
Ian Shi contributed to the StuyPulse/Aunt-Mary robotics repository by developing and refining autonomous navigation, control systems, and field interaction routines in Java. Over three months, he delivered 62 features and resolved 27 bugs, focusing on robust swerve drive control, vision-based alignment, and dynamic pathfinding for complex reef and coral scenarios. His work included state-space control for arm and elevator subsystems, dynamic obstacle generation, and safety guard logic to prevent collisions. Through disciplined code refactoring, configuration management, and telemetry improvements, Ian enhanced system reliability and maintainability, demonstrating depth in embedded systems, command-based programming, and real-time robotics software engineering.

April 2025 highlights for StuyPulse/Aunt-Mary: delivered core reliability improvements and advanced reef autonomy. Key items include shooter score button reliability fix, swerve velocity tuning, reef interaction/navigation enhancements, automated coral handling/autonomy improvements, and dynamic reef clearance obstacle generation. These changes reduce failure modes, improve autonomous reef tasks, and demonstrate robust control, planning, and code maintainability.
April 2025 highlights for StuyPulse/Aunt-Mary: delivered core reliability improvements and advanced reef autonomy. Key items include shooter score button reliability fix, swerve velocity tuning, reef interaction/navigation enhancements, automated coral handling/autonomy improvements, and dynamic reef clearance obstacle generation. These changes reduce failure modes, improve autonomous reef tasks, and demonstrate robust control, planning, and code maintainability.
March 2025 — StuyPulse/Aunt-Mary: Delivered focused improvements across vision, arm/elevator automation, autonomous behaviors, and code health. Vision alignment improvements reduced field errors by correcting y-offset conventions between Camera.java and LimelightVision.java. Arm/elevator controls were hardened with processor-level handling post algae acquisition, refined motion profiles, and safety checks to prevent collisions with opposite alliance reefs, increasing autonomous reliability and operator safety. Pathfinding cleanup removed unnecessary coral alignment logic, added a warmup pathfinding command to reduce start-up latency, and addressed known alignment glitches for coral stations, improving repeatability. General cleanup and refactoring improved maintainability, reduced logging noise, and simplified drive nudges, contributing to faster iteration and lower risk of regressions. Additional targeted work included onboard arm control loop migration, swerve feedforward for arm, and clearer motion profiling for debugging, enabling more predictable performance. Technologies/skills demonstrated: Java robotics development, Limelight integration and orientation updates, onboard motor control, motion profiling, swerve drive tuning, IMU management, and disciplined code hygiene.
March 2025 — StuyPulse/Aunt-Mary: Delivered focused improvements across vision, arm/elevator automation, autonomous behaviors, and code health. Vision alignment improvements reduced field errors by correcting y-offset conventions between Camera.java and LimelightVision.java. Arm/elevator controls were hardened with processor-level handling post algae acquisition, refined motion profiles, and safety checks to prevent collisions with opposite alliance reefs, increasing autonomous reliability and operator safety. Pathfinding cleanup removed unnecessary coral alignment logic, added a warmup pathfinding command to reduce start-up latency, and addressed known alignment glitches for coral stations, improving repeatability. General cleanup and refactoring improved maintainability, reduced logging noise, and simplified drive nudges, contributing to faster iteration and lower risk of regressions. Additional targeted work included onboard arm control loop migration, swerve feedforward for arm, and clearer motion profiling for debugging, enabling more predictable performance. Technologies/skills demonstrated: Java robotics development, Limelight integration and orientation updates, onboard motor control, motion profiling, swerve drive tuning, IMU management, and disciplined code hygiene.
February 2025 focused on delivering measurable business value through safer, faster configuration, stronger autonomous capabilities, and clearer observability. The team consolidated core automation patterns, improved hardware configuration ergonomics, and expanded end-to-end readiness for coral-algae-reef scoring scenarios, while tightening telemetry and guardrails to reduce risk during live operations.
February 2025 focused on delivering measurable business value through safer, faster configuration, stronger autonomous capabilities, and clearer observability. The team consolidated core automation patterns, improved hardware configuration ergonomics, and expanded end-to-end readiness for coral-algae-reef scoring scenarios, while tightening telemetry and guardrails to reduce risk during live operations.
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