CMU-cabot/cabot
Nov 2024 – Feb 2025
2 Months active
Languages Used
PythonTkinter
Technical Skills
Data VisualizationPython ScriptingROSRoboticsBug FixData Processing
fukimiyazaki
PROFILE
Fukimiyazaki
Fumihiro Miyazaki contributed to the CMU-cabot/cabot repository by developing robust data visualization and sensor integration features for robotics applications. He enhanced the robot’s speed visualization by integrating new data sources, such as social distance and obstacle avoidance speeds, and refactored data retrieval to run in a Python subprocess, improving reliability and responsiveness. Miyazaki also expanded touch sensor monitoring by adding capacitive and ToF sensor data visualization, introducing a dedicated touch graph, and improving data filtering. His work addressed data integrity issues in the logging pipeline, demonstrating strong skills in Python scripting, ROS, and GUI development with Tkinter for real-time analytics.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
211
Activity Months2
Your Network
5 peopleWork History
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 highlights for CMU-cabot/cabot: Delivered two critical updates focused on data integrity and observability, delivering clear business value and expanding monitoring capabilities. Key features delivered: - Touch Sensor Data Visualization and Filtering Enhancement: Added new touch topics and a dedicated 'touch' graph; expanded data filtering and plotting to include capacitive and ToF touch sensor data, improving monitoring and display of touch information. Major bugs fixed: - Data Logging Completeness Fix: Resolved a bug where the second-to-last data point was not appended to the processed data; ensures both the last timestamp and the second-to-last data point are included in process_st and process_data lists, eliminating incomplete data logging and reducing downstream data gaps. Overall impact and accomplishments: - Improved data integrity and reliability of sensor logging, enabling more accurate analytics, reporting, and alerting. - Enhanced observability with richer visualization, supporting faster issue diagnosis and proactive monitoring. Technologies/skills demonstrated: - Debugging and data pipeline correctness, real-time data visualization, topic-based graphing, and integration of capacitive/ToF touch sensor data for expanded monitoring.
2 Commits • 1 Features
Feb 1, 2025February 2025 highlights for CMU-cabot/cabot: Delivered two critical updates focused on data integrity and observability, delivering clear business value and expanding monitoring capabilities. Key features delivered: - Touch Sensor Data Visualization and Filtering Enhancement: Added new touch topics and a dedicated 'touch' graph; expanded data filtering and plotting to include capacitive and ToF touch sensor data, improving monitoring and display of touch information. Major bugs fixed: - Data Logging Completeness Fix: Resolved a bug where the second-to-last data point was not appended to the processed data; ensures both the last timestamp and the second-to-last data point are included in process_st and process_data lists, eliminating incomplete data logging and reducing downstream data gaps. Overall impact and accomplishments: - Improved data integrity and reliability of sensor logging, enabling more accurate analytics, reporting, and alerting. - Enhanced observability with richer visualization, supporting faster issue diagnosis and proactive monitoring. Technologies/skills demonstrated: - Debugging and data pipeline correctness, real-time data visualization, topic-based graphing, and integration of capacitive/ToF touch sensor data for expanded monitoring.
February 2025
November 2024
1 Commits • 1 Features
Nov 1, 2024Monthly performance summary for 2024-11 focused on CMU-cabot/cabot. Highlights include the delivery of an enhanced speed visualization feature with broader data sources and increased reliability, underpinned by a subprocess-based data retrieval workflow. This work strengthens the robot's speed behavior insights across diverse scenarios, supporting faster, data-driven navigation improvements and clearer traceability to commits.
November 2024
1 Commits • 1 Features
Nov 1, 2024Monthly performance summary for 2024-11 focused on CMU-cabot/cabot. Highlights include the delivery of an enhanced speed visualization feature with broader data sources and increased reliability, underpinned by a subprocess-based data retrieval workflow. This work strengthens the robot's speed behavior insights across diverse scenarios, supporting faster, data-driven navigation improvements and clearer traceability to commits.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture73.4%
Performance66.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonTkinter
Technical Skills
Bug FixData ProcessingData VisualizationGUI DevelopmentPython ScriptingROSRoboticsSensor Integration
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