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FRC Team 2910's robot code for the 2024 FRC game CRESCENDO.

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2024CompetitionRobot

FRC Team 2910's robot code for the 2024 FRC game CRESCENDO.

Notable features include:

  • Continuous goal tracking
  • Absolute turret location calculation on startup
  • State machine architecture integrated with WPILIB subsystems
  • AdvantageKit logging and IO abstraction layers

Organization

Here's how we have organized our code logically.

Thanks to FRC Teams 254 and 6328 for the inspiration.

Packages

autos - contains autonomous frameworks and programs

commands - contains classic WPILIB commands

config - contains configuration frameworks with robot data

subsystems - contains robot subsystems and overall robot state machine/superstructure

util - contains utility classes

General

  1. Clone this repo
  2. Run ./gradlew to download gradle and needed FRC/Vendor libraries. (make sure you're using Java 17 or greater)
  3. Run ./gradlew downloadAll to download FRC tools (ShuffleBoard, etc.)
  4. Run ./gradlew tasks to see available options
  5. Have fun!

Visual Studio Code (Official IDE)

  1. Get the WPILib extension for easiest use from the VSCode Marketplace - Requires Java 17 or greater
  2. In .vscode/settings.json, set the User Setting, java.home, to the correct directory pointing to your JDK 17 directory

IntelliJ

  1. Run ./gradlew idea
  2. Open the 2024CompetitioRobot.ipr file with IntelliJ
  3. When prompted, select import Gradle build

Basic Gradle Commands

  • Run ./gradlew deploy to deploy to the robot in Terminal (*nix) or Powershell (Windows)
  • Run ./gradlew build to build the code. Use the --info flag for more details.
  • Run ./gradlew assemble to build the code without running all unit tests. Use the --info flag for more details.
  • Run ./gradlew test to run all the JUnit tests.

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FRC Team 2910's robot code for the 2024 FRC game CRESCENDO.

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License

MIT, GPL-3.0 licenses found

Licenses found

MIT
LICENSE
GPL-3.0
AdvantageKit-License.md

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