Team 5010 · Spitfire & Tigershark · 2023-2025
FRC Competition Robotics
I led Java software for two competition robots spanning autonomous and teleoperated motion, perception, aiming, and game-piece handling.
Expanded technical stack
Overview
Our software team needed robust field localization and automation that could keep working through the variability of real FRC matches.
My contribution
As team co-lead, I led Java development across drivetrain, vision, aiming, and game-piece systems. I built calibrated camera-based 3D pose estimation with sensor fusion and beam-break sensing, plus predictive auto-aim and anti-tip controls.
Challenge
I needed to turn noisy camera and mechanism data into reliable autonomous behavior while keeping drivers fast and the robot stable under match conditions.
Technical approach
I integrated calibrated 3D vision, state estimation, sensor fusion, automated loading, predictive shot targeting, and anti-tip logic across autonomous and teleoperated systems.
Result / outcome
My predictive auto-aim increased the team's shot rate by more than 50%, while the anti-tip controls I developed eliminated competition tip-overs. I developed substantial portions of the Java robot software, including autonomous routines, drivetrain and control behavior, calibrated 3D computer vision, pose and state estimation, sensor fusion, predictive targeting, game-piece handling logic, and beam-break sensing and state logic. These systems materially improved scoring throughput, autonomous capability, targeting accuracy, robustness, and match reliability. My software contributions helped the team become Indiana State Runner-Up and qualify for the FIRST Robotics World Championship.
Gallery / media