Sensor fusion with OpenLog Artemis with IMU

Hi,

I’m trying to implement a sensor fusion using accelerometer and gyro readings (6 DoF, I’m open to using magnetometer as well making it 9DoF).

Now I’ve tried implementing Madgwick and Mahoney https://x-io.co.uk/open-source-imu-and-ahrs-algorithms/ as well as Extended Kalman Filter https://www.youtube.com/watch?v=7HVPjkWOrLE but non of them seem to work and I really don’t know what I’m doing wrong.

What happends is:

  1. The complimentary filter is just bad…

  2. EKF algorithm diverges after 5 or so prediction steps…

  3. and 4. → Mahony and Madgwick: I just don’t know but the yaw pitch and roll values go from some MIN to some MAX value back and forth… For example, the yaw goes from -5 to 50 degrees and back to -5 while standing still on the table.

I’m using accelerometer and gyro data with low pass filter enabled, at 60 Hz (everything else is at default)

I know I’m not supposed to do this… But here is a link to my github repo where you can find what I’m doing: https://discordapp.com/channels/@me/978 … 4879759420

I tried using DMP for 6DoF and it works quite nicely actually, but I would like to implement that myself…

I know its a long shot, but does anyone have any sensor fusion code specifically for OpenLog Artemis with IMU?

If I can provide some additional information that would help You help me, please let me know!

Thank You for Your help and time!

Filip