FRC7902/Reefscape2025
Feb 2025 – Feb 2025
1 Month active
Languages Used
Java
Technical Skills
Command-Based FrameworkControl SystemsJavaRobot ControlRoboticsSwerve Drive
Arjun Bhatia
PROFILE
Arjun Bhatia
During February 2025, Reefscape2025 (FRC7902) developer Argon Boron focused on refining robot control systems within the Reefscape2025 repository. They enhanced elevator control by refactoring constants and utilities, improving setpoint accuracy, PID gains, CAN IDs, and unit conversions, which addressed gear ratio calculation issues. Argon also improved driver controls by implementing strafing via controller triggers and introducing an angle-snapping command, increasing maneuverability and precision during teleoperation. Working primarily in Java and leveraging the Command-Based Framework and swerve drive concepts, Argon’s contributions deepened the reliability and tunability of the robot’s control systems, supporting future competition readiness and iterative development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
249
Activity Months1
Your Network
6 peopleWork History
February 2025
2 Commits • 2 Features
Feb 1, 2025February 2025 performance summary for Reefscape2025 (FRC7902): Delivered targeted control system refinements to enhance precision, reliability, and maneuverability. Elevator control tuning refactored constants and utilities to improve setpoint accuracy, PID gains, CAN IDs, and unit conversions, including fixing meters/rotations conversions for the gear ratio. Driver controls were enhanced with strafing via trigger axes and an angle-snapping command to improve handling and precision. These changes, supported by bug fixes addressing kV/kA/feedforward behavior, reduce control errors, increase reliability, and streamline tuning for future iterations and competition readiness.
2 Commits • 2 Features
Feb 1, 2025February 2025 performance summary for Reefscape2025 (FRC7902): Delivered targeted control system refinements to enhance precision, reliability, and maneuverability. Elevator control tuning refactored constants and utilities to improve setpoint accuracy, PID gains, CAN IDs, and unit conversions, including fixing meters/rotations conversions for the gear ratio. Driver controls were enhanced with strafing via trigger axes and an angle-snapping command to improve handling and precision. These changes, supported by bug fixes addressing kV/kA/feedforward behavior, reduce control errors, increase reliability, and streamline tuning for future iterations and competition readiness.
February 2025
Activity
Loading activity data...
Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
Command-Based FrameworkControl SystemsJavaRobot ControlRoboticsSwerve DriveTeleoperation Control
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline