paper: Team 341 Vision System Code

[Tom Bottiglieri]

Thanks for posting this, Jared. I took a look at your dashboard on the field at Champs and was very impressed. It seems incredibly useful to have the vision system draw its idea of target state on top of the real image.

I suspect if vision is a part of upcoming games, we will probably use a solution very similar to this. This year we wrote all of our vision code on top of WPILib/NIVision to run on the cRIO. In the end we got this to work pretty well, but development and debugging was a bit of a pain compared to your system.

[Leeebowitz]

Very cool! I just finished taking an online data structures course from IIT, so it was really awesome to see the implementation of the TreeMap! Just so that I'm sure I understand, it is used to quickly find an rpm based on your distance, right? What are the advantages (if any) of using this instead of plugging your data points into an excel graph and getting a polynomial best fit equation to transform your distance into an rpm?

[Jared Russell]

Originally Posted by Leeebowitz

Very cool! I just finished taking an online data structures course from IIT, so it was really awesome to see the implementation of the TreeMap! Just so that I'm sure I understand, it is used to quickly find an rpm based on your distance, right? What are the advantages (if any) of using this instead of plugging your data points into an excel graph and getting a polynomial best fit equation to transform your distance into an rpm?

The biggest advantage was it made tuning very easy. Take the bot to the practice field with some balls, fire away, and record the range/RPM information into the TreeMap if you like what you saw (we actually had a version of the software that let the operator do this with the push of a "commit" button, but we ended up doing it all by hand just to sanitize the values). No need to fire up Excel.

[Jared Russell]

Originally Posted by Tom Bottiglieri

I suspect if vision is a part of upcoming games, we will probably use a solution very similar to this. This year we wrote all of our vision code on top of WPILib/NIVision to run on the cRIO. In the end we got this to work pretty well, but development and debugging was a bit of a pain compared to your system.

By far the biggest advantage of a laptop-based solution was the development process that it facilitated. Simply collect some representative images and then you can go off and tune your vision software on a laptop without needing a cRIO or the FRC control system.