MRT AI Robot Set 451

AI, Machine Learning & Scratch Coding with Robot Control (Ages 10–18)

STEM AI Robot Control 451 introduces students to artificial intelligence and machine learning through hands-on robot control. Students train their own AI model using Google Teachable Machine, import the model into MRT AI Studio, and use camera-based recognition to control a physical robot in real time.

Using the MRT Node Board with BLE wireless connectivity, students program in Scratch-based blocks and connect AI recognition to physical robot outputs. This course is the official kit for AI robotics pathways in the UNSW Robotics & Coding Challenge and is suitable for coding competitions, project-based STEM learning, and advanced classroom challenges.

Who Is This For?

• Upper primary to high school students (Ages 10–18)
• Students interested in AI, machine learning, and robotics
• Competition participants — UNSW Robotics & Coding Challenge (Path C official kit)
• Schools and centres adding AI/ML to their STEM curriculum
• Students with Scratch coding experience ready for AI extensions

Learning Focus

• Basic machine learning concepts — training, labels, confidence scores
• AI model training using Google Teachable Machine
• Scratch-style AI coding in MRT AI Studio
• Camera-based image and gesture recognition
• Connecting AI input to physical robot output via BLE wireless
• Motion or gesture-controlled robot behaviour
• Project-based AI robotics design and experimentation

How It Works

Step 1: Train Your AI Model
Students use Google Teachable Machine to create custom image recognition models — for example, training the model to recognise “Go”, “Stop”, “Left”, and “Right” gestures using their webcam.

Step 2: Code in MRT AI Studio
The trained model is loaded into MRT AI Studio (Scratch-based IDE). Students write programs that read camera recognition results and send commands to the robot via BLE wireless connection.

Step 3: Control the Robot
The MRT Node Board receives commands wirelessly and controls DC motors, servos, and sensors on the physical robot. Students see their AI model controlling a real robot in real time.

Example Projects

• A robot car that moves forward when it recognises a “go” gesture
• A robot that turns left or right based on hand movement
• A motion-controlled racing car
• A rescue robot controlled by trained AI commands
• A challenge robot using student-created AI labels — forward, left, right, stop

Main Features

• MRT AI Studio — Scratch-based coding environment with AI/ML extensions
• MRT Node Board with BLE wireless connectivity (included)
• Google Teachable Machine model integration
• Camera-based AI recognition
• 5+ sample robot-building projects with manuals
• Free eLearning access — 2 months full access + core lessons permanently unlocked
• Official kit for UNSW Robotics & Coding Challenge (Path C)

Robot Kit Includes

• MRT Node Board (BLE wireless mainboard)
• IR sensors
• Touch sensors
• DC motors
• Servo motors
• Battery cases
• USB cable
• Wheels and gears
• Durable ABS plastic blocks in various sizes and shapes
• Total: 377 parts

Software Requirements

• MRT AI Studio (free download from eLearning platform — Windows / macOS)
• Google Teachable Machine (free, web-based — teachablemachine.withgoogle.com)
• Webcam or laptop camera for AI model training
• Chrome or Edge browser

Product Information Notice
Product specifications, component counts, colours, packaging, and included accessories may vary slightly due to product updates, supplier changes, packaging revisions, or availability. MRT Robotics makes every reasonable effort to keep product information accurate and up to date. If you require the latest confirmed details before purchase, please contact us directly.