MissouriMRDT/Autonomy_Software
Apr 2025 – May 2025
2 Months active
Languages Used
CC++CowfilePerl
Technical Skills
C++Computer VisionEmbedded SystemsRoboticsSimulationState Machines
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PROFILE
Frawgii
Samantha Hajdukiewicz developed autonomy and simulation features for the MissouriMRDT/Autonomy_Software repository, focusing on robust marker-based navigation and object detection for robotics applications. She enhanced the marker detection pipeline by integrating Torch tag support and refactoring tag identification, using C++ and computer vision techniques to improve navigation reliability. Samantha also refined the SIMZEDCam simulation’s depth decoding, addressing encoded value extraction and correction for greater fidelity. In addition, she expanded object detection with YOLO-based models and improved state-machine logic for object interaction. Her work demonstrated depth in embedded systems, machine learning model integration, and data validation, supporting reliable mission execution.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
14Total
Bugs
0
Commits
14
Features
4
Lines of code
1,264
Activity Months2
Your Network
12 people
Work History
May 2025
11 Commits • 2 Features
May 1, 2025For May 2025, delivered significant autonomy enhancements and data-validation fixes that improve reliability, safety, and developer readiness in MissouriMRDT/Autonomy_Software.
11 Commits • 2 Features
May 1, 2025For May 2025, delivered significant autonomy enhancements and data-validation fixes that improve reliability, safety, and developer readiness in MissouriMRDT/Autonomy_Software.
May 2025
April 2025
3 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary highlighting autonomy software delivery and simulation improvements for MissouriMRDT. Focused on delivering robust marker-based navigation and improving depth perception fidelity in simulation to support reliable mission execution and planning.
April 2025
3 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary highlighting autonomy software delivery and simulation improvements for MissouriMRDT. Focused on delivering robust marker-based navigation and improving depth perception fidelity in simulation to support reliable mission execution and planning.
Activity
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Quality Metrics
Correctness84.2%
Maintainability85.6%
Architecture84.2%
Performance74.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
CC++CowfilePerl
Technical Skills
ASCII ArtC++Computer VisionConfiguration ManagementCowsayData File ManagementEmbedded SystemsMachine LearningMachine Learning Model IntegrationModel IntegrationObject DetectionRoboticsSimulationState MachineState Machines
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