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Built-in OpenCV Image Processing Algorithm 520 Encoder Motors Python Programming Based ROS Jetson Nano 4GB B01 Transbot SE
Product Description
Products Description
TRANSBOT-SE is a tracked robot car developed based on the robot operating system. The entire body is made of aluminum alloy. Equipped with a 3-DOF robotic arm and a 2-DOF camera PTZ, 520 encoder motors, and a large-capacity battery. It is compatible with Jetson Nano B01 and Raspberry Pi 4B. Built-in OpenCV image processing algorithm, MediaPipe machine learning, AI deep learning framework, and movelt simulation platform, Transbot SE can realize functions such as robot motion control, gesture recognition, object recognition, tracking, automatic driving, and robotic arm simulation control.
Key Features
Crawler structure, the whole vehicle is made of all-aluminum alloy, and comes with HQ crawler and high-power motor.
2DOF 2MP camera, combined with APP or remote control handle, it can realize real-time transmission of video.
3DOF robotic arm, which can not only realize the gripping and handling function of the robotic arm, but also realize MoveIt simulation.
Based on the ROS operating system, adopt Python programing, support Jetson Nano B01 and Raspberry Pi 4B.
Through Opencv image processing and MediaPipe framework, it realizes a series of functions related to AI visual recognition.
Product Details
Frequently Asked Questions
Q1 What main control boards are compatible with TRANSBOT-SE?
TRANSBOT-SE is designed to be fully compatible with both Jetson Nano B01 and Raspberry Pi 4B mainboards.
Q2 What operating system and programming language does it run on?
The robot operates on the Robot Operating System (ROS) and utilizes Python programming for software development and algorithm execution.
Q3 What are the capabilities of the robotic arm and camera PTZ?
It features a 3-DOF robotic arm capable of gripping, item handling, and MoveIt simulation, alongside a 2-DOF 2MP camera PTZ for real-time video transmission and machine vision tracking.
Q4 What AI and computer vision functions can TRANSBOT-SE achieve?
By integrating OpenCV image processing and the MediaPipe machine learning framework, it supports gesture recognition, object recognition, target tracking, automatic driving, and visual inspection.
Q5 What materials and driving system are used in the chassis?
The entire body is engineered from all-aluminum alloy, paired with high-quality crawler tracks, 520 encoder motors, and a large-capacity battery for robust off-road mobility and reliable motion control.
Q6 How can TRANSBOT-SE be controlled remotely?
The robot can be operated seamlessly through a dedicated mobile application (APP) or via a wireless remote control handle, with real-time video streaming support.
