R2L Robot Kit – Jetson Nano 4GB | ROS-Enabled Ackermann Steering Robot with AI Model Training & Vision Recognition

Unlock the future of autonomous robotics with the R2L Robot Kit—a powerful educational platform designed for students, developers, and AI enthusiasts. Equipped with the Jetson Nano 4GB, this robot car integrates Ackermann steering, ROS (Robot Operating System), and a full AI deep learning framework for advanced tasks like autopilot, object detection, 3D visual mapping, and voice interaction.

Built with a durable aluminum alloy frame and powered by Ubuntu 18.04 LTS + ROS Melodic, the R2L is capable of processing depth image data, point clouds, LiDAR-based obstacle avoidance, and OpenCV-based image recognition. With over 80 structured learning modules, it’s an ideal choice for serious robotics education, university labs, and developers building real-world autonomous systems.

Key Features:

Jetson Nano 4GB Controller – Supports AI-based image processing, MediaPipe, OpenCV, and model training

ROS & Ubuntu-Based System – Professional-level robotics development environment with ROS Melodic

Ackermann Steering Structure – Realistic vehicle simulation with a high-performance 520 metal motor

AI Model Training Capabilities – Supports object recognition, tag tracking, and automatic driving

3D Vision Mapping & LiDAR Avoidance – Advanced navigation with point cloud processing

Cross-Platform Remote Control – Supports app, gamepad, and FPV live stream control

80+ Educational Video Courses – Learn programming, ROS, autopilot, and deep learning in Python

Modular Design – Expandable for future upgrades and research

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Technical Specifications:

Model: R2L

Processor: Jetson Nano 4GB (B01/SUB)

Motor: 520 Metal Motor (550 rpm ±10 rpm)

Steering Servo: 20kg.cm Metal Digital Servo

Max Speed: 1.8 m/s

OS: Ubuntu 18.04 LTS + ROS Melodic

Programming Language: Python

AI Frameworks: TensorFlow, PyTorch, OpenCV, MediaPipe

Supported Technologies: ROS, NVIDIA, Raspberry Pi, MoveIt, Voice Interaction

Battery: Included

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Educational Applications:

Hands-on learning for autonomous navigation and robotic vision

Python-based AI and ML model training

ROS simulation using MoveIt and Gazebo

Ideal for robotics clubs, high school and university STEM programs

Supports teaching in machine learning, AI, computer vision, and voice control systems

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What’s Included:

Fully assembled R2L Robot Car

Jetson Nano 4GB Controller

High-resolution 2MP vision camera

All required sensors and modules

Rechargeable battery

Access to 80+ online tutorials in English and Chinese

Remote control app and configuration support

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This intelligent programmable robot car is your complete gateway into the world of robotics, automation, and artificial intelligence.

 

 

 

 

     

    

 

 

 

 

 

 

 

 

 

 

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• Supervised Use – Always supervise young children while playing with STEM and Montessori toys to ensure safe and proper use.
• Cleaning & Maintenance – Wipe wooden, plastic, and electronic parts with a soft, damp cloth. Avoid soaking in water or using harsh chemicals.
  
• Storage – Store toys in a cool, dry place away from direct sunlight to maintain durability and color.
  
• Battery-Operated Items – Remove batteries when not in use for long periods to prevent leakage and damage.
  
• Assembly & Parts – Ensure all parts are securely attached before play. Small components should be kept out of reach of children under 3 years old.
  
• Longevity – Encourage gentle handling to extend the life of educational kits and ensure consistent learning value.
  
• Age Appropriateness – Follow the recommended age guidelines for each toy to provide the safest and most effective learning experience.

At  Kidz Garage,  we're committed to getting your orders to you as quickly as possible while ensuring the highest level of quality and care. Below, you'll find important information about our shipping process:

Processing Time:

• Orders are typically processed within 1-2 business days from the date of purchase.
• Please note that processing times may be slightly longer during peak seasons or special promotions.

Shipping Time:

• We aim to deliver your order within 7 - 14 business days from the date of processing.
• Delays in shipping may occur due to unforeseen circumstances, such as weather disruptions, public holidays, or other logistical issues. In such cases, we'll do our best to keep you informed and updated.