Quote:
Originally Posted by Jared341
Austin,
Could you or one of your programmers explain the rationale behind the design of your victor_linearize function? You average 5th and 7th order polynomials together, but it isn't obvious why you do this.
Thanks
This question was brought on by this thread: http://www.chiefdelphi.com/forums/sh...02#post1085502 |
Sure. I wrote this function in 2010, so I'm quite qualified to answer any questions.
Here is the data and the three polynomials that are in the function.
I generated the red data points by putting the robot up on blocks and applying PWM to the motors. I then read out the wheel speed at steady state for various PWM values.
From there, I tried to fit the data. I first started with a 5th order odd polynomial (The + and - response should be the same, which means that f(x) = -f(-x)). It is shown in green. That wasn't a great fit, so I tried a 7th order polynomial, shown in blue. Neither of them were great fits. They are not monatonically increasing functions. When you drive the robot with them, the robot doesn't feel like the throttle is a consistent function, and it feels weird (it has been a while, and feelings don't translate to words so well.)
From there, on a whim, I tried averaging the two functions. This actually turned out quite well. But, when I put it on the robot, it felt like the power was reduced too much at low speeds. To try to compensate for this, I added in a bit of y=x to get the equation shown in the legend above for the pink plot and to boost the power applied at low speeds. This is what is in use today in the victor_linearize function.