
Worked on the Byron-MN-FRC/REEFSCAPE2025 repository to deliver two new features focused on autonomous robot control and subsystem optimization. Developed an overhauled claw and algae handling system, enabling separate coral and algae manipulation through new command structures and refined sensor integration. Enhanced startup and initialization by introducing a pre-initialization sequence and optimizing elevator constants, resulting in faster operational readiness. Applied skills in Java, embedded systems, and command-based frameworks to improve reliability and reduce control latency, particularly in CAN bus communications. The work increased mission readiness and enabled more autonomous cycles, supporting efficient reef data collection and robust subsystem integration.
March 2025 monthly performance summary for Byron-MN-FRC/REEFSCAPE2025 highlighting key feature deliveries, major fixes, and impact. Focused on business value, reliability improvements, and technical excellence demonstrated across embedded controls, autonomous sequencing, and sensor integration.
March 2025 monthly performance summary for Byron-MN-FRC/REEFSCAPE2025 highlighting key feature deliveries, major fixes, and impact. Focused on business value, reliability improvements, and technical excellence demonstrated across embedded controls, autonomous sequencing, and sensor integration.

Overview of all repositories you've contributed to across your timeline