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:
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The complimentary filter is just bad…
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EKF algorithm diverges after 5 or so prediction steps…
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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