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
Worked on the CMU-cabot/cabot-drivers repository to enhance embedded hardware control and thermal management for robotics systems. Developed adaptive fan speed control using C++ and Python, implementing a temperature-linear mapping to dynamically adjust cooling based on real-time sensor data. Refactored the power controller for configurable thresholds and improved parameter handling with floating-point precision. Added dual-driver support for Hesai Lidar, enabling runtime selection and flexible ROS2 topic remapping. Addressed CAN interface stability by refining filter configurations and correcting data conversion logic. The work focused on reliability, maintainability, and precise hardware control, leveraging skills in ROS2, embedded systems, and configuration management.
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 peopleWork 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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