ZEBRA Data Analysis (1 of 3): Overview and Motion
By Caleb Sykes
Happy holidays everyone! Here’s a present that might help tide you over until kickoff. I’m beginning a 3-part series on analyzing ZEBRA Dart data. This is the first entry of the series, focusing on a general overview of the system and motion profiles.
Last year, we started to see an uptick in the number of events that used ZEBRA Dart systems. These systems essentially provide real-time position estimates for every robot on the field in every match. The uses for this kind of data are virtually endless. I’ve been thinking for a long time about what would be the most sensical way to break down this data to make it as useful as possible. I’ve decided that I want a standalone tool that is easy to pick up and quickly customizable between years. As such, I’ve created a workbook called the ZEBRA Data Parser, which you can find on GitHub here.
I am planning to release three additional updates to this tool before the first 2020 event, two based on 2019 data (along with blog posts describing the updates), and one to pave the way for 2020. In the 2020 season, I am planning to pull data directly from this book into my scouting database for all in-season events that are equipped with Dart systems. This blog post will describe the basic capabilities of the data parser, and will help to lay the groundwork for more advanced analysis in future updates of it. Everything here is a work in progress, so if you have any bug reports or feature requests feel free to reach out to me. With that, let’s start with an overview of what data is provided to us by the Zebra system.
Check out the rest of the article here: https://blog.thebluealliance.com/2019/12/28/zebra-data-analysis-1-of-3-overview-and-motion/