
Worked on the MissouriMRR/SUAS-2025 repository, delivering features and fixes to advance drone mission software over a three-month period. Developed robust airdrop cylinder selection and fallback logic, improved state machine handling, and introduced servo control placeholders to support future hardware integration. Enhanced configuration management by hardcoding search boundaries and enabling dynamic camera parameter loading, reducing external dependencies and improving reliability across simulation and real-world environments. Addressed geospatial data precision and corrected gimbal attitude calculations to improve flight control accuracy. Utilized Python, JSON handling, and state machines throughout, demonstrating depth in backend development, computer vision, and UAV mission planning workflows.
Summary for 2025-04: Delivered critical enhancements and bug fixes in MissouriMRR/SUAS-2025 to advance long-range testing and field readiness. Key features include 3-Mile SUAS Mission Waypoints with distance data and unit standardization to meters. Major fixes addressed golf data boundaries precision and gimbal attitude calculation, improving geographic data integrity and drone control accuracy. These changes reduce testing risk, improve data consistency, and demonstrate strong proficiency in geospatial data handling, flight-planning data pipelines, and real-time attitude math.
Summary for 2025-04: Delivered critical enhancements and bug fixes in MissouriMRR/SUAS-2025 to advance long-range testing and field readiness. Key features include 3-Mile SUAS Mission Waypoints with distance data and unit standardization to meters. Major fixes addressed golf data boundaries precision and gimbal attitude calculation, improving geographic data integrity and drone control accuracy. These changes reduce testing risk, improve data consistency, and demonstrate strong proficiency in geospatial data handling, flight-planning data pipelines, and real-time attitude math.
March 2025: Delivered configurable, cross-environment improvements to the MissouriMRR/SUAS-2025 project, enhancing reliability, configurability, and mission readiness with minimal external dependencies. Implemented data-loading simplifications, robust airdrop state handling, and environment-aware camera parameters to support both AirSim and real-world deployments.
March 2025: Delivered configurable, cross-environment improvements to the MissouriMRR/SUAS-2025 project, enhancing reliability, configurability, and mission readiness with minimal external dependencies. Implemented data-loading simplifications, robust airdrop state handling, and environment-aware camera parameters to support both AirSim and real-world deployments.
February 2025 monthly summary for MissouriMRR/SUAS-2025: Delivered key enhancement to Airdrop cylinder selection, improving robustness and system stability during deployment sequences. Implemented iterative cylinder selection within the Airdrop state and updated fallback behavior to return to Mapping state if no loaded cylinders are available. Prepared placeholders for servo control logic and aligned simulation config for odlc search path. No critical bugs logged this month; primary focus on feature delivery and groundwork for future servo integration.
February 2025 monthly summary for MissouriMRR/SUAS-2025: Delivered key enhancement to Airdrop cylinder selection, improving robustness and system stability during deployment sequences. Implemented iterative cylinder selection within the Airdrop state and updated fallback behavior to return to Mapping state if no loaded cylinders are available. Prepared placeholders for servo control logic and aligned simulation config for odlc search path. No critical bugs logged this month; primary focus on feature delivery and groundwork for future servo integration.

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