以下元記事「MARGセンサーから三次元方向推定！(Madgwickフィルター！)」付図
図1：IMU実装用の方向フィルタのブロック図
/*引用元「An efficient orientation filter for inertial and inertial/magnetic sensor arrays」Sebastian O.H. Madgwick(April 30, 2010)」*/
// Math library required for `sqrt'
#include <math.h>
// System constants
#define deltat 0.001f // sampling period in seconds (shown as 1 ms)
#define gyroMeasError 3.14159265358979f * (5.0f / 180.0f) // gyroscope measurement error in rad/s (shown as 5 deg/s)
#define beta sqrt(3.0f / 4.0f) * gyroMeasError // compute beta
// Global system variables
float a_x, a_y, a_z; // accelerometer measurements
float w_x, w_y, w_z; // gyroscope measurements in rad/s
float SEq_1 = 1.0f, SEq_2 = 0.0f, SEq_3 = 0.0f, SEq_4 = 0.0f; // estimated orientation quaternion elements with initial conditions
void filterUpdate(float w_x, float w_y, float w_z, float a_x, float a_y, float a_z)
{
// Local system variables
float norm; // vector norm
float SEqDot_omega_1, SEqDot_omega_2, SEqDot_omega_3, SEqDot_omega_4; // quaternion derrivative from gyroscopes elements
float f_1, f_2, f_3; // objective function elements
float J_11or24, J_12or23, J_13or22, J_14or21, J_32, J_33; // objective function Jacobian elements
float SEqHatDot_1, SEqHatDot_2, SEqHatDot_3, SEqHatDot_4; // estimated direction of the gyroscope error
// Axulirary variables to avoid reapeated calcualtions
float halfSEq_1 = 0.5f * SEq_1;
float halfSEq_2 = 0.5f * SEq_2;
float halfSEq_3 = 0.5f * SEq_3;
float halfSEq_4 = 0.5f * SEq_4;
float twoSEq_1 = 2.0f * SEq_1;
float twoSEq_2 = 2.0f * SEq_2;
float twoSEq_3 = 2.0f * SEq_3;
29
// Normalise the accelerometer measurement
norm = sqrt(a_x * a_x + a_y * a_y + a_z * a_z);
a_x /= norm;
a_y /= norm;
a_z /= norm;
// Compute the objective function and Jacobian
f_1 = twoSEq_2 * SEq_4 - twoSEq_1 * SEq_3 - a_x;
f_2 = twoSEq_1 * SEq_2 + twoSEq_3 * SEq_4 - a_y;
f_3 = 1.0f - twoSEq_2 * SEq_2 - twoSEq_3 * SEq_3 - a_z;
J_11or24 = twoSEq_3; // J_11 negated in matrix multiplication
J_12or23 = 2.0f * SEq_4;
J_13or22 = twoSEq_1; // J_12 negated in matrix multiplication
J_14or21 = twoSEq_2;
J_32 = 2.0f * J_14or21; // negated in matrix multiplication
J_33 = 2.0f * J_11or24; // negated in matrix multiplication
// Compute the gradient (matrix multiplication)
SEqHatDot_1 = J_14or21 * f_2 - J_11or24 * f_1;
SEqHatDot_2 = J_12or23 * f_1 + J_13or22 * f_2 - J_32 * f_3;
SEqHatDot_3 = J_12or23 * f_2 - J_33 * f_3 - J_13or22 * f_1;
SEqHatDot_4 = J_14or21 * f_1 + J_11or24 * f_2;
// Normalise the gradient
norm = sqrt(SEqHatDot_1 * SEqHatDot_1 + SEqHatDot_2 * SEqHatDot_2 + SEqHatDot_3 * SEqHatDot_3 + SEqHatDot_4 * SEqHatDot_4);
SEqHatDot_1 /= norm;
SEqHatDot_2 /= norm;
SEqHatDot_3 /= norm;
SEqHatDot_4 /= norm;
// Compute the quaternion derrivative measured by gyroscopes
SEqDot_omega_1 = -halfSEq_2 * w_x - halfSEq_3 * w_y - halfSEq_4 * w_z;
SEqDot_omega_2 = halfSEq_1 * w_x + halfSEq_3 * w_z - halfSEq_4 * w_y;
SEqDot_omega_3 = halfSEq_1 * w_y - halfSEq_2 * w_z + halfSEq_4 * w_x;
SEqDot_omega_4 = halfSEq_1 * w_z + halfSEq_2 * w_y - halfSEq_3 * w_x;
// Compute then integrate the estimated quaternion derrivative
SEq_1 += (SEqDot_omega_1 - (beta * SEqHatDot_1)) * deltat;
SEq_2 += (SEqDot_omega_2 - (beta * SEqHatDot_2)) * deltat;
SEq_3 += (SEqDot_omega_3 - (beta * SEqHatDot_3)) * deltat;
SEq_4 += (SEqDot_omega_4 - (beta * SEqHatDot_4)) * deltat;
// Normalise quaternion
norm = sqrt(SEq_1 * SEq_1 + SEq_2 * SEq_2 + SEq_3 * SEq_3 + SEq_4 * SEq_4);
SEq_1 /= norm;
SEq_2 /= norm;
SEq_3 /= norm;
SEq_4 /= norm;
}
void loop () {}
