FRC8592/2025-reefscape
Jan 2025 – Mar 2025
3 Months active
Languages Used
Java
Technical Skills
JavaRobot Command FrameworkSubsystem ControlAutonomous ProgrammingAutonomous RoutinesCommand-Based Framework
Jack Runski
PROFILE
Jack Runski
Jack R. developed and refined core robot control systems for the FRC8592/2025-reefscape repository over a three-month period, focusing on elevator, wrist, and scoring subsystems. He established a modular command-based architecture in Java, centralizing control logic to enable precise autonomous and teleoperated positioning. Jack integrated PID control and subsystem refactoring to improve reliability and maintainability, tuning elevator and wrist mechanisms for consistent scoring. He enhanced autonomous routines, improved documentation for maintainability, and addressed control input mapping bugs. His work demonstrated depth in embedded systems, robotics programming, and control systems, resulting in a robust foundation for future development and competition.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
16Total
Bugs
1
Commits
16
Features
5
Lines of code
1,091
Activity Months3
Your Network
18 peopleSame Organization
@novalabsrobotics.org1
Robert S. LeeMember
Shared Repositories
17
Work History
March 2025
4 Commits • 1 Features
Mar 1, 2025March 2025 highlights for FRC8592/2025-reefscape: delivered scoring tuning to refine algae-state handling and scoring positions, and stabilized control workflows to improve reliability during matches. Key features include tuning scoring positions and algae state parameters, plus fixes to control input mappings and periodic update reliability. These changes enhance scoring efficiency, operator reliability, and maintainability, enabling smoother competition runs and faster iteration cycles.
4 Commits • 1 Features
Mar 1, 2025March 2025 highlights for FRC8592/2025-reefscape: delivered scoring tuning to refine algae-state handling and scoring positions, and stabilized control workflows to improve reliability during matches. Key features include tuning scoring positions and algae state parameters, plus fixes to control input mappings and periodic update reliability. These changes enhance scoring efficiency, operator reliability, and maintainability, enabling smoother competition runs and faster iteration cycles.
March 2025
February 2025
11 Commits • 3 Features
Feb 1, 2025February 2025 monthly performance summary for FRC8592/2025-reefscape focused on delivering reliable elevator/wrist control, autonomous improvements, and maintainability enhancements. This period emphasizes business value through robust control, predictable autonomous behavior, and clear documentation to support ongoing development.
February 2025
11 Commits • 3 Features
Feb 1, 2025February 2025 monthly performance summary for FRC8592/2025-reefscape focused on delivering reliable elevator/wrist control, autonomous improvements, and maintainability enhancements. This period emphasizes business value through robust control, predictable autonomous behavior, and clear documentation to support ongoing development.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on elevator subsystem feature delivery for FRC8592/2025-reefscape. Delivered foundational Elevator Command System, new elevator commands, and centralization of control logic in ElevatorCommands class, establishing architecture for elevator, clock arm, and wrist subsystems. This work enables precise element positioning and sets up future improvements for autonomous/teleop gameplay and overall subsystem reliability.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on elevator subsystem feature delivery for FRC8592/2025-reefscape. Delivered foundational Elevator Command System, new elevator commands, and centralization of control logic in ElevatorCommands class, establishing architecture for elevator, clock arm, and wrist subsystems. This work enables precise element positioning and sets up future improvements for autonomous/teleop gameplay and overall subsystem reliability.
January 2025
Activity
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Quality Metrics
Correctness83.8%
Maintainability85.0%
Architecture81.2%
Performance78.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
Autonomous ProgrammingAutonomous RoutinesCommand-Based FrameworkConfigurationControl SystemsDocumentationEmbedded SystemsJavaLoggingMotor ControlPID ControlRobot Command FrameworkRobot ControlRobot ProgrammingRobotics
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