NexArm ROS Advanced Sorting Sandbox Kit: the arm on a square metal baseplate with sorting trays, waste bins and coloured blocks

Robot arms

NexArm ROS Sorting Sandbox Kit

NexArm ROS on a metal sorting sandbox with a touchscreen, in Basic, Standard and Advanced kits.

Raspberry Pi
NVIDIA Jetson
Suggested for university

The NexArm ROS Sorting Sandbox Kit sets the NexArm ROS robot arm on a modular metal baseplate with a recognition zone and a 7-inch touchscreen, making it a smart sorting station. Computer vision, localisation, path planning and grasp control let the arm identify objects by colour and shape and sort cluttered items quickly. The Basic Kit puts the arm, depth camera, touchscreen and recognition panel on a 304 × 304 mm baseplate; the Standard Kit doubles the baseplate and adds sorting trays; and the Advanced Kit doubles it again and adds waste bins for waste classification. Each runs on a Raspberry Pi 5 or NVIDIA Jetson with an ESP32 controller, and Hiwonder supplies tutorials, source code and system images.

Zeta42 is an authorised Hiwonder partner in the Middle East.

Configurations

Choose how it ships.

Model: Basic Sorting Sandbox Kit · Standard Sorting Sandbox Kit · Advanced Sorting Sandbox Kit
Controller: Without Raspberry Pi Controller · With Raspberry Pi 5 (4GB) · With Raspberry Pi 5 (8GB) · With Raspberry Pi 5 (16GB) · Without Jetson Controller · With Jetson Nano(4GB) · With Jetson Orin Nano Super(4GB) · With Jetson Orin Nano Super(8GB) · With Jetson Orin NX Super(8GB) · With Jetson Orin NX Super(16GB)

What it does

Built for.

Three sandbox kits
Basic (304 × 304 mm): the arm, 3D depth camera, 7-inch touchscreen, metal baseplate and recognition panel. Standard (608 × 304 mm): adds four sorting trays. Advanced (608 × 608 mm): adds four waste bins as well.
3D vision and hand-eye coordination
Fusing colour and depth lets the arm see colours and point clouds, and inverse kinematics turns that into 3D grasping, sorting and transporting.
Smooth arm motion
Multi-DOF joints with trapezoidal acceleration and deceleration give smooth, steady motion for grasping, carrying and placing from several angles.
Large AI models and OpenClaw
Language and vision models working with the OpenClaw agent handle tasks such as understanding a scene, tracking a moving object and gathering data into reports.
Grows with the class
The modular baseplate lets a class move from controlling a single arm to work across several stations, and the arm also takes Hiwonder's electric sliding rail.
Choosing a controller
Choose a Raspberry Pi 5 or a Jetson Nano, Orin Nano Super or Orin NX Super. Hiwonder recommends an Orin controller for deeper development of AI models. Kits without a controller come with the matching expansion board and enclosure.

Where it is used

Applications.

Teaching automated sorting and smart logistics
Colour, shape and waste classification exercises (waste bins: Advanced Kit)
University ROS 2 and machine vision labs
Classroom stations that grow from one arm to several workstations

Videos

See it run.

Specifications

The full sheet.

Sandbox dimensions: Basic: 304 × 304 mm; Standard: 608 × 304 mm; Advanced: 608 × 608 mm
Touchscreen: 7-inch HD touchscreen (all kits)
Sorting props: Sorting trays (Standard and Advanced Kit); waste bins (Advanced Kit)
Material: Metal brackets
ROS controller: Raspberry Pi 5 / Jetson Nano / Jetson Orin Nano / Jetson Orin NX
ESP32 controller: ESP-WROOM main chip
Camera: Depth camera
Servo models: HX-12H / HX-30HM / HX-65HM intelligent bus servos
Control methods: ROS topics/nodes, Python programming, app control, PC software control
Power supply: 12V 5A DC power adapter
Operating system: Ubuntu 22.04 + ROS 2 Humble
Software: iOS/Android app, Windows PC software
Communication: USB, Wi-Fi, Ethernet
Programming tools: Python, C, C++
Storage: 64 GB TF card (Raspberry Pi 5 / Jetson Nano); 128 GB SSD (Orin Nano / Orin NX)
Included materials: Tutorials, ROS source code, ESP32 source code, system images, supporting software