Difference between revisions of "FTC 2024 Season"
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= From 2023 Java Training = | = From 2023 Java Training = | ||
− | * [[FTC Power Up a Motor | + | == Prepared Labs == |
− | * [[FTC Move a Distance | + | ** [https://spectrum.ieee.org/the-top-programming-languages-2023 2023 Top Programming Languages] |
+ | * [[FTC Power Up a Motor 20230911]] | ||
+ | * [[FTC Move a Distance 20230919]] | ||
+ | * [[FTC Read Colors 20231017]] | ||
+ | ** [[FTC CanDo with a Color Sensor 20231108]] -- Optional -- | ||
+ | * [[FTC Set Up the Mecanum Training Platform 20231025]] | ||
+ | * [[FTC Make Coding Easier with Methods 20231025]] | ||
+ | * [[FTC Bring Up HuskyLens 20231127]] | ||
+ | |||
+ | == Lab Explorations == | ||
+ | * [[FTC Using Android Debugging Bridge to Locate Bugs 20231108]] | ||
* [[FTC Compute Move Distance 20221014]] | * [[FTC Compute Move Distance 20221014]] | ||
* [[FTC Compute a 90 Degree Turn 20221104]] | * [[FTC Compute a 90 Degree Turn 20221104]] | ||
Line 8: | Line 18: | ||
* [[FTC Mecanum Drivetrain Kit - Assembly and Setup 20221129]] | * [[FTC Mecanum Drivetrain Kit - Assembly and Setup 20221129]] | ||
* [[FTC Working Through Cell Phone Robot Controller and Driver Station Issues 20230320]] | * [[FTC Working Through Cell Phone Robot Controller and Driver Station Issues 20230320]] | ||
− | |||
* [[FTC Color Sensor 20230424]] Small edits to the 20200311 version for Benson | * [[FTC Color Sensor 20230424]] Small edits to the 20200311 version for Benson | ||
+ | * [[FTC IMU 20240204]] A start | ||
+ | |||
+ | = Maintenance = | ||
+ | |||
+ | * [http://10.0.0.9/wiki/index.php/FTC_TrainingBot_Upgrade_20230901 Upgrade Software] | ||
= TensorFlow Video Training = | = TensorFlow Video Training = | ||
* [https://tryengineering.org/tryengineering-community-resources/using-tensorflow-to-detect-game-pieces-in-first-tech-challenge-robot-competitions-an-exploration-in-machine-learning/ Using TensorFlow to Detect Game Pieces in First Tech Challenge] | * [https://tryengineering.org/tryengineering-community-resources/using-tensorflow-to-detect-game-pieces-in-first-tech-challenge-robot-competitions-an-exploration-in-machine-learning/ Using TensorFlow to Detect Game Pieces in First Tech Challenge] | ||
+ | * [https://github.com/edcepp/FTCEppTensorCode/tree/master/FTCEppTensorCode Github for above] | ||
+ | * [https://ftc-docs.firstinspires.org/en/latest/ftc_ml/ FTC Machine Learning] | ||
+ | |||
+ | * [https://ftc-docs.firstinspires.org/en/latest/programming_resources/vision/tensorflow_cs_2023/tensorflow-cs-2023.html Tensorflow CS 2023] | ||
+ | |||
+ | |||
+ | * [https://ftc-docs.firstinspires.org/en/latest/programming_resources/vision/java_tfod_opmode/java-tfod-opmode.html Java TFOD Opmode Java] | ||
+ | /** | ||
+ | * Initialize the Vuforia localization engine. | ||
+ | */ | ||
+ | private void initVuforia() { | ||
+ | /* | ||
+ | * Configure Vuforia by creating a Parameter object, and passing it to the Vuforia engine. | ||
+ | */ | ||
+ | VuforiaLocalizer.Parameters parameters = new VuforiaLocalizer.Parameters(); | ||
+ | |||
+ | parameters.vuforiaLicenseKey = VUFORIA_KEY; | ||
+ | parameters.cameraDirection = CameraDirection.BACK; | ||
+ | |||
+ | // Instantiate the Vuforia engine | ||
+ | vuforia = ClassFactory.getInstance().createVuforia(parameters); | ||
+ | |||
+ | // Loading trackables is not necessary for the TensorFlow Object Detection engine. | ||
+ | } | ||
+ | |||
+ | = Apriltag Notes = | ||
+ | |||
+ | * [[Just a Start ]] | ||
+ | |||
+ | = Control Hub specs = | ||
+ | |||
+ | Notice the Multi-Media Processor at the bottom middle of the block diagram below: | ||
+ | |||
+ | * Graphic Engine | ||
+ | * JPEG Decoder | ||
+ | * IEP | ||
+ | * 1080P Video encoder | ||
+ | * 4K Video decoder | ||
+ | |||
+ | * [https://docs.revrobotics.com/duo-control/control-system-overview/control-hub-basics Control Hub Basics] | ||
+ | |||
+ | General Specifications | ||
+ | |||
+ | * Processor | ||
+ | ** RK3328 Quad-core ARM® Cortex-A53 | ||
+ | ** Texas Instruments ARM® Cortex®-M4 | ||
+ | * Memory 1GB LPDDR3 | ||
+ | * Storage 8GB eMMC 4.51 | ||
+ | * Wireless | ||
+ | ** 802.11 ac/b/g/n/w Wi-Fi; Dual Band 2.4 & 5 GHz | ||
+ | ** Bluetooth 4.1 | ||
+ | * Graphics‡ | ||
+ | ** GPU - ARM® Mali 450MP4 | ||
+ | ** HDMI 2.0 support for 4k @ 60Hz | ||
+ | |||
+ | * [https://opensource.rock-chips.com/wiki_RK3328 WIKI RK3328 | ||
= References = | = References = | ||
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* [https://first-tech-challenge.github.io/SkyStone/index.html FTC API reference] | * [https://first-tech-challenge.github.io/SkyStone/index.html FTC API reference] | ||
* [https://github.com/FIRST-Tech-Challenge/FtcRobotController FTC SDK version 7.1] | * [https://github.com/FIRST-Tech-Challenge/FtcRobotController FTC SDK version 7.1] | ||
− | |||
= Maintenance = | = Maintenance = | ||
* [[FTC TrainingBot Upgrade 20230901]] | * [[FTC TrainingBot Upgrade 20230901]] | ||
+ | |||
+ | = Github fix references = | ||
+ | |||
+ | * [https://www.youtube.com/watch?v=IEWxGbj0SII How To Set Up A Github Repository For FTC] | ||
+ | * [https://www.youtube.com/watch?v=D6aiIB2tMBA How to Use GitHub for Version Control in FTC] | ||
+ | * [https://www.youtube.com/watch?v=KJhD7tVm-yE 9-28-2021 FTC Tuesday with Kevin - Git and GitHub] |
Latest revision as of 12:16, 4 February 2024
Contents
From 2023 Java Training
Prepared Labs
- FTC Power Up a Motor 20230911
- FTC Move a Distance 20230919
- FTC Read Colors 20231017
- FTC CanDo with a Color Sensor 20231108 -- Optional --
- FTC Set Up the Mecanum Training Platform 20231025
- FTC Make Coding Easier with Methods 20231025
- FTC Bring Up HuskyLens 20231127
Lab Explorations
- FTC Using Android Debugging Bridge to Locate Bugs 20231108
- FTC Compute Move Distance 20221014
- FTC Compute a 90 Degree Turn 20221104
- FTC The Challenge - Start Simple and Build 20221108
- FTC Mecanum Drivetrain Kit - Assembly and Setup 20221129
- FTC Working Through Cell Phone Robot Controller and Driver Station Issues 20230320
- FTC Color Sensor 20230424 Small edits to the 20200311 version for Benson
- FTC IMU 20240204 A start
Maintenance
TensorFlow Video Training
- Using TensorFlow to Detect Game Pieces in First Tech Challenge
- Github for above
- FTC Machine Learning
/** * Initialize the Vuforia localization engine. */ private void initVuforia() { /* * Configure Vuforia by creating a Parameter object, and passing it to the Vuforia engine. */ VuforiaLocalizer.Parameters parameters = new VuforiaLocalizer.Parameters(); parameters.vuforiaLicenseKey = VUFORIA_KEY; parameters.cameraDirection = CameraDirection.BACK; // Instantiate the Vuforia engine vuforia = ClassFactory.getInstance().createVuforia(parameters); // Loading trackables is not necessary for the TensorFlow Object Detection engine. }
Apriltag Notes
Control Hub specs
Notice the Multi-Media Processor at the bottom middle of the block diagram below:
- Graphic Engine
- JPEG Decoder
- IEP
- 1080P Video encoder
- 4K Video decoder
General Specifications
- Processor
- RK3328 Quad-core ARM® Cortex-A53
- Texas Instruments ARM® Cortex®-M4
- Memory 1GB LPDDR3
- Storage 8GB eMMC 4.51
- Wireless
- 802.11 ac/b/g/n/w Wi-Fi; Dual Band 2.4 & 5 GHz
- Bluetooth 4.1
- Graphics‡
- GPU - ARM® Mali 450MP4
- HDMI 2.0 support for 4k @ 60Hz
- [https://opensource.rock-chips.com/wiki_RK3328 WIKI RK3328
References
- OnBot Java Guide OnBot Java Guide
- FTC Programming Resources
- Java Video Tutorials
- FTC API reference
- FTC SDK version 7.1