What margin of error is tolerable in FRC?

[Tristan Lall]

Originally Posted by davidthefat

What margin of error is tolerable in FRC? After running tests with last year's robot, the margin of error on the drive train encoder output was 1.45% and 3.45%. That seems insignificant, but is it? Would a kalman filter be necessary if this data was getting put into a PID control loop?

I'm actually more interested in what margin of error is acceptable for the officials' decisions—and that's kind of what I hoped the thread was about when I saw it in the portal—but that's a subject for another thread.

What's the second sensor for the Kalman filter? Even without knowing the plan, given that many teams do without even PID, my educated guess would be that you can get away without it—so it's not "necessary". Are you planning to use this for autonomous modes, or just for analyzing robot motion after the fact? How accurate are your measurements, anyway? What are you using as the baseline? Have you considered how much error is inherent to backlash in the drivetrain, for example?

The real answer is that it depends. You're going to need to define what's important to you, and assess it in that framework. Do some failure mode analysis: if the error on the encoder is 3%, and given certain other assumptions about the robot, what are the effects? Are those tolerable to you?

Another part of the analysis concerns how difficult it is for you to acquire or implement a suitable Kalman filter. Are you good at coding? Do you understand the principle of operation? What other things could you be doing instead of implementing a Kalman filter?