NexArm ROS2 Dual-Arm AI Robotic Arm Conveyor Platform with Jetson Nano (4GB)
- Two NexArm 6DOF robotic arms with inverse-kinematics coordination
- 3D depth camera for depth, spatial coordinates and 3D grasping
- Jetson Nano (4GB) controller running Ubuntu 18.04 + Docker + ROS 2 Humble
- Electric conveyor belt and 11.6-inch HD LCD touchscreen
- WonderEcho Pro AI voice interaction box
- Python, C and C++ with PC software, app, wireless controller and voice control
- 608 × 912 mm platform, 12V 5A power supply
- Trusted dealerDirect manufacturer partnership
- Pan-India deliveryInsured shipping, all states
- Post-sale supportTraining + service included
What makes it work
NexArm ROS2 Dual-Arm AI Robotic Arm Conveyor Platform with Jetson Nano (4GB) – ESP32 & Jetson with 3D Vision, VLA & Multimodal AI
The Dual-Arm Conveyor Development Kit is an all-in-one experimental platform purpose-built for advanced ROS education and embodied AI research.
Product Description
The Dual-Arm Conveyor Development Kit is an all-in-one experimental platform purpose-built for advanced ROS education and embodied AI research. Featuring an advanced modular architecture, it natively fuses multimodal large models, OpenClaw agents, ACT, VLA, machine vision, and inverse kinematics into a complete validation loop spanning foundational concepts to high-level embodied algorithms.
The dual-arm conveyor sandbox integrates advanced hardware—including a 3D vision dual-arm system, a Jetson controller, an electric conveyor belt, and an 11.6-inch HD touchscreen—alongside a visual control center. This setup enables full-stack ROS development experiments, seamlessly replicating complex AI interactions found in industrial production lines.
Available Options
Controller
Key Features & Applications
Dual-Arm Collaboration
Powered by advanced inverse kinematics for precise time synchronization, two NexArm ROS robotic arms seamlessly coordinate to execute complex tasks like transferring, transporting, and sorting.
Large AI Model & OpenClaw
Fusing the OpenClaw agent with multimodal AI models across speech, language, and vision, the NexArm ROS robotic arm executes complex remote tasks like visual scene understanding, dynamic object tracking, and data aggregation and analysis.
3D Depth Perception
Integrated with a 3D depth camera, NexArm accurately captures targets' depth and spatial coordinates, enhancing the robotic arm's environmental perception with true 3D dimensions.
3D Spatial Grasping
By fusing RGB and depth data, NexArm executes advanced AI tasks like omnidirectional grasping, sorting, and transporting in 3D space.
Dual-Arm Conveyor Development Kit
Driven by low-level algorithms like advanced inverse kinematics, this dual-arm conveyor setup efficiently coordinates complex tasks like transferring, transporting, and sorting, perfectly fulfilling the needs of embodied AI education and automation simulation.
Multiple Configuration Options
Supports mobile suspended chassis and electric sliding rails to precisely simulate smart warehousing, logistics sorting, and automated production lines for rapid Embodied AI algorithm validation.
NexArm ROS Robotic Arm
Integrating multimodal large models, advanced machine vision, inverse kinematics, and natural interaction, it supports visual calibration, basic picking, and sorting operations. It offers a flexible development environment for ROS onboarding and rapid algorithm validation, covering full-pipeline embodied AI experimental needs.
Suspended Mobile Chassis
NexArm ROS is integrated with a suspended tank or suspended omnidirectional Mecanum wheel chassis. Beyond supporting remote mobile control via wireless controller or app, the setup drives efficient mobile tracking and autonomous line following.
Sorting Sandbox
Combining computer vision, localization, path planning, and precision grasp control, this sandbox accurately identifies features like color and shape to rapidly classify and sort cluttered items. It serves as an ideal hands-on platform for teaching automated sorting and smart logistics.
Sliding Rail Warehouse Sandbox
Integrates a high-precision electric linear sliding rail and multi-tier shelving. It supports multi-workstation transport, automated inventory sorting, and inbound control to fully replicate industrial warehousing and logistics workflows.
Hardware Specifications
Product Videos
Packing List
Technical Specifications
| Product | NexArm ROS Dual-arm conveyor development kit |
|---|---|
| Dimensions | 608 × 912 mm |
| Weight | Total weight: 7.74 kg; single arm weight: 1.94 kg |
| ROS controller | Jetson Nano (4GB): Ubuntu 18.04 LTS + Docker + ROS 2 Humble |
| Inputs | 3D depth camera, PS3 wireless controller, AI voice interaction box supporting recognition & broadcast |
| Outputs | Robotic arm/gripper, buzzer, 11.6-inch display, conveyor belt, AI voice interaction box supporting recognition & broadcast |
| Programming languages | Python / C / C++ |
| Power supply | 12V 5A DC power adapter |
| Power port | DC5.5 × 2.5 power port |
| Communication methods | USB serial / Wi-Fi / Bluetooth / ROS 2 |
| Control methods | PC software / app / wireless controller / voice / ROS 2 program control |
| Equipped robotic arm | NexArm 6DOF robotic arm |
| Frame material | Metal frame |
Frequently Asked Questions
Which controller does this version use?
This version is the NexArm ROS Dual-arm conveyor development kit with Jetson Nano (4GB), running Ubuntu 18.04 LTS + Docker + ROS 2 Humble.
What is included in the packing list?
The packing list shows NexArm ROS robotic arms, 3D depth cameras with mounting brackets, WonderEcho Pro AI voice interaction boxes, 12V 5A power adapters, G clamps, PS3 wireless controllers, card readers, blocks, cubes and cards, maps, cables, a screw pack, a conveyor belt, sandbox metal baseplates, a recognition panel, sorting trays, waste bins, an 11.6-inch HD LCD touchscreen with bracket, and HDMI and data cables.
How do the two arms work together?
Using inverse kinematics for precise time synchronization, the two NexArm ROS robotic arms coordinate to transfer, transport and sort items.
How does the arm see objects?
A 3D depth camera captures depth and spatial coordinates; fusing RGB and depth data enables omnidirectional grasping, sorting and transporting in 3D space.
Which programming languages and control methods are supported?
Python, C and C++, with PC software, app, wireless controller, voice and ROS 2 program control, over USB serial, Wi-Fi, Bluetooth or ROS 2.
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