Az-RBSI

Arizona's Reference Build and Software Implementation for FRC robots, read as "A-Z-ribsy".

Az-RBSI is a robot-code template for teams that want a reliable swerve, odometry, vision, autonomous, logging, and tuning baseline without starting from an empty project.

Documentation

Start with the full documentation index:

• doc/README.md

Quick links:

• Install and project setup
• Getting started guide
• Constants guide
• Drive subsystem and Phoenix/YAGSL setup
• Vision setup and troubleshooting
• Autonomous setup
• SysId guide
• Pose buffer design notes
• AdvantageScope layout guide

New Team Flow

1. Read INSTALL.md and create your project.
2. Follow RBSI-GSG.md for first robot-code edits.
3. Configure Constants.java with RBSI-Constants.md.
4. Configure the drivetrain with RBSI-Drive.md.
5. Bring up cameras with RBSI-Vision.md.
6. Add autonomous paths with RBSI-Autonomous.md.
7. Open the standard layout with RBSI-AdvantageScope.md.
8. Characterize mechanisms with RBSI-SysId.md.

Experienced User Shortcuts

• Phoenix Tuner X generated constants: RBSI-Drive.md and src/main/java/frc/robot/generated/README
• PathPlanner and Choreo lifecycle: RBSI-Autonomous.md
• Disabled odometry and vision behavior: RBSI-PoseBuffer.md
• Camera transforms, filtering, and simulation: RBSI-Vision.md
• Constants tuning order: RBSI-Constants.md
• AdvantageScope pit-debug layout: RBSI-AdvantageScope.md

Purpose

Az-RBSI helps FRC teams with:

• improving autonomous reliability and performance,
• improving robot build, endurance, gameplay reliability, and troubleshooting,
• standardizing a robot stack so teams can set up software quickly,
• making it easier for Arizona teams to form effective in-state alliances.

Design Philosophy

Az-RBSI is centered around a reference robot that helps teams communicate quickly about gameplay strategy and troubleshooting. A shared robot design also makes it easier to swap spare parts and programming modules.

The software is a robot-program outline that teams can extend for their own mechanisms and game strategy. It combines actively maintained FIRST and community libraries with AdvantageKit logging so teams can diagnose problems from real match data.

Library Dependencies

• WPILib: FIRST robot libraries
• AdvantageKit: logging
• CTRE Phoenix 6: CTRE swerve
• PathPlanner: autonomous path planning
• PhotonVision and Limelight: robot vision
• Autopilot: teleop drive-to-pose

Workshop Slides

2026 REBUILT kickoff workshops:

• AZ RBSI and AdvantageKit
• Know Where You Are: PhotonVision for Alignment and Odometry

2025 Reefscape kickoff workshop:

• AZ Liftoff RBSI

Further Reading

• Command-based best practices
• RBSI releases