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 developed and enhanced data visualization and sensor monitoring features for the CMU-cabot/cabot robotics repository, focusing on reliable speed and touch sensor data processing. He implemented a subprocess-based workflow in Python and ROS to improve speed data retrieval, integrating new sources such as social distance and obstacle avoidance speeds for more comprehensive robot behavior analysis. Miyazaki also expanded the system’s observability by adding real-time touch sensor visualization using Tkinter, including capacitive and ToF data, and resolved a data logging bug to ensure complete sensor records. His work improved data integrity, responsiveness, and monitoring depth across robotic navigation scenarios.
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 people
Work 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
Repositories Contributed To
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