FRC5188/ReefCode
Mar 2025 – Mar 2025
1 Month active
Languages Used
JSONJava
Technical Skills
Autonomous NavigationAutonomous Path PlanningAutonomous Path VisualizationAutonomous Routine ConfigurationAutonomous RoutinesComputer Vision
Henthorn Lab @ RHIT
PROFILE
Henthorn Lab @ Rhit
Henry Thorne developed end-to-end autonomous navigation and perception enhancements for the ReefCode repository, focusing on improving reliability and operator usability. He implemented vision system tuning, camera alignment, and swerve drive gain adjustments using Java, integrating simulation support to accelerate testing. By refining autonomous path planning with the PathPlanner library and enabling autonomous routines, he reduced manual intervention and improved safety. His work included auto-alignment input changes, operator UX cleanup, and the addition of tunable constants for reef element approaches. The depth of his contributions is reflected in robust configuration management and seamless integration of computer vision and control systems.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
14Total
Bugs
0
Commits
14
Features
4
Lines of code
2,321
Activity Months1
Your Network
15 peopleSame Organization
@rose-hulman.edu7
Work History
March 2025
14 Commits • 4 Features
Mar 1, 2025March 2025: ReefCode delivered end-to-end autonomous and perception enhancements for improved reliability, usability, and business value. Key work centered on tuning vision/perception, reinforcing reef-oriented autonomous behavior, refining operator UX, and enabling PathPlanner-based autonomous paths with simulation support. These efforts reduce manual intervention, accelerate testing, and enable safer, more capable autonomous operation.
14 Commits • 4 Features
Mar 1, 2025March 2025: ReefCode delivered end-to-end autonomous and perception enhancements for improved reliability, usability, and business value. Key work centered on tuning vision/perception, reinforcing reef-oriented autonomous behavior, refining operator UX, and enabling PathPlanner-based autonomous paths with simulation support. These efforts reduce manual intervention, accelerate testing, and enable safer, more capable autonomous operation.
March 2025
Activity
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Quality Metrics
Correctness80.8%
Maintainability82.8%
Architecture77.8%
Performance81.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJava
Technical Skills
Autonomous NavigationAutonomous Path PlanningAutonomous Path VisualizationAutonomous Routine ConfigurationAutonomous RoutinesComputer VisionConfiguration ManagementConstants ManagementControl SystemsEmbedded SystemsField2d WidgetGeometryJavaPID TuningPath Planning
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