CMU-cabot/cabot-drivers
Dec 2024 – Feb 2025
2 Months active
Languages Used
C++pythonyaml
Technical Skills
CAN BusCAN busConfiguration ManagementDriver DevelopmentEmbedded SystemsHardware Control
kozenikanta
PROFILE
Kozenikanta
K. Kozeni enhanced the CMU-cabot/cabot-drivers repository by developing adaptive thermal management and dynamic fan speed control for embedded robotics systems. Leveraging C++ and ROS2, Kozeni replaced static fan control logic with a temperature-linear mapping, introducing a calibrated linear function to ensure precise cooling and hardware protection. The work included refactoring parameter handling to use floating-point calculations, implementing configurable thresholds, and adding new ROS subscribers and publishers for real-time temperature and fan control signals. Kozeni also improved CAN interface stability and data conversion, demonstrating depth in control systems, hardware integration, and configuration management over a focused two-month period.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
10Total
Bugs
1
Commits
10
Features
3
Lines of code
366
Activity Months2
Your Network
11 people
Work History
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for CMU-cabot/cabot-drivers: Implemented dynamic fan speed control using a temperature-linear mapping, replacing a static multiplier with a calibrated linear function and establishing a safe baseline. Refactored calculation to use floating-point values and recalculated slope/intercept to operate within defined temperature and fan-speed ranges. This improves cooling precision, protects hardware, and lays groundwork for tunable performance. Two commits completed on the feature: 4045c2c95a61e678962c9e445afc789432a3eb16 and cd5c23dda49dbc3dc6c1f6e7201532dd77df1e5a.
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for CMU-cabot/cabot-drivers: Implemented dynamic fan speed control using a temperature-linear mapping, replacing a static multiplier with a calibrated linear function and establishing a safe baseline. Refactored calculation to use floating-point values and recalculated slope/intercept to operate within defined temperature and fan-speed ranges. This improves cooling precision, protects hardware, and lays groundwork for tunable performance. Two commits completed on the feature: 4045c2c95a61e678962c9e445afc789432a3eb16 and cd5c23dda49dbc3dc6c1f6e7201532dd77df1e5a.
February 2025
December 2024
8 Commits • 2 Features
Dec 1, 2024December 2024 performance summary for CMU-cabot/cabot-drivers: Delivered three key enhancements aimed at reliability, flexibility, and data quality. Thermal Management and Power Controller Enhancements introduced adaptive fan control based on temperature readings, a new temperature subscriber and a fan control signal publisher, and a refactored power controller with configurable thresholds to maintain optimal operating temperatures. This work, supported by commits 58d77c1b5c0185290841627485dee96fc6b1b888, 1605a646380d6ffdbc72baf82b02c441e79d6db7, 9d561bc3b9e61eeddd839188079fa1543c2f78fb, df6b1ea7fa1b08fec6202e4a32fb83dd001a089f, 32a2e8b4a798d403322f9cc95b17047a7a5c54cb, and cad9dd690886f03310ce2bcb23c389d3059189e1, improves cooling efficiency and reduces thermal throttling risk in deployed systems.
December 2024
8 Commits • 2 Features
Dec 1, 2024December 2024 performance summary for CMU-cabot/cabot-drivers: Delivered three key enhancements aimed at reliability, flexibility, and data quality. Thermal Management and Power Controller Enhancements introduced adaptive fan control based on temperature readings, a new temperature subscriber and a fan control signal publisher, and a refactored power controller with configurable thresholds to maintain optimal operating temperatures. This work, supported by commits 58d77c1b5c0185290841627485dee96fc6b1b888, 1605a646380d6ffdbc72baf82b02c441e79d6db7, 9d561bc3b9e61eeddd839188079fa1543c2f78fb, df6b1ea7fa1b08fec6202e4a32fb83dd001a089f, 32a2e8b4a798d403322f9cc95b17047a7a5c54cb, and cad9dd690886f03310ce2bcb23c389d3059189e1, improves cooling efficiency and reduces thermal throttling risk in deployed systems.
Activity
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Quality Metrics
Correctness82.0%
Maintainability86.0%
Architecture78.0%
Performance72.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++pythonyaml
Technical Skills
CAN BusCAN busConfiguration ManagementControl SystemsDriver DevelopmentEmbedded SystemsHardware ControlParameter ManagementROSROS2RoboticsThermal Management
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