Yahboom Transbot ROS AI Robot for Jetson NANO 4GB, Depth Camera, Radar, Robot Arm, and 7-inch Touchscreen (without Jetson NANO SUB board)
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- The whole vehicle is made of green aluminum alloy oxidation material, and supports the installation of robotic arms, 2DOF camera gimbals, 7-inch screens, etc.
- Based on ROS (Robot Operating System) and Python programming.
- Wonderful AI functions: LiDAR obstacle avoidance, fixed-point navigation, skeleton detection, finger following, camera calibration, 3D visual mapping navigation, etc.
- Cross-platform interconnection control.
- We provide 64 video tutorials and detailed documentation.
- [Select Version] Transbot has Jetson Nano version and Raspberry Pi version. The only difference is that the Jetson Nano motherboard equipped with a quad-core cortex-A57 processor, a 128-core Maxwell GPU and 4GB LPDDR memory brings enough Al computing power, providing 472GFLOP computing power, and supports a series of popular Al frameworks and algorithms, such as TensorFlow, Pytorch, caffe/caffe2, Keras, MXNET, etc.
- 【RTAB-VSLAM 3D visual mapping and navigation】Astra Pro 3D Camera III version provides 3D mapping and navigation technology (rtab) that includes pure vision and visual radar fusion. Transbot robots can navigate, avoid obstacles, and globally relocate in 3D maps. Through the corresponding API, they can quickly obtain camera depth maps, color maps, skeletons and other image data. Based on the image-related KCF filtering algorithm, they can select any follow target in the image to open up 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 manipulators, fixed-point navigation, automatic driving, color recognition and tracking, AR tag recognition and reality enhancement, visual image beautification, face detection, laser radar mapping navigation and obstacle avoidance, etc. You will get the open source code provided by Yahboom to realize more possibilities.
- [Cross-platform interconnection control] The robot can be programmed or controlled in 4 ways: ① mobile phone remote control APP with integrated multiple AI functions, ② handle control that can experience FPV real-time visual effects, ③ JupyterLab online programming, ④ professional robot operating system control, multiple control methods to meet different occasions, and deeply experience the fun of controlling the robot.
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