After a few more tests, I now have the final version of the ArduIMU. The main problem was the calibration of the gyros: converting the raw data to degrees/s. I had to change the source code, compile it, upload, and repeat it over and over again. Totally waste of time.So i configured Arduino to externally adjust the gyros and the accelerometer jitter filter, using the nunchuck potentiometers (joystick axis). Now it’s working pretty well. =)Please, in the source code, ignore all the lines marked with "//(kalman)", this lines are related to the kalman filter code, those marked by "//(nunchuck) are related to nunchuck accelerometer and axis control, and all marked by "//(gyro)" are code related to the control of the gyroscope.Another tip, all the data is processed in radians, then is converted to degrees (radian*180/PI = radians*57.295779= degrees). If somebody needs any help, please feel free of asking me.Video:-Yellow color = Just Accelerometer read-Red color= Accelerometer+Gyro+KalmanFIiterArduino Source Code: http://sites.google.com/site/jordiuavs/Home/kalman_filter_by_Jordi.txt Labview (ground station) source code: http://sites.google.com/site/jordiuavs/Home/kalman_filter_by_Jordi.txt To do: -Integrate another Gyro (to make it dual axis) . -Program the SPI altimeter.-And put all the hardware together and make it work (GPS, Altimeter, IMU, Modem).
Done: -Servo control -Gps Waypoint navigation (I’ll post later about it).
The next article I'm going to post all the links to get started with Arduino environment. All you would need to learn: tutorials, examples, references, tips and tricks. If you already know C++ it’s going to be 99% easier. If not, you are going to discover why C/C++ is the most compressive and famous language ever ;-) Then jumping to any AVR, ARM, PIC microcontroller C/C++ language environment, is going to be a lot easier, because they’re all based on the same principles.
Comments
Thanks for the compliment...
Yes i been working in a fuction like this:
Kalman(Gyro, AccelXY, AccelZ);
And the return will be the estimated position in radians... Is better because i save code for the two axis that i need to know (pitch and roll).
I have this for now, is the function:
float kalman (float q_m, float angle_m)
{
/* Unbias our gyro */
const float q = q_m - q_bias; //(Kalman)
const float Pdot[2 * 2] = {
Q_angle - P[0][1] - P[1][0], /* 0,0 */ //(Kalman)
- P[1][1], /* 0,1 */
- P[1][1], /* 1,0 */
Q_gyro /* 1,1 */
};
/* Store our unbias gyro estimate */
float rate = q; //(Kalman)
/*
* Update our angle estimate
* angle += angle_dot * dt
* += (gyro - gyro_bias) * dt
* += q * dt
*/
angle += q * dt; //(Kalman)
/* Update the covariance matrix */
P[0][0] += Pdot[0] * dt; //(Kalman)
P[0][1] += Pdot[1] * dt; //(Kalman)
P[1][0] += Pdot[2] * dt; //(Kalman)
P[1][1] += Pdot[3] * dt; //(Kalman)
R_angle= (joy_y_axis+1)*0.0098039; //external adjust jitter of accelerometer
float angle_err = angle_m - angle; //(Kalman)
float C_0 = 1; //(Kalman)
float PCt_0 = C_0 * P[0][0]; //(Kalman)
float PCt_1 = C_0 * P[1][0]; //(Kalman)
float E =R_angle+ C_0 * PCt_0; //(Kalman)
float K_0 = PCt_0 / E; //(Kalman)
float K_1 = PCt_1 / E; //(Kalman)
float t_0 = PCt_0; /* C_0 * P[0][0] + C_1 * P[1][0] (Kalman) */
const float t_1 = C_0 * P[0][1]; /* + C_1 * P[1][1] = 0 (Kalman) */
P[0][0] -= K_0 * t_0; //(Kalman)
P[0][1] -= K_0 * t_1; //(Kalman)
P[1][0] -= K_1 * t_0; //(Kalman)
P[1][1] -= K_1 * t_1; //(Kalman)
angle += K_0 * angle_err; //(Kalman)
q_bias += K_1 * angle_err; //(Kalman)
return angle*RadToDeg;
}
Good Luck!
I loke your work very much :-)
I'm pretty new in this UAV thingy and want to start with a project similar like your arducopter but make it a bit more "generic".
-> the part i'm trying to do currently is to try to use Kalman filters as "library" or external functions in the Arduino environment (i want to just pass values and get the corrected flattened values as response)
Do you have an earlier version of the Kalman filter code around somewhere? without the specific raedings and settings for your hardware.
Cheers Chris ...
-
1
-
2
-
3
-
4
-
5
of 5 Next