LiU-SeeGoals/controller
Oct 2024 – Dec 2024
2 Months active
Languages Used
Jupyter NotebookPythonGo
Technical Skills
Data ScienceData VisualizationDeep LearningMachine LearningPyTorchPython
Arturas Aleksandraus
PROFILE
Arturas Aleksandraus
Arturas worked on the LiU-SeeGoals/controller repository, focusing on deep learning model improvements and architectural refactoring. He delivered a performance-oriented refactor of the SeeGoalsDNN, introducing interactive evaluation and enhancing trajectory control through an exponential distance-based force model and distance-aware loss, using Python and PyTorch. To improve data consistency and maintainability, he unified game state, status, and field geometry into a single GameInfo data model, replacing the legacy state package and updating documentation for clarity. His work emphasized code organization, robust model validation, and streamlined data management, resulting in more reliable real-time control and easier onboarding for future development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
1,470
Activity Months2
Your Network
12 people
Work History
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024: Delivered a focused refactor in LiU-SeeGoals/controller by introducing a unified GameInfo data model and info package, consolidating game state, status, and field geometry into a single source of truth. This replaces the legacy state package and aligns data access with a coherent API, enabling simpler data management and stronger consistency across components. Updated developer notes and README to reflect the structural changes, improving onboarding and API guidance for future work.
1 Commits • 1 Features
Dec 1, 2024December 2024: Delivered a focused refactor in LiU-SeeGoals/controller by introducing a unified GameInfo data model and info package, consolidating game state, status, and field geometry into a single source of truth. This replaces the legacy state package and aligns data access with a coherent API, enabling simpler data management and stronger consistency across components. Updated developer notes and README to reflect the structural changes, improving onboarding and API guidance for future work.
December 2024
October 2024
2 Commits • 1 Features
Oct 1, 2024October 2024 monthly summary for LiU-SeeGoals/controller: Delivered performance-focused refactor of SeeGoalsDNN with interactive evaluation, training I/O improvements, and trajectory control enhancements using an exponential distance-based force model and a distance-aware loss. Implemented robustness improvements by refining force calculation logic in apply_force_based_on_distance, addressing stability concerns and improving trajectory predictability. Overall, the work accelerates experimentation cycles, improves model validation throughput, and strengthens real-time control reliability in production settings.
October 2024
2 Commits • 1 Features
Oct 1, 2024October 2024 monthly summary for LiU-SeeGoals/controller: Delivered performance-focused refactor of SeeGoalsDNN with interactive evaluation, training I/O improvements, and trajectory control enhancements using an exponential distance-based force model and a distance-aware loss. Implemented robustness improvements by refining force calculation logic in apply_force_based_on_distance, addressing stability concerns and improving trajectory predictability. Overall, the work accelerates experimentation cycles, improves model validation throughput, and strengthens real-time control reliability in production settings.
Activity
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Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture83.4%
Performance76.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
GoJupyter NotebookPython
Technical Skills
Code OrganizationData ScienceData VisualizationDeep LearningDocumentation UpdateMachine LearningPackage ManagementPyTorchPythonRefactoring
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