Zebracorn Labs

Here at the Zebracorns, we believe in learning and pushing boundaries. In pursuit of that, we have published papers, given talks, and have other tidbits of knowledge lying around. We hope you enjoy these as much as we do.

27 Jun 2021 - Linden James, Diya Nerurkar, Marshall Massengill


Upon the occasion of the Global Innovation Competition, we were asked if we would like to share a regional recipe. Many of The Zebracorns enjoy baking so we were thrilled to be asked so that we could share our recipe for (Zebra)Cornbread, a true southern classic and something we hope others will enjoy.

17 Aug 2020 - Yashas Ambati, Gabe Hart, Kevin Jaget

Zebravision 7.0

During the past few years, we have focused on developing robust sensing and inference systems to accelerate our progress towards a fully autonomous robot. The ability to estimate the robot’s absolute position on the field is critical to achieving this goal. During the 2020 season, we made groundbreaking strides in this vein, developing systems to make our robot more environment-aware. In this paper, we introduce two systems: a neural network-based object detector and a particle filter localization system. We believe that neural networks are the future of computer vision in FRC; to help foster innovation in the FRC community, we release our dataset from this season.

06 Aug 2020 - Yashas Ambati, Olivia Fugikawa, Gabe Hart, Adam Kosinski, Trey Wiedmann, Nathan Yang, Viggy Dhanasekaran, Kevin Jaget, Marshall Massengill

ZebROS 2020

Over the past four years, the Zebracorns have created a modular design philosophy and development model based on the Robot Operating System (ROS). Last year, we focused on polishing the core elements and laying the foundation of our robot code base. During the 2020 season, we were able to leverage the advantages of this system as we continue to build upon our previous work. Many of this year’s improvements centered around reliability of the robot itself, as well as driver-robot interaction. Other improvements are new features that bring us closer to the goal of a fully autonomous robot.

26 Nov 2019 - Caleb Krellwitz, Camryn Byrum, Grace Sullivan, Kevin Jaget, Marshall Massengill, The Zebracorns

ZebROS Nano

At long last, we have scaled down our robot (but not our efforts) in an attempt to bring our work with ROS to more people. This tutorial focuses on our work with the NVIDIA Jetson Nano, a TileRunner Chassis from AndyMark, and Talon SRX Motor Controllers from Cross The Road Electronics to bring our ZebROS work to a larger audience. We think that the NVIDIA Jetson Nano is an excellent system to bring new robots online or bring older robots back to life and teach yourself some new skills around ROS in the process. We've done our best to make sure this Tutorial is easy to follow but we are releasing the document as a living Google document and not a PDF so that we can keep updating this as we get questions and eventually add even more to this tutorial. We're also releasing our complete software image for this so getting started is even easier.

26 Sep 2019 -

Collaborative Whitepapers Using Overleaf

Overleaf generously agreed to provide us with a premium subscription which allows us to keep and share the source code of our whitepapers. In this paper, we want to express our gratitude for their generosity, explain our process for writing, editing, and publishing whitepapers, and talk about the features of Overleaf that we like the most.

11 Sep 2019 - Niall Mullane

Terabee Sensors for Robot Alignment

During the 2019 season, we received some distance sensors from Terabee which we have been experimenting with throughout the competition season. This whitepaper discusses the alignment algorithms that we developed using the Terabee sensors and how successful they were for the 2019 game.