MissouriMRR/SUAS-2025
Nov 2024 – Jun 2025
7 Months active
Languages Used
PythonJSONShell
Technical Skills
Asynchronous ProgrammingDrone ControlEmbedded SystemsMAVLinkTestingCode Refactoring
Ooglely
PROFILE
Ooglely
Alen Navdić developed core autonomous drone features and robust vision pipelines for the MissouriMRR/SUAS-2025 repository, focusing on reliable payload deployment, image capture, and real-time object detection. He engineered asynchronous Python systems using asyncio and PyTorch, integrating GPU-accelerated inference and ONNX Runtime for YOLOv9-based perception. His work included servo control for airdrop mechanisms, camera gimbal workflows, and state machine-driven flight-perception synchronization, all supported by automated testing and detailed logging. By refactoring legacy components, improving error handling, and hardening safety controls, Alen delivered maintainable, data-driven solutions that increased mission reliability, reduced operational risk, and enabled scalable, autonomous field deployments.
Overall Statistics
Feature vs Bugs
79%Features
Repository Contributions
61Total
Bugs
4
Commits
61
Features
15
Lines of code
9,412
Activity Months7
Your Network
7 people
Work History
June 2025
18 Commits • 5 Features
Jun 1, 2025June 2025 highlights: Delivered a robust set of features and reliability improvements to increase mission success, safety, and operator confidence for MissouriMRR/SUAS-2025. Key outcomes include data-driven default handling for airdrop locations, improved vision accuracy with detailed logging and overlays, synchronized flight-perception sequencing, and hardened safety controls. These changes reduce drop failures, shorten decision cycles, and enable safer, more maintainable operations across the platform. Technologies leveraged include Python/CV, OpenCV/YOLO, JSON data handling, and real-time state machines with enhanced telemetry.
18 Commits • 5 Features
Jun 1, 2025June 2025 highlights: Delivered a robust set of features and reliability improvements to increase mission success, safety, and operator confidence for MissouriMRR/SUAS-2025. Key outcomes include data-driven default handling for airdrop locations, improved vision accuracy with detailed logging and overlays, synchronized flight-perception sequencing, and hardened safety controls. These changes reduce drop failures, shorten decision cycles, and enable safer, more maintainable operations across the platform. Technologies leveraged include Python/CV, OpenCV/YOLO, JSON data handling, and real-time state machines with enhanced telemetry.
June 2025
May 2025
4 Commits • 1 Features
May 1, 2025May 2025 performance summary for MissouriMRR/SUAS-2025: Delivered core feature enhancements and fixed critical hardware/software issues, driving reliability, data quality, and safety for autonomous operations. Focused on robust image processing, precise hardware control, and end-to-end data integrity to enable more accurate mapping and reduced manual intervention. The work directly supports better decision-making, faster field deployment, and lower maintenance costs.
May 2025
4 Commits • 1 Features
May 1, 2025May 2025 performance summary for MissouriMRR/SUAS-2025: Delivered core feature enhancements and fixed critical hardware/software issues, driving reliability, data quality, and safety for autonomous operations. Focused on robust image processing, precise hardware control, and end-to-end data integrity to enable more accurate mapping and reduced manual intervention. The work directly supports better decision-making, faster field deployment, and lower maintenance costs.
April 2025
16 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for MissouriMRR/SUAS-2025. This period focused on expanding autonomous actuation, strengthening perception and data capture pipelines, and reducing maintenance overhead by removing obsolete components. The work delivered aligns with increased mission reliability, safer autonomous flight, and higher-quality data for analytics and decision-making. Business value was realized through more capable drones, robust software with fewer regressions, and clearer ownership boundaries for future enhancements.
16 Commits • 4 Features
Apr 1, 2025April 2025 monthly summary for MissouriMRR/SUAS-2025. This period focused on expanding autonomous actuation, strengthening perception and data capture pipelines, and reducing maintenance overhead by removing obsolete components. The work delivered aligns with increased mission reliability, safer autonomous flight, and higher-quality data for analytics and decision-making. Business value was realized through more capable drones, robust software with fewer regressions, and clearer ownership boundaries for future enhancements.
April 2025
March 2025
13 Commits • 2 Features
Mar 1, 2025March 2025: Delivered a robust YOLOv9 vision pipeline and significant robustness improvements to the SUAS-2025 vision system. Key features delivered include a new YOLOv9 model inference class with ONNX Runtime integration, asynchronous image processing, enhanced bounding box handling, and comprehensive tests; centralization of model inference within the pipeline and updates to bbox/utils; plus major robustness/configuration improvements including cancellable async queues and asyncio.Event-based status signaling. Major fixes addressed reliable queue cancellation, write access to camera_config, pre-commit hygiene, and configuration adjustments for HereLink connectivity. Overall impact: improved real-time detection reliability, reduced race conditions, expanded test coverage, and smoother deployment readiness. Technologies/skills demonstrated: Python asyncio, ONNX Runtime integration, custom asyncio.Queue subclassing, asyncio.Event usage, unit testing, and end-to-end pipeline integration.
March 2025
13 Commits • 2 Features
Mar 1, 2025March 2025: Delivered a robust YOLOv9 vision pipeline and significant robustness improvements to the SUAS-2025 vision system. Key features delivered include a new YOLOv9 model inference class with ONNX Runtime integration, asynchronous image processing, enhanced bounding box handling, and comprehensive tests; centralization of model inference within the pipeline and updates to bbox/utils; plus major robustness/configuration improvements including cancellable async queues and asyncio.Event-based status signaling. Major fixes addressed reliable queue cancellation, write access to camera_config, pre-commit hygiene, and configuration adjustments for HereLink connectivity. Overall impact: improved real-time detection reliability, reduced race conditions, expanded test coverage, and smoother deployment readiness. Technologies/skills demonstrated: Python asyncio, ONNX Runtime integration, custom asyncio.Queue subclassing, asyncio.Event usage, unit testing, and end-to-end pipeline integration.
February 2025
7 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for MissouriMRR/SUAS-2025: Delivered end-to-end improvements to the gimbal-based image capture workflow, modernized dependencies for asynchronous IO and GPU-accelerated inference, and hardened the camera module for robustness. These updates increased capture reliability and throughput, improved deployment readiness, and set the stage for scalable, CUDA-enabled compute.
7 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for MissouriMRR/SUAS-2025: Delivered end-to-end improvements to the gimbal-based image capture workflow, modernized dependencies for asynchronous IO and GPU-accelerated inference, and hardened the camera module for robustness. These updates increased capture reliability and throughput, improved deployment readiness, and set the stage for scalable, CUDA-enabled compute.
February 2025
January 2025
1 Commits
Jan 1, 2025January 2025: Stabilized the deskew workflow in MissouriMRR/SUAS-2025. No new features released this month; major focus on fixing the deskew integration bug to improve reliability, maintainability, and production risk. The fix removes a stray binary, renames a unit test for better organization, and resolves the deskew integration issue, enabling more robust data processing and smoother deployments.
January 2025
1 Commits
Jan 1, 2025January 2025: Stabilized the deskew workflow in MissouriMRR/SUAS-2025. No new features released this month; major focus on fixing the deskew integration bug to improve reliability, maintainability, and production risk. The fix removes a stray binary, renames a unit test for better organization, and resolves the deskew integration issue, enabling more robust data processing and smoother deployments.
November 2024
2 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for MissouriMRR/SUAS-2025 focusing on delivering core payload deployment capability and validating flight maneuvers through automated testing. Implemented an asynchronous PWM-based servo control (set_servo) for the airdrop system and added takeoff_land.py tests to validate takeoff, hover, and landing sequences. These changes establish a foundation for reliable autonomous payload deployment in field missions and improve safety through automated test coverage. No major bugs reported this month; work emphasized feature delivery and traceability.
2 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for MissouriMRR/SUAS-2025 focusing on delivering core payload deployment capability and validating flight maneuvers through automated testing. Implemented an asynchronous PWM-based servo control (set_servo) for the airdrop system and added takeoff_land.py tests to validate takeoff, hover, and landing sequences. These changes establish a foundation for reliable autonomous payload deployment in field missions and improve safety through automated test coverage. No major bugs reported this month; work emphasized feature delivery and traceability.
November 2024
Activity
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Quality Metrics
Correctness85.4%
Maintainability86.2%
Architecture80.0%
Performance75.6%
AI Usage20.4%
Skills & Technologies
Programming Languages
JSONPythonShell
Technical Skills
API IntegrationAsynchronous ProgrammingAsyncioBackend DevelopmentCUDACamera ControlCamera Gimbal ControlCloud ComputingCode CleanupCode MaintenanceCode RefactoringComputer VisionConcurrencyConfiguration ManagementControl Systems
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