March 2025 monthly summary for RobotCasserole2025: The team delivered a set of high-impact features and stability improvements across autonomous, control, and vision stacks, with clear operator feedback and measurable business value. Key features delivered included Endgame LED improvements for clearer status indicators; Elevator control tuning and gains for smoother and safer operation; L4 autonomous improvements with refined scoring/trajectory and an added eject capability; Path alignment enhancements adding default extra alignment time to improve handling; Apriltag vision enhancements and filtering to improve auto-path alignment and outlier rejection; Kraken AutoDrive tuning and faster update rates to improve responsiveness across the stack; PV picture capture enhancements with higher current limit and gating to enable higher-power capture; Elevator and drivetrain performance optimization for faster operation; Autosteer and AutoDrive behavior improvements with safety toggles and driver control integration. Major bugs fixed included pose estimation stability fixes to prevent resets and maintain vision operation; logging cleanup to temporarily disable file logging to reduce long log loops; L1 coral eject reliability tweaks to reduce mis-ejections; tag management cleanup deprecating unreliable Barge Tag IDs. Overall impact: enhanced reliability and predictability of autonomous scoring, reduced operational friction due to cleaner diagnostics and log management, and tangible performance gains in elevator, drivetrain, and perception stacks. This supports faster iteration cycles and improved on-field performance. Technologies/skills demonstrated: real-time control tuning and gains management, autonomous trajectory planning and scoring logic, vision system robustness including pose estimation and apriltag filtering, autosteer/autodrive safety controls, performance optimization for Kraken-based update rates, and maintainable code through targeted refactors and modular gains updates.
March 2025 monthly summary for RobotCasserole2025: The team delivered a set of high-impact features and stability improvements across autonomous, control, and vision stacks, with clear operator feedback and measurable business value. Key features delivered included Endgame LED improvements for clearer status indicators; Elevator control tuning and gains for smoother and safer operation; L4 autonomous improvements with refined scoring/trajectory and an added eject capability; Path alignment enhancements adding default extra alignment time to improve handling; Apriltag vision enhancements and filtering to improve auto-path alignment and outlier rejection; Kraken AutoDrive tuning and faster update rates to improve responsiveness across the stack; PV picture capture enhancements with higher current limit and gating to enable higher-power capture; Elevator and drivetrain performance optimization for faster operation; Autosteer and AutoDrive behavior improvements with safety toggles and driver control integration. Major bugs fixed included pose estimation stability fixes to prevent resets and maintain vision operation; logging cleanup to temporarily disable file logging to reduce long log loops; L1 coral eject reliability tweaks to reduce mis-ejections; tag management cleanup deprecating unreliable Barge Tag IDs. Overall impact: enhanced reliability and predictability of autonomous scoring, reduced operational friction due to cleaner diagnostics and log management, and tangible performance gains in elevator, drivetrain, and perception stacks. This supports faster iteration cycles and improved on-field performance. Technologies/skills demonstrated: real-time control tuning and gains management, autonomous trajectory planning and scoring logic, vision system robustness including pose estimation and apriltag filtering, autosteer/autodrive safety controls, performance optimization for Kraken-based update rates, and maintainable code through targeted refactors and modular gains updates.
February 2025 monthly summary for RobotCasserole2025: Focused on autonomous navigation reliability, safety controls, and developer ergonomics. Delivered feature completions and stability improvements across navigation, perception, and control loops, resulting in safer autonomous operation, improved path planning accuracy, and clearer system state visibility for debugging and performance reviews.
February 2025 monthly summary for RobotCasserole2025: Focused on autonomous navigation reliability, safety controls, and developer ergonomics. Delivered feature completions and stability improvements across navigation, perception, and control loops, resulting in safer autonomous operation, improved path planning accuracy, and clearer system state visibility for debugging and performance reviews.
January 2025: Key features delivered and major bug fixes across the RobotCasserole2025 repo, with a focus on reliability, maintainability, and faster feedback loops for autonomous drive functionality.
January 2025: Key features delivered and major bug fixes across the RobotCasserole2025 repo, with a focus on reliability, maintainability, and faster feedback loops for autonomous drive functionality.
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