SwerveRobotics/FtcRobotController
Nov 2024 – Nov 2024
1 Month active
Languages Used
Java
Technical Skills
Control SystemsEmbedded SystemsHardware AbstractionJavaRobot ControlRobotics
bharv
PROFILE
Bharv
Bharvi Doshi developed robust arm, slides, dumper, and intake control enhancements for the SwerveRobotics/FtcRobotController repository, focusing on preset-driven automation and TeleOp integration. Leveraging Java and expertise in control systems and embedded systems, Bharvi implemented and stabilized presets for transfer and ground positions, improving reliability and operator efficiency. The work included refining hardware abstraction layers to support runtime visibility of control updates and ensuring maintainable, incremental commits. Bharvi also identified and reverted a drive-tuning regression, restoring proven performance parameters. The depth of the work is reflected in the comprehensive approach to both feature delivery and system stability within robotics control.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
8Total
Bugs
1
Commits
8
Features
1
Lines of code
142
Activity Months1
Your Network
6 people
Work History
November 2024
8 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for SwerveRobotics/FtcRobotController focused on delivering robust arm/slides/dumper/intake control with presets, TeleOp integration, and stability improvements. Highlights include completing and stabilizing presets for transfer and ground positions, enabling slides/dumper control in TeleOp, and improving runtime visibility of control updates. A drive-tuning regression was identified and reverted to restore proven performance. Finalized preset code across all positions, improving reliability, repeatability, and operator efficiency for fielded robots.
8 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for SwerveRobotics/FtcRobotController focused on delivering robust arm/slides/dumper/intake control with presets, TeleOp integration, and stability improvements. Highlights include completing and stabilizing presets for transfer and ground positions, enabling slides/dumper control in TeleOp, and improving runtime visibility of control updates. A drive-tuning regression was identified and reverted to restore proven performance. Finalized preset code across all positions, improving reliability, repeatability, and operator efficiency for fielded robots.
November 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture70.0%
Performance67.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Java
Technical Skills
Control SystemsEmbedded SystemsHardware AbstractionJavaRobot ControlRoboticsTuning
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