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I have two sensors providing a z-axis rotation estimate on a two-wheeled differential drive platform:
Does it make sense to use some algorithm to merge these two, or should I just rely on the gyro? If I should combine them, what's the proper algorithm to use (Kalman filter, Complementary filter, simple moving average, etc)?
I suggest you to use an Extended Kalman Filter. It can provide an estimation of the robot's orientation by filtering both wheel's and gyro's drifts.
Is there a simple implementation you can recommend, preferably that could run on an Arduino? All the ones I've found seem terribly complicated, and assume you're trying to merge two three-dimensional vectors representing accelerometer and gryoscope readings, not simple scalars, as I'm trying to do.
Asked: 2017-03-27 14:04:28 -0600
Seen: 456 times
Last updated: Mar 28 '17
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