Byron-MN-FRC/REEFSCAPE2025
Jan 2025 – Aug 2025
4 Months active
Languages Used
JavaJSON
Technical Skills
Control SystemsEmbedded SystemsRoboticsAutonomous RoutinesCode RefactoringCommand-Based Framework
p-reeve1
PROFILE
P-reeve1
Paxton Reeve developed and enhanced core robotics features for the Byron-MN-FRC/REEFSCAPE2025 repository, focusing on autonomous path planning, subsystem integration, and operator interface improvements. Over four months, Paxton overhauled manipulation and handling subsystems, implemented coordinated autonomous routines, and introduced a centralized dashboard configuration with web server integration. Using Java and JSON, Paxton refactored command-based architectures, tuned PID controllers for swerve and elevator systems, and integrated vision processing with Limelight. The work emphasized maintainability and reproducibility, with thorough documentation and configuration management. These contributions improved trajectory tracking, operator visibility, and testing efficiency, demonstrating depth in robotics software engineering and control systems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
20Total
Bugs
0
Commits
20
Features
7
Lines of code
6,047
Activity Months4
Your Network
8 people
Work History
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025: Delivered a Dashboard Configuration and Web Server for the Robot Dashboard in Byron-MN-FRC/REEFSCAPE2025, centralizing UI layouts and enabling live hosting of dashboards (SmartDashboard, LiveWindow, DriverDashboard, Testing). Replaced the previous DriverElastic2025 configuration and updated UI tabs across Teleoperated, Autonomous, DriverDashboard, and TESTING. This work enhances operator visibility, accelerates testing cycles, and improves maintainability of the UI layer.
2 Commits • 1 Features
Aug 1, 2025August 2025: Delivered a Dashboard Configuration and Web Server for the Robot Dashboard in Byron-MN-FRC/REEFSCAPE2025, centralizing UI layouts and enabling live hosting of dashboards (SmartDashboard, LiveWindow, DriverDashboard, Testing). Replaced the previous DriverElastic2025 configuration and updated UI tabs across Teleoperated, Autonomous, DriverDashboard, and TESTING. This work enhances operator visibility, accelerates testing cycles, and improves maintainability of the UI layer.
August 2025
March 2025
11 Commits • 3 Features
Mar 1, 2025March 2025: Core autonomous control and testing enhancements across the ReefScape2025 project, delivering three major feature areas: Coral/Algae Handling overhaul, Elevator/Shoulder control enhancements, and Vision/UI/Testing improvements. These changes increase autonomous reliability, reduce manual intervention, and accelerate validation for future iterations. Notable outcomes include updated pathing and sub-systems for coral/algae workflows, stabilized vertical positioning via improved homing and PID tuning, and enhanced Shuffleboard-based testing with Limelight vision integration.
March 2025
11 Commits • 3 Features
Mar 1, 2025March 2025: Core autonomous control and testing enhancements across the ReefScape2025 project, delivering three major feature areas: Coral/Algae Handling overhaul, Elevator/Shoulder control enhancements, and Vision/UI/Testing improvements. These changes increase autonomous reliability, reduce manual intervention, and accelerate validation for future iterations. Notable outcomes include updated pathing and sub-systems for coral/algae workflows, stabilized vertical positioning via improved homing and PID tuning, and enhanced Shuffleboard-based testing with Limelight vision integration.
February 2025
6 Commits • 2 Features
Feb 1, 2025February 2025: Delivered a major overhaul of the robot manipulation subsystem and optimized autonomous routines for REEFSCAPE2025. Implemented a comprehensive control set for claw, elevator, shoulder, and wrist, refactored the RobotContainer, and established the groundwork for advanced tasks (grab/place/store/climb). Also parallelized autonomous actions and clarified path naming to boost reliability and throughput. Achieved stability improvements by removing deprecated wrist references and tuning shoulder positions and limits, aligning the codebase with the Falcon-based hardware and cross-team changes.
6 Commits • 2 Features
Feb 1, 2025February 2025: Delivered a major overhaul of the robot manipulation subsystem and optimized autonomous routines for REEFSCAPE2025. Implemented a comprehensive control set for claw, elevator, shoulder, and wrist, refactored the RobotContainer, and established the groundwork for advanced tasks (grab/place/store/climb). Also parallelized autonomous actions and clarified path naming to boost reliability and throughput. Achieved stability improvements by removing deprecated wrist references and tuning shoulder positions and limits, aligning the codebase with the Falcon-based hardware and cross-team changes.
February 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 – Byron-MN-FRC/REEFSCAPE2025: Delivered targeted swerve drive control tuning to enhance precision and responsiveness, completed drive and steer PID/feedforward tuning and encoder offset adjustments, and closed the characterization loop with final gains. This work improves trajectory tracking, reduces settling time, and enhances autonomous reliability, contributing to more consistent match performance and easier tuning in future iterations. Tech stack included PID tuning, encoder alignment, and data-driven characterization; all changes committed for reproducibility.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 – Byron-MN-FRC/REEFSCAPE2025: Delivered targeted swerve drive control tuning to enhance precision and responsiveness, completed drive and steer PID/feedforward tuning and encoder offset adjustments, and closed the characterization loop with final gains. This work improves trajectory tracking, reduces settling time, and enhances autonomous reliability, contributing to more consistent match performance and easier tuning in future iterations. Tech stack included PID tuning, encoder alignment, and data-driven characterization; all changes committed for reproducibility.
Activity
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Quality Metrics
Correctness83.0%
Maintainability82.0%
Architecture82.0%
Performance75.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJava
Technical Skills
Autonomous Path PlanningAutonomous RoutinesCode RefactoringCommand-Based ArchitectureCommand-Based FrameworkConfiguration ManagementControl SystemsDashboard ConfigurationDashboard DevelopmentEmbedded SystemsJavaJava DevelopmentMotor ControlPath PlanningRobot Command Programming
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