Yahboom AI Robotic Kit with Jetson Nano Radar ROS2 Smart Tank Car Robot Arm Kit for Adults Autonomous Navigation, 7-inch Touch Screen & Depth Camera Optional for Teens Adults

Experience the cutting-edge Yahboom AI Robotic Kit, designed for ROS enthusiasts and robot developers. Featuring the powerful Jetson Nano, advanced radar sensing, and optional 7-inch touch screen with depth camera, this kit empowers adults and teens to develop autonomous navigation, robot arm control, and more. Dive into AI robotics with a versatile smart tank car platform that supports numerous programming and control methods to enhance learning and creativity.

Transbot is a crawler off-road robot built on the Robot Operating System (ROS), specially crafted for ROS enthusiasts and robot players. Its rugged, all-terrain design allows it to navigate complex environments while serving as an educational platform for ROS programming and robotics experimentation.

Equipped with high-performance hardware such as Jetson Nano or Raspberry Pi, lidar, HD and depth cameras, this robot integrates powerful sensors and computing capabilities. This hardware setup enables advanced functions including mapping navigation, obstacle avoidance, and AI vision.

The robot supports applications like real-time motion control, remote communication, and autonomous mapping navigation. It also enables following and avoidance behaviors, autopilot modes, and simulation for robotic arms using MoveIt in ROS2.

Targets closer to the radar are detected and locked, enabling the robot car to keep its front always facing the target. This Lidar guard ensures responsive environmental awareness and precise target tracking for smarter navigation.

Using OpenCV libraries, the robot's video feed is processed for beautification effects. This function enhances real-time visual data, allowing clearer and more aesthetically pleasing imagery during operation.

The robot independently explores and constructs maps using the Rapidly-Exploring Random Tree (RRT) algorithm. It saves maps and autonomously returns to its starting point with efficient and smart navigation.

Supporting custom color selection, the robot autonomously recognizes colors and drives forward following the selected color. This autopilot feature integrates AI vision for interactive color tracking and control.

The robot can select a target color through its screen interface and track the target dynamically. This feature allows interactive control and real-time color-based following.

The rear light bar produces various magical and colorful lighting effects, enhancing visibility and aesthetics during robot operation and patrolling.

Define patrol routes using the mobile app and watch the robot follow them autonomously. This intelligent patrol feature brings programmable pathing for exploration and monitoring.

This robot scans its environment with lidar to detect and select the closest target to follow. Lidar tracking ensures smooth and accurate follow-the-target movements indoors or outdoors.

Multiple control methods are integrated, including mobile remote app, real-time FPV video handle control, JupyterLab online programming, and professional ROS robot operating system control. This provides versatile ways to program and interact with the robot for different skill levels.

Detailed hardware modules include customizable expanding boards and sensor arrays built to work seamlessly with Jetson Nano and Raspberry Pi versions. The extensive hardware expands robot functions and learning possibilities.

The Robot Operating System 2 (ROS2) serves as the backbone for software development, enabling advanced robotic control, mapping, and autonomous behaviors with strong community support and open-source flexibility.

Jetson Nano integration provides high computational power ideal for AI vision and processing sensor data in real-time, making the robot capable of autonomous decision-making and smooth control.

The smart tank car chassis offers robust movement, traction and flexible control. It acts as a stable platform for AI and robotics projects, practical for learning autonomous navigation and control.