Cornell-University-Combat-Robotics/Autonomous-24-25
Jan 2025 – Jan 2025
1 Month active
Languages Used
CSVPython
Technical Skills
Algorithm DevelopmentAlgorithm TestingCSV ManagementControl SystemsData EngineeringData Logging
ethandecamp
PROFILE
Ethandecamp
Ethan DeCamp contributed to the Cornell-University-Combat-Robotics/Autonomous-24-25 repository by delivering core platform enhancements focused on control reliability, data handling, and testing infrastructure. He expanded the RamRamTest framework with comprehensive CSV-based test data, improving simulation validation for robot positions, velocities, and sensor data. Using Python and numpy, Ethan overhauled the robot movement and control algorithms to consolidate turn and speed predictions, extending return values for easier debugging and more robust control. He also integrated a pre-trained greyscale model to enable image processing and improved repository hygiene by refining CSV data management, resulting in cleaner version control and streamlined development workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
10Total
Bugs
0
Commits
10
Features
4
Lines of code
12,901
Activity Months1
Your Network
13 people
Work History
January 2025
10 Commits • 4 Features
Jan 1, 2025January 2025 monthly performance for Cornell-University-Combat-Robotics/Autonomous-24-25: Delivered core platform enhancements with a focus on testing, control reliability, model integration, and repository hygiene. Expanded RamRamTest data coverage and testing infrastructure; overhauled robot movement and data handling for more robust control; integrated a pre-trained greyscale model; and improved data hygiene by excluding generated CSV data from version control. These changes reduce risk, enable faster debugging, and broaden sensing/decision capabilities in simulation and field tests.
10 Commits • 4 Features
Jan 1, 2025January 2025 monthly performance for Cornell-University-Combat-Robotics/Autonomous-24-25: Delivered core platform enhancements with a focus on testing, control reliability, model integration, and repository hygiene. Expanded RamRamTest data coverage and testing infrastructure; overhauled robot movement and data handling for more robust control; integrated a pre-trained greyscale model; and improved data hygiene by excluding generated CSV data from version control. These changes reduce risk, enable faster debugging, and broaden sensing/decision capabilities in simulation and field tests.
January 2025
Activity
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Quality Metrics
Correctness94.0%
Maintainability94.0%
Architecture90.0%
Performance94.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVPython
Technical Skills
Algorithm DevelopmentAlgorithm TestingCSV ManagementControl SystemsData EngineeringData LoggingPython ProgrammingRoboticsSimulation DataTesting
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