Discover the cutting-edge ROS AI Robotics Platform, designed for both educational and advanced research applications. This versatile smart vehicle chassis offers both Mecanum wheel omnidirectional drive and Ackermann steering options, powered by NVIDIA Jetson Nano for robust AI computing.
Equipped with a comprehensive suite of optional sensors including LiDAR, depth cameras, IMU, and ultrasonic modules, this platform enables advanced functionalities such as SLAM mapping, obstacle avoidance, and visual navigation. Its open-source control and simulation environment, including Gazebo and RViz, empowers users to rapidly prototype and develop complex AI and navigation algorithms.
The modular design allows for easy expansion with additional cameras, sensors, mechanical arms, and LiDAR modules, making it a future-proof investment for robotics enthusiasts and professionals alike. Constructed with a precision CNC machined aluminum alloy frame, it guarantees durability and stable performance in various environments.
Key Features
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ROS-Ready Smart AI Platform
Fully compatible with ROS Noetic/Melodic, pre-configured for mapping, navigation, object recognition, and autonomous driving research—ideal for education, R&D, and robotics competition. -
AI Computing with Jetson Nano
Powered by NVIDIA GPU accelerated computing for real-time deep learning inference, vision tracking, and intelligent path planning. -
Flexible Chassis Options
Supports both Mecanum wheel omnidirectional drive for agile movement and Ackermann steering for realistic autonomous vehicle simulation. -
Advanced Perception System
Integrates LiDAR, depth cameras, IMU, and ultrasonic sensors, enabling SLAM mapping, obstacle avoidance, and visual navigation. -
Open-Source Control and Simulation
Supports Gazebo simulation, RViz visualization, and custom ROS nodes, empowering users to prototype navigation and AI control algorithms quickly. -
Modular Design & Easy Expansion
Modular electronic system allows quick upgrades — add LiDAR, depth sensing, robot arms, or autonomous driving algorithms as needed. -
Educational and Research Applications
Excellent for STEM education, university robotics labs, and autonomous driving projects, bridging theoretical AI with real-world robotics practice. -
Industrial-Grade Build Quality
Precision aluminum-alloy chassis ensures durability, lightweight mobility, and stable sensor installation for outdoor or lab use.
Technical Specifications
| Feature | Detail |
|---|---|
| Product Name | ROS AI Robotics Platform – Mecanum / Ackermann Smart Vehicle Chassis |
| Model | Jetson Nano ROS Educational AI Robot Car |
| Processor | NVIDIA Jetson Nano Developer Kit (optional support for Xavier NX / Orin Nano variants) |
| Control System | ROS (Robot Operating System) – Pre-installed Ubuntu + ROS Noetic / Melodic |
| Drive Type |
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| Motor Type | DC encoder motors with closed-loop PID control (precise odometry feedback) |
| Power Supply | 12–24 V DC battery pack (typ. 8,400 – 12,000 mAh, Li-ion recommended) |
| Control Interface | USB / UART / CAN / Wi-Fi / Bluetooth (Remote and APP compatible) |
| Sensors (Optional) |
|
| Software Environment |
|
| Chassis Material | CNC machined aluminum alloy frame |
| Dimensions | Customizable (typ. 35 × 25 × 12 cm depending on version) |
| Connectivity | Ethernet, Wi-Fi 802.11 b/g/n, Bluetooth 5.0 |
| Expandability | Support for additional cameras, sensors, mechanical arms, and LiDAR modules |
| Programming Languages | Python, C++, C (ROS node level development) |
| Operating System | Linux (ROS Ubuntu distribution) |
| Certification | CE, RoHS (compliant for educational export) |