
Kjaget developed advanced robotics software for the FRC900/900RobotCode repository, focusing on perception, control, and deployment automation over a ten-month period. He engineered GPU-accelerated AprilTag detection and robust teleoperation features using C++ and Python, integrating ROS for real-time data processing and visualization. His work included build system upgrades with CMake and deployment script refinements to support Jetson and RoboRIO platforms, improving reliability and maintainability. Kjaget also implemented system identification tools and motion profiling for precise robot control, addressing both hardware integration and software configuration. The depth of his contributions reflects strong expertise in embedded systems, computer vision, and robotics programming.

January 2026 highlights for FRC900/900RobotCode: Teleop Orientation Driver improvements with motion profiling and tuning, plus fixed rotation transition issues, delivering more accurate and responsive teleop control and configurable tuning parameters.
January 2026 highlights for FRC900/900RobotCode: Teleop Orientation Driver improvements with motion profiling and tuning, plus fixed rotation transition issues, delivering more accurate and responsive teleop control and configurable tuning parameters.
Month: 2025-08 – Key features delivered in repository FRC900/900RobotCode include a Clangd Diagnostics Filtering Enhancement and a SysId Action Server for System Identification. The work improved diagnostics accuracy, data collection capabilities, and maintainability.
Month: 2025-08 – Key features delivered in repository FRC900/900RobotCode include a Clangd Diagnostics Filtering Enhancement and a SysId Action Server for System Identification. The work improved diagnostics accuracy, data collection capabilities, and maintainability.
In July 2025, delivered key enhancements to the deployment pipeline for FRC900/900RobotCode by upgrading the allwpilib dependency to the latest release and refining deployment scripts for more precise file transfers. This work improves deployment reliability, accelerates future updates, and ensures the project remains current with library fixes and features.
In July 2025, delivered key enhancements to the deployment pipeline for FRC900/900RobotCode by upgrading the allwpilib dependency to the latest release and refining deployment scripts for more precise file transfers. This work improves deployment reliability, accelerates future updates, and ensures the project remains current with library fixes and features.
April 2025 — Key contributions focused on improving robot control fidelity, reducing latency across the stack, stabilizing simulator integration, and strengthening the separation between autonomy and teleoperation to enable more predictable operations. The work enhances operator responsiveness, reliability of placement tasks, and end-to-end control performance in real missions.
April 2025 — Key contributions focused on improving robot control fidelity, reducing latency across the stack, stabilizing simulator integration, and strengthening the separation between autonomy and teleoperation to enable more predictable operations. The work enhances operator responsiveness, reliability of placement tasks, and end-to-end control performance in real missions.
March 2025 performance summary for FRC900/900RobotCode focused on strengthening control robustness, trajectory fidelity, and development efficiency. Delivered key features, reliability fixes, and tooling updates that improve tuning, field reliability, and build/deploy cycles. Demonstrated proficiency with dynamic configuration, CTRE hardware interfaces, ROS-based teleop, and calibration tooling, delivering measurable business value through more repeatable piece handling, faster iteration, and smoother field operations.
March 2025 performance summary for FRC900/900RobotCode focused on strengthening control robustness, trajectory fidelity, and development efficiency. Delivered key features, reliability fixes, and tooling updates that improve tuning, field reliability, and build/deploy cycles. Demonstrated proficiency with dynamic configuration, CTRE hardware interfaces, ROS-based teleop, and calibration tooling, delivering measurable business value through more repeatable piece handling, faster iteration, and smoother field operations.
February 2025 monthly performance summary for FRC900/900RobotCode. Delivered end-to-end enhancements across perception, Jetson hardware integration, and fleet reliability, with a focus on business value and maintainability. Key work includes GPU-accelerated Apriltag processing on Xavier with YAML-configurable detection and threshold control, Jetson camera system improvements (ArduCAM MIPI installation step and dual Xavier OV2311 fixes), deployment robustness across the Jetson fleet (cross-build enforcement, time synchronization, and per-device startup clock tuning), a new Roller Controller for the 2025 season (voltage output mode, continuous operation, and ROS service integration), and a bug fix for swerve cancoder joint naming that resolves wheel-offset dumps. These efforts improve perception reliability, deployment consistency, and control capabilities while showcasing skills in GPU computing, embedded Linux, ROS, and hardware-software integration.
February 2025 monthly performance summary for FRC900/900RobotCode. Delivered end-to-end enhancements across perception, Jetson hardware integration, and fleet reliability, with a focus on business value and maintainability. Key work includes GPU-accelerated Apriltag processing on Xavier with YAML-configurable detection and threshold control, Jetson camera system improvements (ArduCAM MIPI installation step and dual Xavier OV2311 fixes), deployment robustness across the Jetson fleet (cross-build enforcement, time synchronization, and per-device startup clock tuning), a new Roller Controller for the 2025 season (voltage output mode, continuous operation, and ROS service integration), and a bug fix for swerve cancoder joint naming that resolves wheel-offset dumps. These efforts improve perception reliability, deployment consistency, and control capabilities while showcasing skills in GPU computing, embedded Linux, ROS, and hardware-software integration.
January 2025 monthly summary for FRC900/900RobotCode. Focused on delivering a robust data prep pipeline for 2025 YOLO training, aligning hardware configurations with licensing, and stabilizing the codebase and build environment to decrease risk and increase maintainability. Key outcomes included a data prep workflow for the 2025 object detection dataset, 2024 button box compatibility with legal AprilTags, a license-compliant swerve feedback update, and comprehensive codebase/environment stabilization through WPIlib upgrades and install-path refinements.
January 2025 monthly summary for FRC900/900RobotCode. Focused on delivering a robust data prep pipeline for 2025 YOLO training, aligning hardware configurations with licensing, and stabilizing the codebase and build environment to decrease risk and increase maintainability. Key outcomes included a data prep workflow for the 2025 object detection dataset, 2024 button box compatibility with legal AprilTags, a license-compliant swerve feedback update, and comprehensive codebase/environment stabilization through WPIlib upgrades and install-path refinements.
December 2024 monthly summary for FRC900/900RobotCode focusing on key features delivered, critical bug fixes, and overall impact/value. Highlights include GPU-accelerated perception improvements, reliable current-limiting safety for TalonFX Pro, and comprehensive deployment/toolchain upgrades that streamline Jetson deployments and developer workflows.
December 2024 monthly summary for FRC900/900RobotCode focusing on key features delivered, critical bug fixes, and overall impact/value. Highlights include GPU-accelerated perception improvements, reliable current-limiting safety for TalonFX Pro, and comprehensive deployment/toolchain upgrades that streamline Jetson deployments and developer workflows.
Delivered a set of impactful enhancements for FRC900/900RobotCode in November 2024, focusing on perception, teleoperation, dependencies, autonomous reliability, and platform tooling. Resulted in a more robust, scalable robot software stack with improved field reliability and faster feature delivery.
Delivered a set of impactful enhancements for FRC900/900RobotCode in November 2024, focusing on perception, teleoperation, dependencies, autonomous reliability, and platform tooling. Resulted in a more robust, scalable robot software stack with improved field reliability and faster feature delivery.
Month: 2024-10 | Focus: platform upgrades, data tooling, and build stability for RoboRIO/Jetson. Delivered feature work and fixes across WPILib integration, GPU-accelerated perception, ROS data processing, and Jetson build resilience. Representative commits include upgrades and scripts to 2025, CUDA/AprilTag cleanups, and HAL stub support. Key outcomes: - Upgraded to WPILib 2025 beta and updated deployment/build scripts to the 2025 directory structure for RoboRIO and Jetson targets; enhanced CTRE integration and cross-compile support. - Improved GPU-based AprilTag processing: streamlined CUDA compile commands and launch configurations; verified correct GPU AprilTag version in ov2311 launch; resolved static analysis issues after command updates. - Introduced ROS Bag Processing and Visualization Tool: Python-based solution to extract robot positions and AprilTag data from ROS bags, export CSV, and generate heatmaps and distance histograms for tag tracking. - Increased Jetson build stability by adding HAL stubs for unsupported platforms, with error logging and graceful handling to prevent build failures. Representative commits used: - 90e8d7e0c613edb7b5cb1d5a386e8d728e28ee63 — Beta 2025 (#2) - 69488523853594e19ac5fe1eeaf3fba5322cda36 — Update install scripts to 2025 - e8f0fde459fe40235bd4ae12a249bdb4240c5cbe — Gpu apriltag cleanup (#213) - a240d60f39c404844da1e5e88978a9b0d1f56f12 — Localized script (#3) - 3caff2c7621a901ed57779b77257829f20d6be6c — Fix Jetson builds
Month: 2024-10 | Focus: platform upgrades, data tooling, and build stability for RoboRIO/Jetson. Delivered feature work and fixes across WPILib integration, GPU-accelerated perception, ROS data processing, and Jetson build resilience. Representative commits include upgrades and scripts to 2025, CUDA/AprilTag cleanups, and HAL stub support. Key outcomes: - Upgraded to WPILib 2025 beta and updated deployment/build scripts to the 2025 directory structure for RoboRIO and Jetson targets; enhanced CTRE integration and cross-compile support. - Improved GPU-based AprilTag processing: streamlined CUDA compile commands and launch configurations; verified correct GPU AprilTag version in ov2311 launch; resolved static analysis issues after command updates. - Introduced ROS Bag Processing and Visualization Tool: Python-based solution to extract robot positions and AprilTag data from ROS bags, export CSV, and generate heatmaps and distance histograms for tag tracking. - Increased Jetson build stability by adding HAL stubs for unsupported platforms, with error logging and graceful handling to prevent build failures. Representative commits used: - 90e8d7e0c613edb7b5cb1d5a386e8d728e28ee63 — Beta 2025 (#2) - 69488523853594e19ac5fe1eeaf3fba5322cda36 — Update install scripts to 2025 - e8f0fde459fe40235bd4ae12a249bdb4240c5cbe — Gpu apriltag cleanup (#213) - a240d60f39c404844da1e5e88978a9b0d1f56f12 — Localized script (#3) - 3caff2c7621a901ed57779b77257829f20d6be6c — Fix Jetson builds
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