Yahboom JetCobot 7-DOF Visual Collaborative Robotic Arm for Jetson Nano B01 4GB/Orin Nano SUPER/Orin NX SUPER

Yahboom

$1,167.80 USD

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Main control board With Jetson NANO 4GB With Jetson Orin NANO 4GB SUPER With Jetson Orin NANO 8GB SUPER With Jetson Orin NX 8GB SUPER With Jetson Orin NX 16G SUPER

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Overview

JetCobot is a 7-axis visual collaborative robotic arm that uses an NVIDIA Jetson series development board as the main control board (Jetson Nano B01 4GB / Jetson Orin Nano SUPER / Jetson Orin NX SUPER). With a UR-like robot configuration, ROS robot operating system, and an inverse kinematics algorithm, it supports coordinate control, motion planning, gripping, sorting, and related vision-interaction tasks.

JetCobot integrates a robotic arm and camera system. It is equipped with a 0.3MP USB camera (110° field of view) and supports OpenCV image processing, machine vision, and deep learning workflows for functions such as color interaction, face detection/tracking, label recognition, model training, and gesture interaction.

Key Features

7-DOF structure with UR-like configuration: Smooth body design, large range of motion, and hidden servo wiring (as described in the comparison chart).
Inverse kinematics + ROS workflow: Supports coordinate control and motion planning.
MoveIt + RViz support: Includes URDF kinematics simulation model, MoveIt simulation control/trajectory planning, collision detection, and spatial gripping scenarios.
AI visual recognition and target tracking: Color recognition and tracking, color block sorting, color block grabbing, color interaction, face recognition and tracking, and label recognition/intelligent stacking (Apriltag label codes).
Deep learning / model training: Supports garbage classification workflows and region-based grabbing examples (region identification: grabbing and place; region detection: customize grabbing).
MediaPipe development / AI interaction upgrade: Gesture control action group, gesture recognition control stack, robotic arm recognition and palm tracking, and gesture posture control robotic arm.
Multiple control methods: Supports MoveIt simulation control, handle control, and PC web control (Jupyter Lab control is also shown).

Specifications

Product	JetCobot AI visual collaborative robotic arm
Degrees of freedom	7
Maximum effective arm span	270MM
Joint rotation range	-153° to 153°
Repeat positioning accuracy	±0.5mm
Camera	0.3MP USB camera
Camera field of view	110°
Camera frame rate (shown)	30fps
Visual dimension (chart)	Plane 2D image
Gripper (shown)	Electric gripper
Gripper open-close angle (chart)	5cm
Gripper range (shown)	20-45mm
Gripper force (shown)	150g force
Structure type (chart)	UR-like robot structure
Main control (chart)	Jetson Nano B01 / Jetson Orin Nano SUPER / Jetson Orin NX SUPER
Function (chart)	Interconnection control; MoveIt motion planning; RViz robot simulation; 2D visual interaction
Voice (chart)	/
Display (chart)	/

Jetson Master Control Options (Reference Chart)

Main control board	Jetson Nano B01 4GB	Jetson Orin Nano SUPER 4GB	Jetson Orin Nano SUPER 8GB	Jetson Orin NX SUPER 8GB	Jetson Orin NX SUPER 16GB
Computing power	0.5TFLOPS (FP16)	34 TOPS	67 TOPS	117 TOPS	157 TOPS
CPU	4 cores Arm Cortex-A57 MPCore processor	6-core Arm Cortex-A78AE v8.2 64-bit CPU; 1.5MB L2 + 4MB L3	6-core Arm Cortex-A78AE v8.2 64-bit CPU; 1.5MB L2 + 4MB L3	6-core NVIDIA Arm Cortex-A78AE v8.2 64-bit CPU; 1.5MB L2 + 4MB L3	8-core NVIDIA Arm Cortex-A78AE v8.2 64-bit CPU; 2MB L2 + 4MB L3
GPU	128 cores NVIDIA Maxwell GPU	512-core NVIDIA Ampere architecture GPU with 16 Tensor Cores	1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores	1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores	1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores
Memory	4GB 64-bit LPDDR4 25.6GB/s	4GB 64-bit LPDDR5 51GB/s	8GB 128-bit LPDDR5 102 GB/s	8GB 128-bit LPDDR5 102 GB/s	16GB 128-bit LPDDR5 102 GB/s
Storage	16GB eMMC + 64GB U disk	256GB SSD
Power	5W - 10W	7W, 10W, 25W	7W, 15W, 25W	10W, 15W, 25W, 40W
ROS system version	Ubuntu18.04 + ROS1 Melodic	Ubuntu22.04 LTS + ROS2 Humble

The chart also notes that the usage methods of multiple Jetson series control boards are basically the same; different control boards mainly affect JetCobot performance.

Measured Function/Performance Difference (Reference Chart)

Item	Jetson Nano Version Program start time / Program running frame rate	Jetson Orin Nano SUPER 8GB Version Program start time / Program running frame rate	Jetson Orin NX SUPER 16GB Version Program start time / Program running frame rate
Robot startup	43s Robotic arm initialization completed / /	38s Robotic arm initialization completed / /	37s Robotic arm initialization completed / /
Basic visual function (Color recognition)	6s / 12s	5s / 30fps	4s / 30fps
Yolov5 garbage classification	31s / 6s	17s / 30fps	16s / 30fps
Mediapipe face detection	13s / 30s	8s / 30fps-40fps	7s / 30fps-50fps
Color block tracking	10s / 30s	7s / 30fps	5s / 30fps
Apriltag tag code recognition	5s / 25s	3s / 30fps	3s / 30fps
RVIZ simulation modeling	16s / 31s	9s / 31fps	7s / 31fps

Notes shown with the chart: JetCobot is not configured with Docker container technology; it uses an official native image configuration function environment to give full play to overall motherboard performance. The data is from an actual Yahboom laboratory test; Jetson Orin Nano SUPER 4GB and 8GB performance is similar, and Jetson Orin NX SUPER 8GB and 16GB performance is close.

What's Included

myCobot280 7-DOF collaborative robotic arm (JetCobot)
Electric gripper
USB camera
Jetson main control (Jetson Nano B01 / Jetson Orin Nano SUPER / Jetson Orin NX SUPER, depending on version)
OLED screen (listed in the shipping list chart)
Accessories (as listed in the shipping list chart)

Applications

ROS learning, kinematics, and motion planning (MoveIt / RViz)
Machine vision and OpenCV-based interaction experiments
AI interaction demos: color tracking, label recognition (Apriltag), gesture recognition, and model training workflows
Desktop grasping, sorting, and basic coordinate-based pick-and-place tasks

Manuals / Documentation

Tutorials: https://www.yahboom.net/study/JetCobot

For pre-sales selection help or after-sales support, contact https://rcdrone.top/ or email support@rcdrone.top.

Details

Comparison chart highlighting JetCobot vs other ROS robotic arm masters, with key specs and features

Compare JetCobot with other ROS master-control options to choose the right platform for your application.

Specs table for DOFBOT SE ROS master control, listing accuracy, arm span, camera type, and functions

Multiple Yahboom arm platforms share a similar ROS workflow, while hardware and vision options vary by model.

DOFBOT-PRO comparison table featuring depth camera option and 3D visual interaction capability

Depth-camera configurations support 3D vision tasks such as distance-aware tracking and interaction.

JetCobot comparison chart listing 7-DOF, 270 mm reach, ±0.5 mm repeat accuracy, and UR-like structure

JetCobot focuses on a 7-DOF UR-like structure with millimeter-level repeatability for coordinated motion tasks.

Yahboom JetCobot 7-DOF AI visual collaborative robotic arm kit with base, arm, and packaging

Yahboom JetCobot is a desktop 7-DOF visual collaborative robotic arm built around NVIDIA Jetson control boards.

JetCobot product introduction poster with icons for ROS, MoveIt, RViz, OpenCV, deep learning, and MediaPipe

A complete software stack supports ROS control, MoveIt planning, RViz visualization, and OpenCV-based vision.

Jetson Orin SUPER performance overview graphic comparing Nano B01, Orin Nano, and Orin NX options

Select Jetson Nano B01, Orin Nano SUPER, or Orin NX SUPER based on the compute needed for your AI pipeline.

Jetson series selection matrix for ROS master control, with CPU/GPU specs, memory, and Ubuntu/ROS versions

A clear Jetson comparison helps match CPU/GPU and memory capacity to ROS and vision workloads.

Function operation difference table for JetCobot across Jetson versions, with task timing and FPS metrics

Performance varies by Jetson controller, while the JetCobot feature set and course examples remain consistent.

JetCobot UR-like robot configuration photo highlighting smooth arm design and hidden wiring concept

The UR-like configuration provides a wide range of motion with a cleaner build for classroom and lab use.

Analysis graphic comparing JetCobot 7-DOF UR-like design vs typical 6-DOF arms, wiring, reach, and control

A 7-DOF layout improves flexibility for positioning, grasping, and path planning in tight workspaces.

Integrated robotic arm and camera setup scanning color blocks; text notes ±0.5 mm repeat positioning accuracy

An integrated USB camera enables visual picking and sorting workflows without complex external camera setups.

AI visual recognition and target tracking examples: color sorting, grabbing, interaction, tag stacking, tracking

Built-in demos cover color recognition, block sorting, tag-based stacking, and tracking-based interaction.

Deep learning and MediaPipe feature panel: model training, region detection grabbing, gesture recognition control

Use deep-learning model training and MediaPipe gesture interaction to build more responsive pick-and-place tasks.

MoveIt kinematics and planning collage for JetCobot, including URDF model, collision detection, and spatial grip

MoveIt and URDF models support simulation, trajectory planning, and collision checking before running on hardware.

Cross-platform remote control options: web-based JupyterLab control and USB gamepad teleoperation

Control JetCobot through a browser-based Jupyter environment or a USB gamepad for quick testing and demos.

Inverse kinematics algorithm graphic with multi-pose arm overlay for coordinate-based positioning control

Inverse kinematics enables coordinate input for repeatable positioning and consistent end-effector orientation.

7-DOF collaborative robot joint map labeled J1–J7 on JetCobot arm beside a laptop and Jetson carrier base

Seven joints (J1–J7) provide extra flexibility for motion planning and coordinated grasping.

JetCobot robotic arm working radius diagram with 270mm reach and J1 base rotation range ±153°

JetCobot offers a 270mm maximum effective arm span (without gripper), with J1 base rotation of ±153° and ±0.5mm repeatability.

Graphic describing ROS Robot Operating System support for Yahboom JetCobot, listing ROS2 Humble and ROS1 Melodic.

JetCobot is built around the ROS Robot Operating System and lists compatibility with ROS2 Humble and ROS1 Melodic.

JetCobot robotic arm beside a monitor showing MoveIt simulation control interface for a 7-DOF collaborative arm

MoveIt simulation support lets the JetCobot robotic arm be tested and controlled in a virtual environment before running on hardware.

Yahboom JetCobot robotic arm kit with gripper, USB HD camera, OLED screen, suction-cup base and metal chassis

The JetCobot arm kit combines a gripper, USB HD camera, OLED screen, and a suction-cup base for stable desktop setups.

Yahboom JetCobot robotic arm with USB HD camera module and motorized gripper mounted on the end effector

The JetCobot arm pairs a USB HD camera (480p, 30 fps, 110° field of view) with a compact electric gripper for vision-guided picking and placement tasks.

JetCobot course outline table listing lessons on assembly, ROS/Ubuntu setup, SLAM, AI vision, tracking, and grasping

The JetCobot curriculum covers setup and assembly, ROS/Ubuntu basics, SLAM mapping, AI vision with MediaPipe, and visual tracking and grasping exercises.

JetCobot tutorial materials page with download folders and course sections, plus study link yahboom.net/study/JetCobot

JetCobot tutorial materials include organized download folders and course content such as AI visual basics and Mediapipe, with a study link at yahboom.net/study/JetCobot.

Course resource overview for Yahboom JetCobot, listing AI visual tracking/grabbing, MoveIt, ROS2 tutorials, and Python code

JetCobot learning resources include AI visual tracking and grabbing courses, MoveIt tutorials, ROS2 basics, and open Python source code.

JetCobot robotic arm with gripper dimension drawing showing overall height and base footprint measurements in mm

JetCobot with gripper dimensions are provided in millimeters to help plan mounting space and overall arm clearance.

JetCobot 7-DOF visual collaborative robotic arm specs table with Python support, ROS options, and camera details

JetCobot supports Python programming with ROS options for Jetson Nano B01 and Jetson Orin Nano/NX, plus a fixed-focus 0.3MP camera (480P, 30fps, 110° wide angle).