Cornell-University-Combat-Robotics/Autonomous-24-25
Nov 2024 – May 2025
6 Months active
Languages Used
CSVPythonNumpyArduino C++C++
Technical Skills
Algorithm DevelopmentAlgorithm ImplementationCode DocumentationComputer VisionData LoggingDebugging
Ananya-Jajodia
PROFILE
Ananya-jajodia
Over six months, contributed to the Cornell-University-Combat-Robotics/Autonomous-24-25 repository by developing and refining autonomous robotics control systems. Built a modular Ram class architecture with Python and C++, integrating Pygame and Tkinter for simulation and UI, and implemented robust motor control workflows supporting dual-channel operation. Enhanced reliability through comprehensive unit testing, code cleanup, and documentation updates, while improving data logging and telemetry for debugging and analytics. Refactored algorithms for safer hardware-in-the-loop validation and streamlined serial communication, enabling efficient multi-motor coordination. The work emphasized maintainability, clear separation of concerns, and consistent data handling across embedded systems and simulation environments.
Overall Statistics
Feature vs Bugs
86%Features
Repository Contributions
24Total
Bugs
2
Commits
24
Features
12
Lines of code
3,253
Activity Months6
Your Network
13 peopleWork History
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly highlights for the Cornell-University-Combat-Robotics/Autonomous-24-25 repo focused on enabling robust concurrent motor control and streamlined serial communication. Delivered dual-channel capability to update and control two channels simultaneously, reducing transmission overhead and enabling more sophisticated multi-motor choreography for autonomous tasks.
2 Commits • 1 Features
May 1, 2025May 2025 monthly highlights for the Cornell-University-Combat-Robotics/Autonomous-24-25 repo focused on enabling robust concurrent motor control and streamlined serial communication. Delivered dual-channel capability to update and control two channels simultaneously, reducing transmission overhead and enabling more sophisticated multi-motor choreography for autonomous tasks.
May 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025, autonomous robotics project: Cornell-University-Combat-Robotics/Autonomous-24-25. Focused on codebase cleanliness and documentation to enable faster onboarding, safer maintenance, and more reliable experimentation.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025, autonomous robotics project: Cornell-University-Combat-Robotics/Autonomous-24-25. Focused on codebase cleanliness and documentation to enable faster onboarding, safer maintenance, and more reliable experimentation.
February 2025
6 Commits • 3 Features
Feb 1, 2025February 2025 performance summary for Cornell-University-Combat-Robotics/Autonomous-24-25 focusing on delivering core control capabilities, expanding hardware interoperability, and improving data consistency to enable reliable operation and easier analytics.
6 Commits • 3 Features
Feb 1, 2025February 2025 performance summary for Cornell-University-Combat-Robotics/Autonomous-24-25 focusing on delivering core control capabilities, expanding hardware interoperability, and improving data consistency to enable reliable operation and easier analytics.
February 2025
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 highlights for Cornell-University-Combat-Robotics/Autonomous-24-25 focused on reliability, safety, and maintainability of RamRam navigation. Key features and robustness improvements were delivered, alongside targeted bug fixes that strengthen autonomous decision-making and reduce regression risk. The work enhances planning accuracy, safer maneuvers, and faster iteration through improved tests and clearer diagnostics.
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 highlights for Cornell-University-Combat-Robotics/Autonomous-24-25 focused on reliability, safety, and maintainability of RamRam navigation. Key features and robustness improvements were delivered, alongside targeted bug fixes that strengthen autonomous decision-making and reduce regression risk. The work enhances planning accuracy, safer maneuvers, and faster iteration through improved tests and clearer diagnostics.
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 — Summary focused on key accomplishments, major fixes, impact, and skills demonstrated for Cornell-University-Combat-Robotics/Autonomous-24-25. Implemented a Ram integration overhaul with a Pygame-based testing harness, refactored Ram to output motor commands as a dictionary, and removed outdated transmission code to improve maintainability and testability. These changes enable safer hardware-in-the-loop validation, faster iteration, and a clearer separation of concerns.
3 Commits • 2 Features
Dec 1, 2024December 2024 — Summary focused on key accomplishments, major fixes, impact, and skills demonstrated for Cornell-University-Combat-Robotics/Autonomous-24-25. Implemented a Ram integration overhaul with a Pygame-based testing harness, refactored Ram to output motor commands as a dictionary, and removed outdated transmission code to improve maintainability and testability. These changes enable safer hardware-in-the-loop validation, faster iteration, and a clearer separation of concerns.
December 2024
November 2024
9 Commits • 4 Features
Nov 1, 2024November 2024: Delivered foundational Ram class architecture with test-mode CSV logging and a Pygame-based simulation GUI; introduced a Tkinter-based point-selection UI for Ram navigation; resolved critical orientation issues and improved shutdown handling; enhanced testing workflows and data logging; and applied code quality improvements to increase maintainability and clarity. Business value includes improved simulation fidelity for feature validation, reliable telemetry for debugging, faster development iteration, and readiness for battle-mode validation. Technologies demonstrated include Python, Pygame, Tkinter, CSV logging, and type hints.
November 2024
9 Commits • 4 Features
Nov 1, 2024November 2024: Delivered foundational Ram class architecture with test-mode CSV logging and a Pygame-based simulation GUI; introduced a Tkinter-based point-selection UI for Ram navigation; resolved critical orientation issues and improved shutdown handling; enhanced testing workflows and data logging; and applied code quality improvements to increase maintainability and clarity. Business value includes improved simulation fidelity for feature validation, reliable telemetry for debugging, faster development iteration, and readiness for battle-mode validation. Technologies demonstrated include Python, Pygame, Tkinter, CSV logging, and type hints.
Activity
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Quality Metrics
Correctness82.6%
Maintainability83.4%
Architecture80.0%
Performance71.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Arduino C++C++CSVNumpyPython
Technical Skills
Algorithm DevelopmentAlgorithm ImplementationAlgorithm TestingArduinoC++Code CleanupCode DocumentationCode RefactoringComputer VisionData LoggingDebuggingDocumentation UpdateEmbedded SystemsGUI DevelopmentGame Development
Repositories Contributed To
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