AI ROS2 4-Wheel Autonomous Robot Car with LiDAR SLAM & Jetson Nano GPU Computing | Smart AI Vision STEM Platform for Education & Research | Supports OpenCV & TensorFlow for Object Detection & Path Planning | Wi-Fi Control System

AI ROS2 autonomous car platform combines Jetson Nano GPU computing and ESP32 motor control to deliver real-time AI vision and SLAM navigation. AI robot integrates LiDAR, IMU, camera vision and encoder feedback to teach students autonomous navigation, mapping and AI decision logic inside ROS 2 architecture. The system uses DDS-based communication for node-to-node data exchange, allowing learners to experience distributed robotic software design in a hands-on way.

AI vision robot captures HD video and analyzes frames using OpenCV and TensorFlow to recognize objects, colors and movement in real time. LiDAR and IMU fusion enables precise SLAM mapping and localization. Students learn how autonomous robots perceive environments and plan optimal routes while avoiding obstacles. Wi-Fi and Bluetooth modules allow remote control, telemetry and AIoT data logging for IoT-connected robotics projects.

AI computing on Jetson Nano executes deep-learning models locally without cloud dependence. The platform supports Python and C++ coding for ROS 2 nodes, topics and services, allowing students to build complete AI pipelines. Gazebo and RViz software provide simulation and visualization for path planning and sensor feedback testing. The open-source ROS 2 framework enables integration of custom algorithms and hardware expansion for advanced projects.

4WD structure ensures excellent mobility and stability. Each wheel is driven independently by high-torque DC motors with PID closed-loop control and encoder feedback for precise speed and direction adjustment. The robot can climb slopes and operate on indoor and outdoor surfaces smoothly. Students learn real-world mechanics such as differential drive, wheel slip correction and IMU balancing.

AI education robot bridges the gap between mechanics, electronics and programming through an open-source learning ecosystem. It is widely used in universities and research labs for AI vision training, navigation algorithm research and autonomous vehicle development. The AI STEM platform empowers learners to develop ROS 2-based applications for intelligent mobility, SLAM optimization and AI-driven navigation control.

1️⃣ AI Vision and LiDAR SLAM Integration
AI vision robot combines camera and LiDAR data to map and recognize its environment in real time. Students gain practical experience in sensor fusion and path optimization.

2️⃣ ROS 2 Programming and DDS Communication
ROS 2 teaches modern distributed robot software architecture using nodes, topics and services. Students learn real-time data synchronization and multi-sensor coordination.

3️⃣ Jetson Nano GPU AI Computing
The AI engine runs TensorFlow and PyTorch models locally for object tracking, classification and navigation decisions.

4️⃣ 4WD Structure with PID Motion Control
Four-wheel differential drive offers precise movement and stability on various terrains with encoder feedback.

5️⃣ STEM Open-Source Learning and Research Platform
Open architecture invites students to add sensors and write custom AI navigation algorithms for research and education.

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