FRCTeam360/RainMaker25
Feb 2025 – Feb 2025
1 Month active
Languages Used
JSONJava
Technical Skills
Autonomous Path PlanningControl SystemsEmbedded SystemsJavaRoboticsRobotics Programming
RuotT
PROFILE
Ruott
During February 2025, Thiep Ruot enhanced the FRCTeam360/RainMaker25 robotics codebase by delivering three autonomous features focused on reliability and field performance. He refactored the coral path planning system, introducing new waypoint logic and event markers to improve navigation accuracy. Leveraging Java and embedded systems expertise, he upgraded the algae tilt mechanism by switching to absolute encoders and refining control setpoints, resulting in more precise actuation. Thiep also tuned drive train constants and PID gains, optimizing motor response and throughput. His work demonstrated depth in autonomous path planning, control systems, and hardware-software integration, yielding robust, production-ready robotics capabilities.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
3
Lines of code
257
Activity Months1
Your Network
8 peopleSame Organization
@bprep.org3
Work History
February 2025
3 Commits • 3 Features
Feb 1, 2025February 2025 (Month: 2025-02) — Delivered three high-impact autonomous capabilities and performance improvements for FRCTeam360/RainMaker25, strengthening reliability, harvest yield, and field readiness. Key features delivered: - Coral Path Planning Rework and New 3p Path: Refactored and renamed autonomous path; updated coral 3p path files with adjusted waypoint coordinates and elevator event markers; introduced Coral 3p Path 6.path. (Commit: 2e51dd10ea95e754bf29b32e2f73dc31253da948) - Algae Tilt Mechanism Precision Improvement: Fine-tuned tilt setpoints; updated default/controller positions; switched from relative to absolute encoder for more accurate position tracking to improve algae collection reliability. (Commit: 6babda9613eabfc8640fd8adc0d2351c5a2fa832) - Drive Train Tuning for Performance: Tuned drive train constants, PID gains, and feedforward for steer and drive motors; updated theoretical free speed to reflect new tuning for better robot performance. (Commit: 0697adc3684428a32aa1148b804f2cd3e2551783) Major bugs fixed: - No explicit critical bugs reported this month. Notable reliability and accuracy improvements were achieved through encoder updates and controller/tuning refinements. Overall impact and accomplishments: - Enhanced autonomy reliability for coral harvesting and algae collection due to improved planning, encoding, and control. - Increased mission throughput and decision confidence thanks to more accurate positioning and responsive drive behavior. - Clear demonstration of end-to-end path planning, precise actuation, and robust control loops in a production-ready configuration. Technologies/skills demonstrated: - Path planning and file/versioned path management; autonomous navigation. - Encoder integration (absolute vs relative) and position tracking accuracy. - PID and feedforward tuning; drive train constants; performance optimization. - System calibration, hardware-software integration, and deliverable documentation relationships (commit-level traceability).
3 Commits • 3 Features
Feb 1, 2025February 2025 (Month: 2025-02) — Delivered three high-impact autonomous capabilities and performance improvements for FRCTeam360/RainMaker25, strengthening reliability, harvest yield, and field readiness. Key features delivered: - Coral Path Planning Rework and New 3p Path: Refactored and renamed autonomous path; updated coral 3p path files with adjusted waypoint coordinates and elevator event markers; introduced Coral 3p Path 6.path. (Commit: 2e51dd10ea95e754bf29b32e2f73dc31253da948) - Algae Tilt Mechanism Precision Improvement: Fine-tuned tilt setpoints; updated default/controller positions; switched from relative to absolute encoder for more accurate position tracking to improve algae collection reliability. (Commit: 6babda9613eabfc8640fd8adc0d2351c5a2fa832) - Drive Train Tuning for Performance: Tuned drive train constants, PID gains, and feedforward for steer and drive motors; updated theoretical free speed to reflect new tuning for better robot performance. (Commit: 0697adc3684428a32aa1148b804f2cd3e2551783) Major bugs fixed: - No explicit critical bugs reported this month. Notable reliability and accuracy improvements were achieved through encoder updates and controller/tuning refinements. Overall impact and accomplishments: - Enhanced autonomy reliability for coral harvesting and algae collection due to improved planning, encoding, and control. - Increased mission throughput and decision confidence thanks to more accurate positioning and responsive drive behavior. - Clear demonstration of end-to-end path planning, precise actuation, and robust control loops in a production-ready configuration. Technologies/skills demonstrated: - Path planning and file/versioned path management; autonomous navigation. - Encoder integration (absolute vs relative) and position tracking accuracy. - PID and feedforward tuning; drive train constants; performance optimization. - System calibration, hardware-software integration, and deliverable documentation relationships (commit-level traceability).
February 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJava
Technical Skills
Autonomous Path PlanningControl SystemsEmbedded SystemsJavaRoboticsRobotics Programming
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