File content as of revision 0:32b177f0030e:

#include "LSM9DS0_mbed.h"
#include "mbed.h"

#define INT1    PB_3
#define INT2    PA_10
#define DR_DYG  PB_5

#define SDA PB_9
#define SCL PB_8

///////////////////////
// Example I2C Setup //
///////////////////////
// SDO_XM and SDO_G are both grounded, so our addresses are:
#define LSM9DS0_XM  0x1D // Would be 0x1E if SDO_XM is LOW
#define LSM9DS0_G   0x6B // Would be 0x6A if SDO_G is LOW

// Create an instance of the LSM9DS0 library called `dof` the
// parameters for this constructor are:
// [I2C SDA], [I2C SCL],[gyro I2C address],[xm I2C add.]
LSM9DS0 dof(SDA, SCL, LSM9DS0_G, LSM9DS0_XM);

///////////////////////////////////
// Interrupt Handler Definitions //
///////////////////////////////////
DigitalIn INT1XM(INT1);
DigitalIn INT2XM(INT2);
DigitalIn DRDYG(DR_DYG);

// global constants for 9 DoF fusion and AHRS (Attitude and Heading Reference System)
#define GyroMeasError PI * (40.0f / 180.0f)       // gyroscope measurement error in rads/s (shown as 3 deg/s)
#define GyroMeasDrift PI * (0.0f / 180.0f)      // gyroscope measurement drift in rad/s/s (shown as 0.0 deg/s/s)
// There is a tradeoff in the beta parameter between accuracy and response speed.
// In the original Madgwick study, beta of 0.041 (corresponding to GyroMeasError of 2.7 degrees/s) was found to give optimal accuracy.
// However, with this value, the LSM9SD0 response time is about 10 seconds to a stable initial quaternion.
// Subsequent changes also require a longish lag time to a stable output, not fast enough for a quadcopter or robot car!
// By increasing beta (GyroMeasError) by about a factor of fifteen, the response time constant is reduced to ~2 sec
// I haven't noticed any reduction in solution accuracy. This is essentially the I coefficient in a PID control sense;
// the bigger the feedback coefficient, the faster the solution converges, usually at the expense of accuracy.
// In any case, this is the free parameter in the Madgwick filtering and fusion scheme.
#define beta sqrt(3.0f / 4.0f) * GyroMeasError   // compute beta
#define zeta sqrt(3.0f / 4.0f) * GyroMeasDrift   // compute zeta, the other free parameter in the Madgwick scheme usually set to a small or zero value
#define Kp 2.0f * 5.0f // these are the free parameters in the Mahony filter and fusion scheme, Kp for proportional feedback, Ki for integral
#define Ki 0.0f
const float  PI = 3.14159265358979f;

Timer t1;   //Integration timer
Timer t2;   //Print timer
Serial pc(SERIAL_TX, SERIAL_RX);
DigitalOut myled(LED1);
float pitch, yaw, roll, heading;
float deltat = 0.0f;        // integration interval for both filter schemes


float abias[3] = {0, 0, 0}, gbias[3] = {0, 0, 0};
float ax, ay, az, gx, gy, gz, mx, my, mz; // variables to hold latest sensor data values
float q[4] = {1.0f, 0.0f, 0.0f, 0.0f};    // vector to hold quaternion
float eInt[3] = {0.0f, 0.0f, 0.0f};       // vector to hold integral error for Mahony method
float temperature;

//////////////////////////////////
//      FUNCTION DECLARATION    //
//////////////////////////////////
void setup();
void loop();
void MadgwickQuaternionUpdate(float ax, float ay, float az, float gx, float gy, float gz, float mx, float my, float mz);
void MahonyQuaternionUpdate(float ax, float ay, float az, float gx, float gy, float gz, float mx, float my, float mz);
void dataGyro();
void dataAccel();
void dataMag();

//////////////////////////////////
//             MAIN             //
//////////////////////////////////
int main()
{
    setup();  //Setup sensor and Serial
    pc.printf("Setup Done\n\r");


    while (true)
        loop();
}


//////////////////////////////////
//          FUNCTION BODY       //
//////////////////////////////////
void dataGyro()
{
    dof.readGyro();           // Read raw gyro data
    gx = dof.calcGyro(dof.gx) - gbias[0];   // Convert to degrees per seconds, remove gyro biases
    gy = dof.calcGyro(dof.gy) - gbias[1];
    gz = dof.calcGyro(dof.gz) - gbias[2];
}
void dataAccel()
{
    dof.readAccel();         // Read raw accelerometer data
    ax = dof.calcAccel(dof.ax) - abias[0];   // Convert to g's, remove accelerometer biases
    ay = dof.calcAccel(dof.ay) - abias[1];
    az = dof.calcAccel(dof.az) - abias[2];
}
void dataMag()
{
    dof.readMag();           // Read raw magnetometer data
    mx = dof.calcMag(dof.mx);     // Convert to Gauss and correct for calibration
    my = dof.calcMag(dof.my);
    mz = dof.calcMag(dof.mz);
}
void setup()
{
    pc.baud(115200); // Start serial at 115200 bps
    myled = true;
    /*//Interrupt
    INT1XM.rise(&dataAccel);
    INT2XM.rise(&dataMag);
    DRDYG.rise(&dataGyro);
    */
    // begin() returns a 16-bit value which includes both the gyro
    // and accelerometers WHO_AM_I response. You can check this to
    // make sure communication was successful.
    uint16_t status = dof.begin();

    pc.printf("LSM9DS0 WHO_AM_I's returned: ");
    pc.printf("0x%X\t", status);
    pc.printf("Should be 0x49D4");
    pc.printf("\n\r");


// Set data output ranges; choose lowest ranges for maximum resolution
// Accelerometer scale can be: A_SCALE_2G, A_SCALE_4G, A_SCALE_6G, A_SCALE_8G, or A_SCALE_16G
    dof.setAccelScale(dof.A_SCALE_2G);
// Gyro scale can be:  G_SCALE__245, G_SCALE__500, or G_SCALE__2000DPS
    dof.setGyroScale(dof.G_SCALE_245DPS);
// Magnetometer scale can be: M_SCALE_2GS, M_SCALE_4GS, M_SCALE_8GS, M_SCALE_12GS
    dof.setMagScale(dof.M_SCALE_2GS);

// Set output data rates
// Accelerometer output data rate (ODR) can be: A_ODR_3125 (3.225 Hz), A_ODR_625 (6.25 Hz), A_ODR_125 (12.5 Hz), A_ODR_25, A_ODR_50,
//                                              A_ODR_100,  A_ODR_200, A_ODR_400, A_ODR_800, A_ODR_1600 (1600 Hz)
    dof.setAccelODR(dof.A_ODR_200); // Set accelerometer update rate at 100 Hz
// Accelerometer anti-aliasing filter rate can be 50, 194, 362, or 763 Hz
// Anti-aliasing acts like a low-pass filter allowing oversampling of accelerometer and rejection of high-frequency spurious noise.
// Strategy here is to effectively oversample accelerometer at 100 Hz and use a 50 Hz anti-aliasing (low-pass) filter frequency
// to get a smooth ~150 Hz filter update rate
    dof.setAccelABW(dof.A_ABW_50); // Choose lowest filter setting for low noise

// Gyro output data rates can be: 95 Hz (bandwidth 12.5 or 25 Hz), 190 Hz (bandwidth 12.5, 25, 50, or 70 Hz)
//                                 380 Hz (bandwidth 20, 25, 50, 100 Hz), or 760 Hz (bandwidth 30, 35, 50, 100 Hz)
    dof.setGyroODR(dof.G_ODR_190_BW_125);  // Set gyro update rate to 190 Hz with the smallest bandwidth for low noise

// Magnetometer output data rate can be: 3.125 (ODR_3125), 6.25 (ODR_625), 12.5 (ODR_125), 25, 50, or 100 Hz
    dof.setMagODR(dof.M_ODR_125); // Set magnetometer to update every 80 ms

// Use the FIFO mode to average accelerometer and gyro readings to calculate the biases, which can then be removed from
// all subsequent measurements.
    dof.calLSM9DS0(gbias, abias);

// Start timers to get integration time and print time
    t2.start();
    t1.start();
    dataGyro();
    dataAccel();
    dataMag();
}

void loop()
{
    //Couldn't manage to get these in interrupt, the interrupt won't fire. It isn't so nececesary indeed.
    if(INT1XM.read())
        dataAccel();
    if(INT2XM.read()) 
    {
        dataMag();
       // dof.readTemp(); Can't get temp reading from a Sparkfun breakout board, the problem is not just mine.
        //temperature = 21.0 + (float) dof.temperature/8.0f; // slope is 8 LSB per degree C, just guessing at the intercept
    }
    if(DRDYG.read())
        dataGyro();

    deltat = t1.read(); // set integration time by time elapsed since last filter update
    t1.reset();

    // Sensors x- and y-axes are aligned but magnetometer z-axis (+ down) is opposite to z-axis (+ up) of accelerometer and gyro!
    // This is ok by aircraft orientation standards!
    // Pass gyro rate as rad/s
    MadgwickQuaternionUpdate(ax, ay, az, gx*PI/180.0f, gy*PI/180.0f, gz*PI/180.0f, mx, my, mz);
//MahonyQuaternionUpdate(ax, ay, az, gx*PI/180.0f, gy*PI/180.0f, gz*PI/180.0f, mx, my, mz);


    // Serial print at 0.5 s rate independent of data rates
    if (t2.read() > 1.0f) {
        t2.reset();

        myled = !myled;

        pc.printf("%f\t%f\t%f\n\r", ax, ay, az);
        pc.printf("%f\t%f\t%f\n\r", gx, gy, gz);
        pc.printf("%f\t%f\t%f\n\r", mx, my, mz);
        /*
         // Define output variables from updated quaternion---these are Tait-Bryan angles, commonly used in aircraft orientation.
         // In this coordinate system, the positive z-axis is down toward Earth.
         // Yaw is the angle between Sensor x-axis and Earth magnetic North (or true North if corrected for local declination),
         // looking down on the sensor positive yaw is counterclockwise.
         // Pitch is angle between sensor x-axis and Earth ground plane, toward the Earth is positive, up toward the sky is negative.
         // Roll is angle between sensor y-axis and Earth ground plane, y-axis up is positive roll.
         // These arise from the definition of the homogeneous rotation matrix constructed from quaternions.
         // Tait-Bryan angles as well as Euler angles are non-commutative; that is, to get the correct orientation the rotations must be
         // applied in the correct order which for this configuration is yaw, pitch, and then roll.
         // For more see http://en.wikipedia.org/wiki/Conversion_between_quaternions_and_Euler_angles which has additional links.
         */
        yaw   = atan2(2.0f * (q[1] * q[2] + q[0] * q[3]), q[0] * q[0] + q[1] * q[1] - q[2] * q[2] - q[3] * q[3]);
        pitch = -asin(2.0f * (q[1] * q[3] - q[0] * q[2]));
        roll  = atan2(2.0f * (q[0] * q[1] + q[2] * q[3]), q[0] * q[0] - q[1] * q[1] - q[2] * q[2] + q[3] * q[3]);
        pitch *= 180.0f / PI;
        yaw   *= 180.0f / PI;
        roll  *= 180.0f / PI;
        //yaw   -= 13.8; // Declination at Danville, California is 13 degrees 48 minutes and 47 seconds on 2014-04-04

/*
        pc.printf("Temperature = ");
        pc.printf("%d\n\r", dof.temperature);
*/
        //Angles print
        pc.printf("Yaw, Pitch, Roll: ");
        pc.printf("%f", yaw);
        pc.printf(", ");
        pc.printf("%f", pitch);
        pc.printf(", ");
        pc.printf("%f\n\r", roll);

        //Update rate print
        pc.printf("Filter rate = ");
        pc.printf("%f\n\r", 1.0f/deltat);

        /*
        // The filter update rate can be increased by reducing the rate of data reading. The optimal implementation is
        // one which balances the competing rates so they are about the same; that is, the filter updates the sensor orientation
        // at about the same rate the data is changing. Of course, other implementations are possible. One might consider
        // updating the filter at twice the average new data rate to allow for finite filter convergence times.
        // The filter update rate is determined mostly by the mathematical steps in the respective algorithms,
        // the processor speed (8 MHz for the 3.3V Pro Mini), and the sensor ODRs, especially the magnetometer ODR:
        // smaller ODRs for the magnetometer produce the above rates, maximum magnetometer ODR of 100 Hz produces
        // filter update rates of ~110 and ~135 Hz for the Madgwick and Mahony schemes, respectively.
        // This is presumably because the magnetometer read takes longer than the gyro or accelerometer reads.
        // With low ODR settings of 100 Hz, 95 Hz, and 6.25 Hz for the accelerometer, gyro, and magnetometer, respectively,
        // the filter is updating at a ~150 Hz rate using the Madgwick scheme and ~200 Hz using the Mahony scheme.
        // These filter update rates should be fast enough to maintain accurate platform orientation for
        // stabilization control of a fast-moving robot or quadcopter. Compare to the update rate of 200 Hz
        // produced by the on-board Digital Motion Processor of Invensense's MPU6050 6 DoF and MPU9150 9DoF sensors.
        // The 3.3 V 8 MHz Pro Mini is doing pretty well!
        */
    }
}




// Implementation of Sebastian Madgwick's "...efficient orientation filter for... inertial/magnetic sensor arrays"
// (see http://www.x-io.co.uk/category/open-source/ for examples and more details)
// which fuses acceleration, rotation rate, and magnetic moments to produce a quaternion-based estimate of absolute
// device orientation -- which can be converted to yaw, pitch, and roll. Useful for stabilizing quadcopters, etc.
// The performance of the orientation filter is at least as good as conventional Kalman-based filtering algorithms
// but is much less computationally intensive---it can be performed on a 3.3 V Pro Mini operating at 8 MHz!
void MadgwickQuaternionUpdate(float ax, float ay, float az, float gx, float gy, float gz, float mx, float my, float mz)
{
    float q1 = q[0], q2 = q[1], q3 = q[2], q4 = q[3];   // short name local variable for readability
    float norm;
    float hx, hy, _2bx, _2bz;
    float s1, s2, s3, s4;
    float qDot1, qDot2, qDot3, qDot4;

    // Auxiliary variables to avoid repeated arithmetic
    float _2q1mx;
    float _2q1my;
    float _2q1mz;
    float _2q2mx;
    float _4bx;
    float _4bz;
    float _2q1 = 2.0f * q1;
    float _2q2 = 2.0f * q2;
    float _2q3 = 2.0f * q3;
    float _2q4 = 2.0f * q4;
    float _2q1q3 = 2.0f * q1 * q3;
    float _2q3q4 = 2.0f * q3 * q4;
    float q1q1 = q1 * q1;
    float q1q2 = q1 * q2;
    float q1q3 = q1 * q3;
    float q1q4 = q1 * q4;
    float q2q2 = q2 * q2;
    float q2q3 = q2 * q3;
    float q2q4 = q2 * q4;
    float q3q3 = q3 * q3;
    float q3q4 = q3 * q4;
    float q4q4 = q4 * q4;

    // Normalise accelerometer measurement
    norm = sqrt(ax * ax + ay * ay + az * az);
    if (norm == 0.0f) return; // handle NaN
    norm = 1.0f/norm;
    ax *= norm;
    ay *= norm;
    az *= norm;

    // Normalise magnetometer measurement
    norm = sqrt(mx * mx + my * my + mz * mz);
    if (norm == 0.0f) return; // handle NaN
    norm = 1.0f/norm;
    mx *= norm;
    my *= norm;
    mz *= norm;

    // Reference direction of Earth's magnetic field
    _2q1mx = 2.0f * q1 * mx;
    _2q1my = 2.0f * q1 * my;
    _2q1mz = 2.0f * q1 * mz;
    _2q2mx = 2.0f * q2 * mx;
    hx = mx * q1q1 - _2q1my * q4 + _2q1mz * q3 + mx * q2q2 + _2q2 * my * q3 + _2q2 * mz * q4 - mx * q3q3 - mx * q4q4;
    hy = _2q1mx * q4 + my * q1q1 - _2q1mz * q2 + _2q2mx * q3 - my * q2q2 + my * q3q3 + _2q3 * mz * q4 - my * q4q4;
    _2bx = sqrt(hx * hx + hy * hy);
    _2bz = -_2q1mx * q3 + _2q1my * q2 + mz * q1q1 + _2q2mx * q4 - mz * q2q2 + _2q3 * my * q4 - mz * q3q3 + mz * q4q4;
    _4bx = 2.0f * _2bx;
    _4bz = 2.0f * _2bz;

    // Gradient decent algorithm corrective step
    s1 = -_2q3 * (2.0f * q2q4 - _2q1q3 - ax) + _2q2 * (2.0f * q1q2 + _2q3q4 - ay) - _2bz * q3 * (_2bx * (0.5f - q3q3 - q4q4) + _2bz * (q2q4 - q1q3) - mx) + (-_2bx * q4 + _2bz * q2) * (_2bx * (q2q3 - q1q4) + _2bz * (q1q2 + q3q4) - my) + _2bx * q3 * (_2bx * (q1q3 + q2q4) + _2bz * (0.5f - q2q2 - q3q3) - mz);
    s2 = _2q4 * (2.0f * q2q4 - _2q1q3 - ax) + _2q1 * (2.0f * q1q2 + _2q3q4 - ay) - 4.0f * q2 * (1.0f - 2.0f * q2q2 - 2.0f * q3q3 - az) + _2bz * q4 * (_2bx * (0.5f - q3q3 - q4q4) + _2bz * (q2q4 - q1q3) - mx) + (_2bx * q3 + _2bz * q1) * (_2bx * (q2q3 - q1q4) + _2bz * (q1q2 + q3q4) - my) + (_2bx * q4 - _4bz * q2) * (_2bx * (q1q3 + q2q4) + _2bz * (0.5f - q2q2 - q3q3) - mz);
    s3 = -_2q1 * (2.0f * q2q4 - _2q1q3 - ax) + _2q4 * (2.0f * q1q2 + _2q3q4 - ay) - 4.0f * q3 * (1.0f - 2.0f * q2q2 - 2.0f * q3q3 - az) + (-_4bx * q3 - _2bz * q1) * (_2bx * (0.5f - q3q3 - q4q4) + _2bz * (q2q4 - q1q3) - mx) + (_2bx * q2 + _2bz * q4) * (_2bx * (q2q3 - q1q4) + _2bz * (q1q2 + q3q4) - my) + (_2bx * q1 - _4bz * q3) * (_2bx * (q1q3 + q2q4) + _2bz * (0.5f - q2q2 - q3q3) - mz);
    s4 = _2q2 * (2.0f * q2q4 - _2q1q3 - ax) + _2q3 * (2.0f * q1q2 + _2q3q4 - ay) + (-_4bx * q4 + _2bz * q2) * (_2bx * (0.5f - q3q3 - q4q4) + _2bz * (q2q4 - q1q3) - mx) + (-_2bx * q1 + _2bz * q3) * (_2bx * (q2q3 - q1q4) + _2bz * (q1q2 + q3q4) - my) + _2bx * q2 * (_2bx * (q1q3 + q2q4) + _2bz * (0.5f - q2q2 - q3q3) - mz);
    norm = sqrt(s1 * s1 + s2 * s2 + s3 * s3 + s4 * s4);    // normalise step magnitude
    norm = 1.0f/norm;
    s1 *= norm;
    s2 *= norm;
    s3 *= norm;
    s4 *= norm;

    // Compute rate of change of quaternion
    qDot1 = 0.5f * (-q2 * gx - q3 * gy - q4 * gz) - beta * s1;
    qDot2 = 0.5f * (q1 * gx + q3 * gz - q4 * gy) - beta * s2;
    qDot3 = 0.5f * (q1 * gy - q2 * gz + q4 * gx) - beta * s3;
    qDot4 = 0.5f * (q1 * gz + q2 * gy - q3 * gx) - beta * s4;

    // Integrate to yield quaternion
    q1 += qDot1 * deltat;
    q2 += qDot2 * deltat;
    q3 += qDot3 * deltat;
    q4 += qDot4 * deltat;
    norm = sqrt(q1 * q1 + q2 * q2 + q3 * q3 + q4 * q4);    // normalise quaternion
    norm = 1.0f/norm;
    q[0] = q1 * norm;
    q[1] = q2 * norm;
    q[2] = q3 * norm;
    q[3] = q4 * norm;

}



// Similar to Madgwick scheme but uses proportional and integral filtering on the error between estimated reference vectors and
// measured ones.
void MahonyQuaternionUpdate(float ax, float ay, float az, float gx, float gy, float gz, float mx, float my, float mz)
{
    float q1 = q[0], q2 = q[1], q3 = q[2], q4 = q[3];   // short name local variable for readability
    float norm;
    float hx, hy, bx, bz;
    float vx, vy, vz, wx, wy, wz;
    float ex, ey, ez;
    float pa, pb, pc;

    // Auxiliary variables to avoid repeated arithmetic
    float q1q1 = q1 * q1;
    float q1q2 = q1 * q2;
    float q1q3 = q1 * q3;
    float q1q4 = q1 * q4;
    float q2q2 = q2 * q2;
    float q2q3 = q2 * q3;
    float q2q4 = q2 * q4;
    float q3q3 = q3 * q3;
    float q3q4 = q3 * q4;
    float q4q4 = q4 * q4;

    // Normalise accelerometer measurement
    norm = sqrt(ax * ax + ay * ay + az * az);
    if (norm == 0.0f) return; // handle NaN
    norm = 1.0f / norm;        // use reciprocal for division
    ax *= norm;
    ay *= norm;
    az *= norm;

    // Normalise magnetometer measurement
    norm = sqrt(mx * mx + my * my + mz * mz);
    if (norm == 0.0f) return; // handle NaN
    norm = 1.0f / norm;        // use reciprocal for division
    mx *= norm;
    my *= norm;
    mz *= norm;

    // Reference direction of Earth's magnetic field
    hx = 2.0f * mx * (0.5f - q3q3 - q4q4) + 2.0f * my * (q2q3 - q1q4) + 2.0f * mz * (q2q4 + q1q3);
    hy = 2.0f * mx * (q2q3 + q1q4) + 2.0f * my * (0.5f - q2q2 - q4q4) + 2.0f * mz * (q3q4 - q1q2);
    bx = sqrt((hx * hx) + (hy * hy));
    bz = 2.0f * mx * (q2q4 - q1q3) + 2.0f * my * (q3q4 + q1q2) + 2.0f * mz * (0.5f - q2q2 - q3q3);

    // Estimated direction of gravity and magnetic field
    vx = 2.0f * (q2q4 - q1q3);
    vy = 2.0f * (q1q2 + q3q4);
    vz = q1q1 - q2q2 - q3q3 + q4q4;
    wx = 2.0f * bx * (0.5f - q3q3 - q4q4) + 2.0f * bz * (q2q4 - q1q3);
    wy = 2.0f * bx * (q2q3 - q1q4) + 2.0f * bz * (q1q2 + q3q4);
    wz = 2.0f * bx * (q1q3 + q2q4) + 2.0f * bz * (0.5f - q2q2 - q3q3);

    // Error is cross product between estimated direction and measured direction of gravity
    ex = (ay * vz - az * vy) + (my * wz - mz * wy);
    ey = (az * vx - ax * vz) + (mz * wx - mx * wz);
    ez = (ax * vy - ay * vx) + (mx * wy - my * wx);
    if (Ki > 0.0f) {
        eInt[0] += ex;      // accumulate integral error
        eInt[1] += ey;
        eInt[2] += ez;
    } else {
        eInt[0] = 0.0f;     // prevent integral wind up
        eInt[1] = 0.0f;
        eInt[2] = 0.0f;
    }

    // Apply feedback terms
    gx = gx + Kp * ex + Ki * eInt[0];
    gy = gy + Kp * ey + Ki * eInt[1];
    gz = gz + Kp * ez + Ki * eInt[2];

    // Integrate rate of change of quaternion
    pa = q2;
    pb = q3;
    pc = q4;
    q1 = q1 + (-q2 * gx - q3 * gy - q4 * gz) * (0.5f * deltat);
    q2 = pa + (q1 * gx + pb * gz - pc * gy) * (0.5f * deltat);
    q3 = pb + (q1 * gy - pa * gz + pc * gx) * (0.5f * deltat);
    q4 = pc + (q1 * gz + pa * gy - pb * gx) * (0.5f * deltat);

    // Normalise quaternion
    norm = sqrt(q1 * q1 + q2 * q2 + q3 * q3 + q4 * q4);
    norm = 1.0f / norm;
    q[0] = q1 * norm;
    q[1] = q2 * norm;
    q[2] = q3 * norm;
    q[3] = q4 * norm;

}