Using AprilTags
AprilTags are a vital part of the modern FRC control system. They allow a robot to localize itself on the field without relying on dead-reckoning. Use the topics on this document to set up a robust AprilTag localization system.
PhotonVision
Team 401 uses a piece of open-source software called PhotonVision to run our vision pipeline. We recommend reading their docs to learn how to set it up for your year. Also feel free to read Common PhotonVision Problems.
Overlayroot
If you’re using a Beelink or other mini-PC running Ubuntu Server, we recommend setting up overlayroot to ensure the operating system survives a sudden power loss. If the PC shuts of suddenly without overlayroot enabled, you risk breaking the OS installation, and you will have to reinstall. See Using Overlayroot for more details.
Kalman Filter
As far as an FRC student is concerned, a Kalman filter is a giant pile of linear algebra that combines measurements from unreliable sources. For a robot pose estimator, one can specify expected standard deviations for the x-axis, the y-axis, and robot rotation or theta. For detailed, high school-level information on the mechanics of a Kalman filter, look here, here, or at the Matlab video series on the subject. For information on using WPIlib’s pose estimator object, look here.
For more information on what should inform AprilTag standard deviations, read What Affects AprilTag Accuracy?