Sensor Fusion Limitations & Razor

Hey!

I bought a SparkFun 9DOF Sensor Stick some time ago and everything is working fine with an Aduino and the Razor code, that uses the DCM algorithm to calculate the pitch/roll/yaw. However, I find that the YPR calculations are not accurate when I move the sensor really fast in x, y or z axis. So my first questions is: Is it possible to have accurate pitch/roll/yaw calculations when moving the sensor fast?

My goal is to have a sensor connected to an Arduino that can send pitch/roll/yaw calculations with a reasonable accuracy in a high speed/acceleration scenario (i.e. mounted to a racing drone). Can anybody help me with:

  • What IMU can I use? I was using the SparkFun 9DOF but it is not longer for sale. I wouldn't mind changing, as long as it has SPI or I2C to interface with an Arduino.
  • What algorithm can I use? The DCM used in Razor seems to be good, but as I explained I'm not getting accurate measurements when having acceleration along x,y or z axis.
  • What about Kalman filtering or complimentary filter? What are they limitations?

Thank you!

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Replies

  • ok, now we come to the heavy part.

    you might consider switching over to an arm derivate as mcu.

    the madgewick sensor fusion is somewhat more optimised.

    give google a try.

    7ms is very very slow for fast movements.

  • run the sensor fusion with new data all 2ms.

    that should help.

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