; k<100/update_dt_milliseconds; k++) {
wait_for_sample();
update();
hal.scheduler->delay(update_dt_milliseconds);
}
uint32_t num_samples = 0;
while (num_samples < 400/update_dt_milliseconds) {
wait_for_sample();
// read samples from ins
update();
// capture sample
for (uint8_t k=0; k<num_accels; k++) {
Vector3f samp;
if(get_delta_velocity(k,samp) && _delta_velocity_dt[k] > 0) {
samp /= _delta_velocity_dt[k];
} else {
samp = get_accel(k);
}
samples[k][i] += samp;
if (!get_accel_health(k)) {
interact->printf_P(PSTR("accel[%u] not healthy"), (unsigned)k);
goto failed;
}
}
hal.scheduler->delay(update_dt_milliseconds);
num_samples++;
}
for (uint8_t k=0; k<num_accels; k++) {
samples[k][i] /= num_samples;
}
}
// run the calibration routine
for (uint8_t k=0; k<num_accels; k++) {
if (!_check_sample_range(samples[k], saved_orientation, interact)) {
interact->printf_P(PSTR("Insufficient accel range"));
continue;
}
bool success = _calibrate_accel(samples[k], new_offsets[k], new_scaling[k], saved_orientation);
interact->printf_P(PSTR("Offsets[%u]: %.2f %.2f %.2f\n"),
(unsigned)k,
new_offsets[k].x, new_offsets[k].y, new_offsets[k].z);
interact->printf_P(PSTR("Scaling[%u]: %.2f %.2f %.2f\n"),
(unsigned)k,
new_scaling[k].x, new_scaling[k].y, new_scaling[k].z);
if (success) num_ok++;
}
if (num_ok == num_accels) {
interact->printf_P(PSTR("Calibration successful\n"));
for (uint8_t k=0; k<num_accels; k++) {
// set and save calibration
_accel_offset[k].set(new_offsets[k]);
_accel_scale[k].set(new_scaling[k]);
}
_save_parameters();
check_3D_calibration();
/*
calculate the trims as well from primary accels
We use the original board rotation for this sample
*/
Vector3f level_sample = samples[0][0];
level_sample.rotate(saved_orientation);
_calculate_trim(level_sample, trim_roll, trim_pitch);
_board_orientation = saved_orientation;
_calibrating = false;
return true;
}
failed:
interact->printf_P(PSTR("Calibration FAILED\n"));
// restore original scaling and offsets
for (uint8_t k=0; k<num_accels; k++) {
_accel_offset[k].set(orig_offset[k]);
_accel_scale[k].set(orig_scale[k]);
}
_board_orientation = saved_orientation;
_calibrating = false;
return false;
}
#endif
/*
check if the accelerometers are calibrated in 3D. Called on startup
and any accel cal
*/
void AP_InertialSensor::check_3D_calibration()
{
_have_3D_calibration = false;
// check each accelerometer has offsets saved
for (uint8_t i=0; i<get_accel_count(); i++) {
// exactly 0.0 offset is extremely unlikely
if (_accel_offset[i].get().is_zero()) {
return;
}
// exactly 1.0 scaling is extremely unlikely
const Vector3f &scaling = _accel_scale[i].get();
if (fabsf(scaling.x - 1.0f) < 0.00001f &&
fabsf(scaling.y - 1.0f) < 0.00001f &&
fabsf(scaling.z - 1.0f) < 0.00001f) {
return;
}
}
// if we got this far the accelerometers must have been calibrated
_have_3D_calibration = true;
}
/*
return true if we have 3D calibration values
*/
bool AP_InertialSensor::calibrated() const
{
return _have_3D_calibration;
}
void
AP_InertialSensor::init_gyro()
{
_init_gyro();
// save calibration
_save_parameters();
}
// get_gyro_health_all - return true if all gyros are healthy
bool AP_InertialSensor::get_gyro_health_all(void) const
{
for (uint8_t i=0; i<get_gyro_count(); i++) {
if (!get_gyro_health(i)) {
return false;
}
}
// return true if we have at least one gyro
return (get_gyro_count() > 0);
}
// gyro_calibration_ok_all - returns true if all gyros were calibrated successfully
bool AP_InertialSensor::gyro_calibrated_ok_all() const
{
for (uint8_t i=0; i<get_gyro_count(); i++) {
if (!gyro_calibrated_ok(i)) {
return false;
}
}
return (get_gyro_count() > 0);
}
// get_accel_health_all - return true if all accels are healthy
bool AP_InertialSensor::get_accel_health_all(void) const
{
for (uint8_t i=0; i<get_accel_count(); i++) {
if (!get_accel_health(i)) {
return false;
}
}
// return true if we have at least one accel
return (get_accel_count() > 0);
}
void
AP_InertialSensor::_init_gyro()
{
uint8_t num_gyros = min(get_gyro_count(), INS_MAX_INSTANCES);
Vector3f last_average[INS_MAX_INSTANCES], best_avg[INS_MAX_INSTANCES];
Vector3f new_gyro_offset[INS_MAX_INSTANCES];
float best_diff[INS_MAX_INSTANCES];
bool converged[INS_MAX_INSTANCES];
// exit immediately if calibration is already in progress
if (_calibrating) {
return;
}
// record we are calibrating
_calibrating = true;
// flash leds to tell user to keep the IMU still
AP_Notify::flags.initialising = true;
// cold start
hal.console->print_P(PSTR("Init Gyro"));
/*
we do the gyro calibration with no board rotation. This avoids
having to rotate readings during the calibration
*/
enum Rotation saved_orientation = _board_orientation;
_board_orientation = ROTATION_NONE;
// remove existing gyro offsets
for (uint8_t k=0; k<num_gyros; k++) {
_gyro_offset[k].set(Vector3f());
new_gyro_offset[k].zero();
best_diff[k] = 0;
last_average[k].zero();
converged[k] = false;
}
for(int8_t c = 0; c < 5; c++) {
hal.scheduler->delay(5);
update();
}
// the strategy is to average 50 points over 0.5 seconds, then do it
// again and see if the 2nd average is within a small margin of
// the first
uint8_t num_converged = 0;
// we try to get a good calibration estimate for up to 30 seconds
// if the gyros are stable, we should get it in 1 second
for (int16_t j = 0; j <= 30*4 && num_converged < num_gyros; j++) {
Vector3f gyro_sum[INS_MAX_INSTANCES], gyro_avg[INS_MAX_INSTANCES], gyro_diff[INS_MAX_INSTANCES];
Vector3f accel_start;
float diff_norm[INS_MAX_INSTANCES];
uint8_t i;
memset(diff_norm, 0, sizeof(diff_norm));
hal.console->print_P(PSTR("*"));
for (uint8_t k=0; k<num_gyros; k++) {
gyro_sum[k].zero();
}
accel_start = get_accel(0);
for (i=0; i<50; i++) {
update();
for (uint8_t k=0; k<num_gyros; k++) {
gyro_sum[k] += get_gyro(k);
}
hal.scheduler->delay(5);
}
Vector3f accel_diff = get_accel(0) - accel_start;
if (accel_diff.length() > 0.2f) {
// the accelerometers changed during the gyro sum. Skip
// this sample. This copes with doing gyro cal on a
// steadily moving platform. The value 0.2 corresponds
// with around 5 degrees/second of rotation.
continue;
}
for (uint8_t k=0; k<num_gyros; k++) {
gyro_avg[k] = gyro_sum[k] / i;
gyro_diff[k] = last_average[k] - gyro_avg[k];
diff_norm[k] = gyro_diff[k].length();
}
for (uint8_t k=0; k<num_gyros; k++) {
if (j == 0) {
best_diff[k] = diff_norm[k];
best_avg[k] = gyro_avg[k];
} else if (gyro_diff[k].length() < ToRad(0.1f)) {
// we want the average to be within 0.1 bit, which is 0.04 degrees/s
last_average[k] = (gyro_avg[k] * 0.5f) + (last_average[k] * 0.5f);
if (!converged[k] || last_average[k].length() < new_gyro_offset[k].length()) {
new_gyro_offset[k] = last_average[k];
}
if (!converged[k]) {
converged[k] = true;
num_converged++;
}
} else if (diff_norm[k] < best_diff[k]) {
best_diff[k] = diff_norm[k];
best_avg[k] = (gyro_avg[k] * 0.5f) + (last_average[k] * 0.5f);
}
last_average[k] = gyro_avg[k];
}
}
// we've kept the user waiting long enough - use the best pair we
// found so far
hal.console->println();
for (uint8_t k=0; k<num_gyros; k++) {
if (!converged[k]) {
hal.console->printf_P(PSTR("gyro[%u] did not converge: diff=%f dps\n"),
(unsigned)k, ToDeg(best_diff[k]));
_gyro_offset[k] = best_avg[k];
// flag calibration as failed for this gyro
_gyro_cal_ok[k] = false;
} else {
_gyro_cal_ok[k] = true;
_gyro_offset[k] = new_gyro_offset[k];
}
}
// restore orientation
_board_orientation = saved_orientation;
// record calibration complete
_calibrating = false;
// stop flashing leds
AP_Notify::flags.initialising = false;
}
#if !defined( __AVR_ATmega1280__ )
/*
check that the samples used for accel calibration have a sufficient
range on each axis. The sphere fit in _calibrate_accel() can produce
bad offsets and scaling factors if the range of input data is
insufficient.
We rotate each sample in the check to body frame to cope with 45
board orientations which could result in smaller ranges. The sample
inputs are in sensor frame
*/
bool AP_InertialSensor::_check_sample_range(const Vector3f accel_sample[6], enum Rotation rotation,
AP_InertialSensor_UserInteract* interact)
{
// we want at least 12 m/s/s range on all axes. This should be
// very easy to achieve, and guarantees the accels have been
// exposed to a good range of data
const float min_range = 12.0f;
Vector3f min_sample, max_sample;
// start with first sample
min_sample = accel_sample[0];
min_sample.rotate(rotation);
max_sample = min_sample;
for (uint8_t s=1; s<6; s++) {
Vector3f sample = accel_sample[s];
sample.rotate(rotation);
for (uint8_t i=0; i<3; i++) {
if (sample[i] < min_sample[i]) {
min_sample[i] = sample[i];
}
if (sample[i] > max_sample[i]) {
max_sample[i] = sample[i];
}
}
}
Vector3f range = max_sample - min_sample;
interact->printf_P(PSTR("AccelRange: %.1f %.1f %.1f"),
range.x, range.y, range.z);
bool ok = (range.x >= min_range &&
range.y >= min_range &&
range.z >= min_range);
return ok;
}
// _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(const Vector3f accel_sample[6],
Vector3f& accel_offsets, Vector3f& accel_scale,
enum Rotation rotation)
{
int16_t i;
int16_t num_iterations = 0;
float eps = 0.000000001f;
float change = 100.0f;
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] = 1.0f/GRAVITY_MSS;
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_MSS;
accel_scale.y = beta[4] * GRAVITY_MSS;
accel_scale.z = beta[5] * GRAVITY_MSS;
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() || fabsf(accel_scale.x-1.0f) > 0.1f || fabsf(accel_scale.y-1.0f) > 0.1f || fabsf(accel_scale.z-1.0f) > 0.1f ) {
success = false;
}
// sanity check offsets (3.5 is roughly 3/10th of a G, 5.0 is roughly half a G)
if( accel_offsets.is_nan() || fabsf(accel_offsets.x) > 3.5f || fabsf(accel_offsets.y) > 3.5f || fabsf(accel_offsets.z) > 3.5f ) {
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 = 1.0f;
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] = 2.0f*b*b*dx;
jacobian[3+j] = -2.0f*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] = 0.0f;
for( k=0; k<6; k++ ) {
JS[j][k] = 0.0f;
}
}
}
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 != 0.0f ) {
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] = 1.0f;
for( j=0; j<i; j++ ) {
mu = JS[i][j];
dS[j] -= mu*dS[i];
JS[i][j] = 0.0f;
}
}
for( i=0; i<6; i++ ) {
delta[i] = dS[i];
}
}
// _calculate_trim - calculates the x and y trim angles (in radians) given a raw accel sample (i.e. no scaling or offsets applied) taken when the vehicle was level
void AP_InertialSensor::_calculate_trim(const Vector3f &accel_sample, float& trim_roll, float& trim_pitch)
{
// scale sample and apply offsets
const Vector3f &accel_scale = _accel_scale[0].get();
const Vector3f &accel_offsets = _accel_offset[0].get();
Vector3f scaled_accels_x( accel_sample.x * accel_scale.x - accel_offsets.x,
0,
accel_sample.z * accel_scale.z - accel_offsets.z );
Vector3f scaled_accels_y( 0,
accel_sample.y * accel_scale.y - accel_offsets.y,
accel_sample.z * accel_scale.z - accel_offsets.z );
// calculate x and y axis angle (i.e. roll and pitch angles)
Vector3f vertical = Vector3f(0,0,-1);
trim_roll = scaled_accels_y.angle(vertical);
trim_pitch = scaled_accels_x.angle(vertical);
// angle call doesn't return the sign so take care of it here
if( scaled_accels_y.y > 0 ) {
trim_roll = -trim_roll;
}
if( scaled_accels_x.x < 0 ) {
trim_pitch = -trim_pitch;
}
}
#endif // __AVR_ATmega1280__
// save parameters to eeprom
void AP_InertialSensor::_save_parameters()
{
_product_id.save();
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
_accel_scale[i].save();
_accel_offset[i].save();
_gyro_offset[i].save();
}
}
/*
update gyro and accel values from backends
*/
void AP_InertialSensor::update(void)
{
// during initialisation update() may be called without
// wait_for_sample(), and a wait is implied
wait_for_sample();
if (!_hil_mode) {
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
// mark sensors unhealthy and let update() in each backend
// mark them healthy via _publish_gyro() and
// _publish_accel()
_gyro_healthy[i] = false;
_accel_healthy[i] = false;
_delta_velocity_valid[i] = false;
_delta_angle_valid[i] = false;
}
for (uint8_t i=0; i<_backend_count; i++) {
_backends[i]->update();
}
// adjust health status if a sensor has a non-zero error count
// but another sensor doesn't.
bool have_zero_accel_error_count = false;
bool have_zero_gyro_error_count = false;
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
if (_accel_healthy[i] && _accel_error_count[i] == 0) {
have_zero_accel_error_count = true;
}
if (_gyro_healthy[i] && _gyro_error_count[i] == 0) {
have_zero_gyro_error_count = true;
}
}
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
if (_gyro_healthy[i] && _gyro_error_count[i] != 0 && have_zero_gyro_error_count) {
// we prefer not to use a gyro that has had errors
_gyro_healthy[i] = false;
}
if (_accel_healthy[i] && _accel_error_count[i] != 0 && have_zero_accel_error_count) {
// we prefer not to use a accel that has had errors
_accel_healthy[i] = false;
}
}
// set primary to first healthy accel and gyro
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
if (_gyro_healthy[i]) {
_primary_gyro = i;
break;
}
}
for (uint8_t i=0; i<INS_MAX_INSTANCES; i++) {
if (_accel_healthy[i]) {
_primary_accel = i;
break;
}
}
}
_have_sample = false;
}
/*
wait for a sample to be available. This is the function that
determines the timing of the main loop in ardupilot.
Ideally this function would return at exactly the rate given by the
sample_rate argument given to AP_InertialSensor::init().
The key output of this function is _delta_time, which is the time
over which the gyro and accel integration will happen for this
sample. We want that to be a constant time if possible, but if
delays occur we need to cope with them. The long term sum of
_delta_time should be exactly equal to the wall clock elapsed time
*/
void AP_InertialSensor::wait_for_sample(void)
{
if (_have_sample) {
// the user has called wait_for_sample() again without
// consuming the sample with update()
return;
}
uint32_t now = hal.scheduler->micros();
if (_next_sample_usec == 0 && _delta_time <= 0) {
// this is the first call to wait_for_sample()
_last_sample_usec = now - _sample_period_usec;
_next_sample_usec = now + _sample_period_usec;
goto check_sample;
}
// see how long it is till the next sample is due
if (_next_sample_usec - now <=_sample_period_usec) {
// we're ahead on time, schedule next sample at expected period
uint32_t wait_usec = _next_sample_usec - now;
hal.scheduler->delay_microseconds_boost(wait_usec);
uint32_t now2 = hal.scheduler->micros();
if (now2+100 < _next_sample_usec) {
timing_printf("shortsleep %u\n", (unsigned)(_next_sample_usec-now2));
}
if (now2 > _next_sample_usec+400) {
timing_printf("longsleep %u wait_usec=%u\n",
(unsigned)(now2-_next_sample_usec),
(unsigned)wait_usec);
}
_next_sample_usec += _sample_period_usec;
} else if (now - _next_sample_usec < _sample_period_usec/8) {
// we've overshot, but only by a small amount, keep on
// schedule with no delay
timing_printf("overshoot1 %u\n", (unsigned)(now-_next_sample_usec));
_next_sample_usec += _sample_period_usec;
} else {
// we've overshot by a larger amount, re-zero scheduling with
// no delay
timing_printf("overshoot2 %u\n", (unsigned)(now-_next_sample_usec));
_next_sample_usec = now + _sample_period_usec;
}
check_sample:
if (!_hil_mode) {
// we also wait for at least one backend to have a sample of both
// accel and gyro. This normally completes immediately.
bool gyro_available = false;
bool accel_available = false;
while (!gyro_available || !accel_available) {
for (uint8_t i=0; i<_backend_count; i++) {
gyro_available |= _backends[i]->gyro_sample_available();
accel_available |= _backends[i]->accel_sample_available();
}
if (!gyro_available || !accel_available) {
hal.scheduler->delay_microseconds(100);
}
}
}
now = hal.scheduler->micros();
_delta_time = (now - _last_sample_usec) * 1.0e-6f;
_last_sample_usec = now;
#if 0
{
static uint64_t delta_time_sum;
static uint16_t counter;
if (delta_time_sum == 0) {
delta_time_sum = _sample_period_usec;
}
delta_time_sum += _delta_time * 1.0e6f;
if (counter++ == 400) {
counter = 0;
hal.console->printf("now=%lu _delta_time_sum=%lu diff=%ld\n",
(unsigned long)now,
(unsigned long)delta_time_sum,
(long)(now - delta_time_sum));
}
}
#endif
_have_sample = true;
}
/*
support for setting accel and gyro vectors, for use by HIL
*/
void AP_InertialSensor::set_accel(uint8_t instance, const Vector3f &accel)
{
if (_accel_count == 0) {
// we haven't initialised yet
return;
}
if (instance < INS_MAX_INSTANCES) {
_accel[instance] = accel;
_accel_healthy[instance] = true;
if (_accel_count <= instance) {
_accel_count = instance+1;
}
}
}
void AP_InertialSensor::set_gyro(uint8_t instance, const Vector3f &gyro)
{
if (_gyro_count == 0) {
// we haven't initialised yet
return;
}
if (instance < INS_MAX_INSTANCES) {
_gyro[instance] = gyro;
_gyro_healthy[instance] = true;
if (_gyro_count <= instance) {
_gyro_count = instance+1;
_gyro_cal_ok[instance] = true;
}
}
}