AdvantageKit is a free, open-source logging, telemetry, and replay framework for FRC Java robot code developed by Team 6328. It enables deterministic log replay in simulation, allowing teams to efficiently replay and debug robot behavior from recorded logs.
AdvantageKit is an open-source FRC logging and simulation framework with comprehensive documentation including replay case studies demonstrating best practices for common robot tasks like elevator profiling, vision, and autoscoring.
AdvantageKit is a data logging and replay framework for FRC robots that supports logging of various data types (primitives, arrays, WPILib classes, custom records) with unit-safe logging and visualization via AdvantageScope. It provides efficient robot telemetry capture for debugging, analysis, and
AdvantageKit is a comprehensive logging and replay framework for FRC robot code that records all sensor inputs and outputs, enabling teams to replay matches in simulation and verify code behavior after competition. It's a developer tool used by many teams for debugging and analysis.
AdvantageKit is a Java-based logging and data replay framework for FRC robots that enables deterministic replay, advanced telemetry visualization in AdvantageScope, and rapid iteration on robot code. It provides automatic logging of sensor data, subsystem states, and network diagnostics with support
AdvantageKit is an open-source FRC logging, replay, and simulation framework that enables teams to record and analyze match data with deterministic replay capabilities. Used by competitive teams for advanced debugging and strategy analysis.
AdvantageKit Vision Template is an open-source, reusable starter project for building deterministic, high-performance vision and pose estimation systems in FRC robots. It provides configurable support for Limelight and PhotonVision cameras with integrated logging, filtering, and simulation capabilit
AdvantageKit is a logging and replay framework for FRC robot code that enables teams to record, analyze, and replay robot behavior for debugging and data analysis. It's a reusable library used by many FRC teams to improve development workflows.
QDriverStation is a cross-platform desktop application that replicates the functionality of the official FRC Driver Station, enabling teams to control and test their robots without requiring the official software.
A modern, user-friendly dashboard application for FRC teams to monitor and display robot telemetry, status, and match information during competition and practice.
An extensible, JavaScript-based framework for building custom driving dashboards (pit displays and driver station overlays) for FRC robots. Teams use it to monitor and control their robots during competition.
Road Runner is a community-developed motion planning and path following library for FTC robots. It provides autonomous movement control with support for trajectory generation, spline-based paths, and integration with FTC Dashboard for tuning and visualization.
Choreo is a time-optimal drivetrain trajectory planner for FRC that provides a graphical interface for designing swerve and differential drive paths with real-time playback and physics-based constraints. It includes a robot-side vendor library (ChoreoLib) for autonomous trajectory execution.
RobotPy WPILib is a Python binding for FRC's WPILib, enabling FRC teams to write robot code in Python. This repository is archived and has been moved to robotpy/mostrobotpy.
Yet Another Generic Swerve Library (YAGSL) is a reusable Java library for FRC swerve drive kinematics and control, archived in favor of the newer main YAGSL project.
PhotonVision is an open-source computer vision system for FRC robots that processes camera input to detect AprilTags and other game pieces. This page provides quick installation instructions for supported coprocessors (Raspberry Pi, Orange Pi, Limelight, Rubik Pi).
Documentation page explaining how to use object detection features in PhotonVision, including setup, tuning, custom model management, and integration with FRC robots. Part of the broader PhotonVision documentation for computer vision processing.
Official documentation for PhotonVision, a free, open-source vision processing solution for FRC that enables AprilTag detection, shape detection, and object detection on affordable hardware like Raspberry Pi and Orange Pi. Includes installation guides, pipeline tuning, PhotonLib programming referenc
PhotonVision is the official free, open-source vision processing solution for FRC robots, providing documentation on hardware setup, camera calibration, pipeline configuration, and programming interfaces (PhotonLib) for integrating vision data into robot code.
Official documentation for PhotonVision, a free, open-source vision processing solution for FRC robots. Provides guides for hardware setup, pipeline tuning, PhotonLib integration, and robot code implementation across Java, C++, and Python.