Cornell-University-Combat-Robotics/Autonomous-24-25
Nov 2024 – Jan 2025
2 Months active
Languages Used
CSVMarkdownPython
Technical Skills
Algorithm DevelopmentData LoggingDocumentationEmbedded SystemsPythonRobotics
Camille Yap
PROFILE
Camille Yap
Camille Yap contributed to the Cornell-University-Combat-Robotics/Autonomous-24-25 repository by developing and refining autonomous robotics features over a two-month period. She built a Pygame-based simulation environment with real-world scaling, accurate collision detection, and improved state representation, enabling safer and faster hardware validation. Camille enhanced the Ram Ram navigation algorithm by fixing orientation bugs, refactoring angle logic, and streamlining testing workflows. She also implemented a Raspberry Pi camera image capture server to support end-to-end data logging and validation. Her work, primarily in Python, focused on algorithm development, code refactoring, and documentation, resulting in more reliable navigation and maintainable simulation tools.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
13Total
Bugs
1
Commits
13
Features
4
Lines of code
703
Activity Months2
Your Network
13 people
Work History
January 2025
10 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments for the Cornell-University-Combat-Robotics/Autonomous-24-25 project. The sprint delivered higher-fidelity Pygame simulation with real-world scaling, improved state representation, and more accurate rendering of the robot, alongside robust collision handling and performance improvements. The work aligned simulation behavior with real-world parameters to enable faster and safer iteration with real hardware validation.
10 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments for the Cornell-University-Combat-Robotics/Autonomous-24-25 project. The sprint delivered higher-fidelity Pygame simulation with real-world scaling, improved state representation, and more accurate rendering of the robot, alongside robust collision handling and performance improvements. The work aligned simulation behavior with real-world parameters to enable faster and safer iteration with real hardware validation.
January 2025
November 2024
3 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for Cornell-University-Combat-Robotics/Autonomous-24-25. Delivered field-data capture tooling and improved testing workflows for the Ram Ram navigation algorithm, fixed a critical angle-determination bug, and enhanced documentation to accelerate validation and onboarding. These efforts improved navigation reliability, reduced debugging time, and strengthened the team's ability to validate autonomous behavior in real-world scenarios.
November 2024
3 Commits • 2 Features
Nov 1, 2024November 2024 monthly summary for Cornell-University-Combat-Robotics/Autonomous-24-25. Delivered field-data capture tooling and improved testing workflows for the Ram Ram navigation algorithm, fixed a critical angle-determination bug, and enhanced documentation to accelerate validation and onboarding. These efforts improved navigation reliability, reduced debugging time, and strengthened the team's ability to validate autonomous behavior in real-world scenarios.
Activity
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Quality Metrics
Correctness81.6%
Maintainability83.0%
Architecture77.0%
Performance70.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVMarkdownPython
Technical Skills
Algorithm DevelopmentAlgorithm OptimizationCode RefactoringCollision DetectionData LoggingDocumentationEmbedded SystemsGame DevelopmentPhysics SimulationPygamePythonRoboticsRobotics SimulationSimulationTesting
Repositories Contributed To
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