Yahboom DOFBOT AI Large Model Vision Robotic Arm (6-DOF) ROS2 Python for Jetson NANO 4GB B01/SUB

Overview

Yahboom DOFBOT is an AI large model vision robotic arm designed for ROS2 development and Python3 programming on Jetson NANO 4GB (B01/SUB). It integrates a USB HD camera with a 6-DOF desktop robotic arm and supports AI vision applications such as color tracking, gesture recognition, face tracking, visual interaction, and sorting demos. The structure uses green oxidized aluminum alloy, including a 2mm-thick aluminum alloy bracket, and a suction-cup chassis for stable placement.

Key Features

• 6-DOF arm + camera integration: “Robotic Arm–Camera Integration” with “6 Degrees of Freedom”.
• ROS2 development: ROS2 Humble is specified (Docker + ROS2 Humble). Supports RViz robot simulation and MoveIt motion planning.
• AI vision & interaction stack: OpenCV, MediaPipe, YOLOv11, inverse kinematics algorithm.
• Multimodal AI large model fusion (listed capabilities): Scalable RAG knowledge base, text semantic understanding, natural speech dialogue, and visual scene understanding.
• Control methods: Android/iOS mobile app, PC host computer control, and USB wired remote control (standard).
• Beginner-friendly setup: Pre-assembled before shipping; TF card with factory image for plug-and-play; app QR-code network setup; tutorials and code provided.
• Servos & expansion: 6 HQ servos; multifunctional expansion board compatible with Jetson NANO, Raspberry Pi, Arduino, and Micro:bit. Servo configuration listed as 5×15KG bus servo + 1×6KG bus servo.

Specifications

Jetson NANO 4GB SUB Notes (listed)

• Jetson NANO 4GB SUB is described as: quad-core Cortex-A57 CPU, 128-core Maxwell GPU, 4GB LPDDR memory, and 472GFLOP computing power.
• Supported AI frameworks listed: TensorFlow, Pytorch, caffe/caffe2, Keras, MXNET, etc.
• Jetson NANO 4GB SUB is marked as Optional.

AI Vision & Large Model Demos (examples shown)

• AI vision interactive functions: color recognition tracking, grab color blocks, color interaction, catch game, garbage sorting, color block stacking.
• MediaPipe machine learning demos: gesture control robotic arm action group, gesture recognition stacking, palm recognition/tracking, arm posture control.
• Multimodal large model applications: video analysis, long-command motion control, intelligent handing, 3D space sorting.
• Embodied intelligence applications: color blocks back in place, visual tracking (KCF), garbage sorting (YOLOv11), intent inference (RAG knowledge base).

Notes from the provided materials: “Model training needs to be done by the user.” Some scene props (e.g., a trash can) are described as display props and are not included.

MoveIt / RViz Simulation & Planning (listed)

• MoveIt simulation control and trajectory planning.
• URDF support with RViz visual manipulation (drag-and-drop control, preset position control, obstacle avoidance).
• Collision detection and “spatial gripping” are shown as supported simulation functions.

What's Included

• Pre-assembled DOFBOT robotic arm (assembled before shipping)
• TF card with factory image file
• USB wired remote control (standard)

Tutorials / Videos

Online tutorials: http://www.yahboom.net/study/Dofbot-Jetson_nano

Support

For compatibility questions (Jetson/Raspberry Pi controller options), configuration confirmation, or after-sales support, contact https://rcdrone.top/ or email support@rcdrone.top.

Details

DOFBOT combines a 6‑DOF desktop arm and USB HD camera for ROS2 Python AI vision development, with 350mm reach and ±0.5mm repeatability.

Choose the control platform that fits your lab setup, from PC environments to Jetson-based AI development.

Upgraded configurations add depth vision and 3D interaction options for more advanced perception demos.

Alternative arm configurations are available when a different reach or degree-of-freedom layout is needed.

A pre-assembled DOFBOT platform that’s ready for guided learning, testing, and rapid ROS2 experimentation.

Built to support OpenCV-style vision workflows and higher-level interaction projects in one desktop system.

Optional Jetson Nano 4GB SUB provides the onboard compute for edge AI vision tasks and Python development.

Demo workflows cover natural interaction, task execution, and basic sorting scenarios for hands-on practice.

Vision-guided behaviors include tracking targets and performing simple pick-and-place style actions.

Interactive learning games help explore vision-plus-language style tasks in a classroom-friendly format.

Core vision demos include color recognition and tracking, interactive “catch” play, and rule-based sorting.

Includes gesture-based interaction concepts, model training examples, and inverse-kinematics motion control.

Use MoveIt with RViz simulation and motion planning to test trajectories and grasping logic before running live.

ROS2 Humble support pairs with mobile app, PC control, and USB wired remote options for flexible operation.

App-based controls add gesture-driven play, tracking demos, and custom action groups for repeatable movements.

Six articulated joints (J1–J6) provide a compact workspace for vision-guided manipulation and teaching motions.

Modular hardware options include bus servos, expansion/control boards, networking, and optional voice components.

The expansion board and serial bus servos simplify wiring and make it easier to extend the arm with add-ons.

The DOFBOT kit includes a USB camera module (480p/30fps, 110°) and an AI voice module with a small speaker for vision and voice input.

Yahboom DOFBOT training resources include 200+ systematic courses for learning vision robotic arm setup and programming.

The included DOFBOT course syllabus lays out the training modules and lesson outlines to guide setup and learning.

Yahboom DOFBOT includes open-source code and detailed tutorials, plus 3D model files and after-sales technical support resources.

The DOFBOT 6-DOF robotic arm includes dimension drawings and a specification table to help plan mounting and workspace clearances.

The DOFBOT kit includes the robotic arm assembly, camera, OLED display, controller handle, cables, suction cups, screws, tools, and a manual.

Jetson Nano accessories include the Nano 4GB board (optional), cooling fan, SD card, wireless network card, and ribbon cable.