Table of Contents
This is the robot code for FRC Team 7913 Bearly Functioning's 2024 Crescendo Season. This will be our 4th season competing, and we're hoping to do well.
This season, we've tried to document our choices and how various components of the robot are implemented in an effort to be more open. We hope this benefits future teams, both ours and others, in understanding the process behind coding our robot and the choices that went into it. Take a look at our journal/documentation here.
- WPILib for just about everything
- REVLib for SPARK MAXes
- Phoenix 5 and Phoenix 6 for Victors and CANcoders, respectively
- PathPlanner for visually building and effortlessly executing autonomous routines
- REV Hardware Client for configuring SPARK MAXes
- Phoenix Tuner X for configuring Victors and CANcoders
- FRC Plugin for JetBrains IDEs
- SSH (macOS/Linux) or PuTTy (Windows) for cleaning up the RoboRIO of old PathPlanner paths and JAR deployments
- Graphite for code collaboration
This project is deployed in the same way as any other WPI Project. Their page also covers deployment.
This assumes you have a working RoboRio connected to power, with or without a transmitter.
Important: You must build the robot code once while connected to the Internet to download all the dependencies.
To ensure all dependencies are downloaded, you must build the robot code before connecting to the robot WiFi. There are three ways to do this.
- With WPILib VS Code, click on the WPILib icon or open the command palette and type "WPILib". Select
Build Robot Code. - In IntelliJ, run the
Build Robottask. - On the command line, run
gradle build(with Gradle installed),gradlew.bat build(on Windows), or./gradlew build(on macOS or Linux).
Once the code dependencies are installed, connect to the robot. There are two ways to do this.
- By WiFi. With the robot WiFi network set up, connect your computer to the robot's WiFi network
- By cable. Connect an ethernet cable from the robot to your computer.
With your computer connected to the robot, run the deploy task.
In VSCode, click on the WPILib icon or open the command palette and type WPILib. Select Deploy Robot Code.
In IntelliJ, select the Build & Deploy Robot command.
On the command line, run gradle deploy (with Gradle installed), gradlew.bat deploy (on Windows), or ./gradlew deploy (on macOS or Linux).
Each mode has a specific purpose.
Note
Limelight-based AprilTag localization was scrapped this season due to hardware issues and time constraints
Fully operable, uses cameras to calibrate field position. To turn off camera features when not on a field to avoid bad readings of AprilTags, use Test mode. Selecting a driver station to work from for simulation may be helpful, too.
Runs the robot without driver input. If cameras and sensing aren't available, check the box on the Shuffleboard to select only auto modes without camera features.
Note
This was never implemented
Has full driver control, but won't use cameras to calibrate position on field. Optionally, you can check a box to use camera calibration when running the shooter, which assumes you have AprilTags on a test Speaker.
For more examples, please refer to the Documentation
Note
This was wishful thinking and this wasn't used that much... Maybe next year?
See the project or the issue list for a full list of proposed features (and known issues).
Generally, work on this project will be done by the 7913 Programming team. Contributions, however, are welcome if you see some glaring issue.
The easiest way to contribute is to open an issue.
You can open an issue and tag it with bug or enhancement.
See our programming workflow document for full documentation of how our contribution process works. For external contributors, please consider using this process, which differs from the typical GitHub workflow. Using this enables us to more easily collaborate with you and work with greater efficiency and speed.
Distributed under the MIT License. See LICENSE for more information.
Team Email - frc7913@sau4.org
Project Link: https://github.com/FRC-7913/Crescendo-2024