Yahboom Transbot ROS AI robot for Jetson NANO 4GB with depth camera, radar, robotic arm and 7" touch screen (without Jetson NANO SUB board)

The whole vehicle is made of green aluminum alloy oxide material and supports the installation of mechanical arms, 2DOF camera gimbal, 7-inch screen, etc.

Based on ROS (Robot Operating System) and Python programming.

Exciting AI features: LiDAR obstacle avoidance, fixed-point navigation, bone detection, finger tracking, camera calibration, 3D visual mapping navigation, etc.

Cross platform interconnection control.

We provide 64 video tutorials and detailed documentation.

[Version Selection] There are Jetson Nano and Raspberry Pi versions of Transbot, with the only difference being that the Jetson Nano motherboard, equipped with a quad core Cortex-A57 processor, 128 core Maxwell GPU, and 4GB LPDDR memory, brings sufficient Al computing power, providing 472GFLOP computing power and supporting a range of popular Al frameworks and algorithms such as TensorFlow, Pytorch, cafe/affe2, Keras, MXNET, etc.

RTAB-VSLAM 3D Visual Mapping and Navigation: The Astra Pro 3D Camera III version provides 3D mapping and navigation technology (rtab) that combines pure vision and visual radar. The Transbot robot can navigate, avoid obstacles, and globally reposition in 3D maps, quickly obtaining camera depth maps, color maps, skeletons, and other image data through corresponding APIs. Based on the KCF filtering algorithm related to images, it can select any target to follow in the image and open the 3D world

[AI Function Combination] The robot integrates rich AI functions, such as intelligent inspection, radar guarding and tracking, three degree of freedom flexible grasping of the robotic arm, fixed-point navigation, autonomous driving, color recognition and tracking, AR tag recognition and reality enhancement, visual image beautification, face detection, LiDAR mapping navigation and obstacle avoidance, etc. You will receive open source code provided by Yahboom to achieve more possibilities.

[Cross platform interconnection control] Robots can be programmed or controlled in four ways: ① a mobile remote control APP integrating multiple AI functions, ② a controller that can experience real-time visual effects of FPV, ③ Jupyter Lab provides online programming and professional robot operating system control, with multiple control methods to meet different situations, allowing for a deep experience of the fun of operating robots.