Wlkata AI Vision Set - Textbook included - OpenMV Machine vision high quality CNC artificial intelligence

Wlkata AI Vision Set - Textbook included - OpenMV Machine vision high quality CNC artificial intelligence

Name: Wlkata AI Vision Set - Textbook included - OpenMV Machine vision high quality CNC artificial intelligence
Brand: Wlkata
SKU: WL-AC-ViMV-Re300
Price: 890.00 USD
Availability: InStock

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SKU WL-AC-ViMV-Re300

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$890.00 - $890.00

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WLKATA AI Vision Set

Overview

The WLKATA AI Vision Set is a machine vision platform for WLKATA robotic arms, built around an OpenMV 3 vision camera. It is an artificial intelligence learning platform based on Python programming, letting students recognize the color and shape of objects and then have a WLKATA Mirobot handle them automatically. It is a practical, hands-on way to teach the basics of machine vision and OpenMV.

The set includes a vision stand, the OpenMV 3 camera module with a 640 by 480 color sensor, a light ring for consistent lighting, a display screen, a visual calibration board, and a package of wooden blocks for experiments. The frame is aluminum alloy with CNC machining for stability, and its modules and stand are detachable for flexible setups. A digital textbook with source code for each experiment is included.

WLKATA AI Vision Set with OpenMV camera and vision stand

Specifications

WLKATA AI Vision Set components and dimensions

Vision
Camera	OpenMV 3 machine vision camera
Resolution	640 x 480 color sensor
Lighting	Light ring for consistent illumination
Display	Included display screen
Build and Software
Construction	Aluminum alloy with CNC machining
Design	Modular, with detachable modules and stand
Software	OpenMV and Python
Compatibility	WLKATA Mirobot and other WLKATA arms

Key Features

OpenMV Machine Vision: An OpenMV 3 camera performs onboard image processing for color and shape recognition.
Python-Based Learning: Students program recognition tasks in Python, a real, transferable skill.
Consistent Imaging: A light ring and display screen support reliable image capture and review.
Calibration Included: A visual calibration board helps align the camera with the robot workspace.
Modular and Portable: Detachable modules and an aluminum-alloy stand allow flexible, custom installations.
Textbook and Code: A digital textbook with source code for each experiment is included.

WLKATA AI Vision Set recognizing object color and shape

Applications

WLKATA AI Vision Set guiding a Mirobot in a classroom

The AI Vision Set is used to teach machine vision and AI in classrooms and labs. Paired with a WLKATA Mirobot, it enables vision-guided pick-and-place and sorting, so students can build a complete see-and-act workflow: the camera identifies an object by color or shape, and the arm handles it.

Because the target objects can be changed, instructors can create progressively more complex scenarios, from simple color sorting to shape-based reorientation, encouraging innovation and deeper understanding of computer vision.

Setup and Getting Started

Assemble the stand: Build the vision stand and mount the OpenMV 3 camera and light ring.
Connect the display: Attach the display screen so you can see the camera view.
Install the software: Set up OpenMV and Python, following the included handbook.
Calibrate: Use the calibration board to align the camera with the robot workspace.
Run a recognition demo: Use the wooden blocks to test color and shape recognition.
Connect a Mirobot: Link the vision system to a Mirobot for vision-guided handling.

WLKATA AI Vision Set assembly and calibration

What's Included

Vision Stand: (x1)
Camera: OpenMV 3 vision camera module (x1)
Lighting: Light ring (x1)
Materials: Wooden blocks package and visual calibration board
Display: Display screen (x1)
Documentation: Handbook and digital textbook with source code

Documentation and Resources

Developer Community (GitHub): github.com/wlkata

Warranty Information

The WLKATA AI Vision Set is covered by the WLKATA Product Warranty Policy, provided by Wristline Inc. (WLKATA) or its authorized agents. RoboticsSelect is an authorized WLKATA dealer, so warranty support is handled through us.

Item	Coverage
WLKATA AI Vision Set	1-year warranty
Spare Parts	3-month, 6-month, or 1-year warranty, depending on the part
Consumables	Not covered under warranty

Not Covered

Damage from misuse, accident, or operation outside the documented limits
Damage from unauthorized repair or modification
Consumable and wear parts

Warranty service requires a valid proof of purchase.

See It In Action

How to Install the WLKATA AI Vision Set

Frequently Asked Questions

What is in the AI Vision Set?

An OpenMV 3 machine-vision camera module with a 640 x 480 color sensor, an aluminum-alloy CNC vision stand, a light ring for consistent lighting, a display screen, a visual calibration board, a package of wooden blocks for experiments, a handbook, and a digital textbook with source code for each experiment. It works with the Mirobot and other WLKATA arms and is designed for teaching the basics of machine vision and OpenMV.

Why OpenMV instead of a regular USB camera?

OpenMV is a self-contained machine-vision module with an onboard MicroPython interpreter. It runs vision code directly on the camera module, returning results (object positions, color matches, marker IDs) over a serial link rather than sending raw video to a host computer. This teaches students about edge AI: real-world deployments often run vision on small embedded devices, not on full PCs.

What can students do with it out of the box?

The included experiments cover color recognition, shape recognition and face tracking, and, with a Mirobot, color sorting, shape sorting and shape reorientation with the arm. Each experiment ships as a standalone MicroPython script with source code. Students can modify any example by editing the script in the OpenMV IDE.

Can students train their own object classifiers?

Not as part of the included curriculum. The textbook experiments use the OpenMV camera's onboard color, shape and face detection rather than trained classifiers. Whether custom neural-network models can be loaded depends on the OpenMV firmware and camera generation; contact us if trained-classifier projects are a requirement for your course.

How does it integrate with WLKATA arms?

The camera mounts on the included vision stand above the workspace, and the visual calibration board aligns camera coordinates with the arm's workspace. The camera identifies an object by color or shape and the arm handles it; the digital textbook's Mirobot applications (color sorting, shape sorting and shape reorientation) include the source code for each experiment.

Does the textbook teach machine learning theory or just practical use?

Mainly practical, with the fundamentals needed to understand it. The digital textbook opens with foundations (introduction, debugging, OpenMV basics and image fundamentals), then moves into OpenMV and Mirobot applications, with additional documents, source code and development materials. Each experiment is hands-on with the included camera and blocks.

What programming languages are required?

MicroPython on the camera (a subset of Python) through OpenMV, and standard Python on the host computer for examples that involve a paired arm through the WLKATA Python SDK. WLKATA describes the set as a Python-based AI learning platform; some Python familiarity helps, and the foundations chapters introduce OpenMV and image basics.

Is the camera durable in a classroom setting?

Reasonably. The camera is a small PCB module mounted on an aluminum-alloy CNC vision stand, with detachable modules for flexible setups, so the electronics stay clear of the work area during normal student handling. Treat the camera module and lens as you would any classroom electronics; spare parts are available through WLKATA.

What is the warranty?

12-month warranty on the AI Vision Set. Spare parts carry 3-month, 6-month or 1-year coverage depending on the part, and consumables are not covered. The textbook is a digital download. RoboticsSelect handles warranty service through the authorized channel.