WLKATA Mirobot 6DoF Mini Industrial Robotic Arm User Manual

Mirobot 6DoF Mini Industrial Robotic Arm

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WLKATA Product Selection Guidebook
Robotics Training Solution For AI and IoT Education

Professional ·

Safe · Desktop

Copyright © WLKATA Robotics 2022

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Contents

Main Product

03

Mirobot Educational 6-Axis Robotic Arm

04

Curriculum Resources

08

Robotics Planning, Control and Innovation

09

Developing Robot With ROS

10

Learning Robots with WLKATA Mirobot

11

Fundamentals of WLKATA Mirobot Robot Arm

13

Control and Programming

Additional Set

14

AI Vision Set

15

Deep Learning Vision Set

17

Robot Arm Vehicle

19

WLkata Mirobot IOA Virtual Factory Set

21

Comprehensive Teaching And Training Platform

24

Fruit Picking Line

25

Logistic Warehousing Sorting Line

26

AI Static Garbage Sorting Production Line

28

AI Automatic Sorting Production Line

29

Automobile Assembly Line

30

Deep Learning Moving Garbage Sorting Line

31

Robotics Integrated Training Station

32

Chess Manufacturing Line

35

Automotive Manufacturing Simulation Line

36

Main Product

03

Mirobot 6-Axis Robotic Arm

04

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Mirobot 6-Axis Robot Arm
Desktop 6-Axis Engineering Educational Robot Arm
Product Description Mirobot Robot Arm is a safe and easy-to-use desktop 6-axis educational robot, using the industrial six-axis robot
arm as the design prototype. It is also an open-source AI robot comprehensive teaching platform. Mirobot has functions such as writing and drawing, laser engraving, handling palletizing, etc. It supports
Bluetooth, Wi-Fi, serial port, RS485, and other communication modes. It can be combined with hardware for smart factory education and application scenarios.
It is flexible to plan the movement and free to add any end tools to meet the learning needs of different ages. It also supports Python, C, C++, ROS, V-REP, MATLAB, and other software for secondary development.
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Product Features
Writing Drawing Digital Twin

Handling Palletizing

Somatosensory Control

AI Vision

Laser Engraving Professional and Easy-to-use: Mirobot references the industrial six-axis robot arm as the design prototype; has a
variety of control methods such as PC, mobile APP, Bluetooth Teach Pendant, etc. meets the needs of practical training and research in multiple scenarios.
Lightweight and Safer: net weight of 1.5Kg, chassis diameter of 160mm. Integrated design to meet the needs of “classroom-research-practice” integration.
Open-source and Extensibility: Mirobot provides open-source for robot learning and scientific research kinematics, vision and other algorithms, supports Bluetooth, Wi-Fi, RS485, and other communication methods, provides students with a new and innovative learning platform.

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Selection Guide

| Product Name |

Model

Highlights

Mirobot Education Kit
Mirobot Professional Kit

WL-MiroEDU-6R200-02MM

Accessories include micro servo gripper, pen holder, pneumatic set (single /double-finger suction cups, three-finger soft gripper)

WL-MiroPRO-6R200-02MM

Accessories include micro servo gripper, pen holder, pneumatic set (single /double-finger suction cups, three-finger soft gripper), Bluetooth teach pendant

Sliding Rail Set

WL-AC-SR500-01MM Features automatic reset function

Conveyor Belt Set

WL-AC-CB600-01MM

Accessory includes photoelectric sensor which enables the detection and action response of objects

Experiment Content
No.
1 2 3 4 5 6 7 8 9 10

Experiment Content
Understanding of Robotic Arm Structure Understanding of Electrical Principles of Robotic Arm
Understanding of Robotic Arm D-H Parameters Understanding of Robotic Arm Coordinate Mode
Understanding of Robotic Arm End Effector Understanding of Electrical Parameters of Robotic Arm Understanding of Robotic Arm Basic Control Command
Understanding of Robotic Arm Movement Robot Arm Programming Control Logic Robotic Arm Application Development

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Product Parameters

Product Name

Detailed Parameters

Number of Axes

6+1

Limit Loads

600g

Workspace

315mm

Net Weight

1.5Kg

Communication Interface

USB/Wi-Fi/Bluetooth/RS485

Base Dimensions

Diameter 160mm

1 axis: -110° ~ +160° maximum speed 85°/s

Axis Motion Parameters (Load 160g)

2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s

Mirobot Education Kit

5-axis: -200° ~ +30° maximum speed 200°/s 6-axis: -360° ~ +360° maximum speed 450°/s

Pen Holder

Range: 7~10mm

Servo Gripper

Range: 0~30mm Torque: 0.6 Kg/cm

Pneumatic Suction Cups

Suction Cup Diameter: 12mm Pressure: -60Kpa

Three-finger Soft Gripper

Range: 5~40mm Pressure: -60/120Kpa

Multifunctional Extender Box

Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED

Application

WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming

Limit Load

10Kg

Distance

500mm

Sliding Rail Set (Optional)

Maximum Speed Size

6000mm/min 860mm×285mm×111mm

Weight

4.6kg

Repeatability

0.5mm

Equipped with photoelectric sensors

Limit Load

5Kg

Conveyor Belt Set (Optional)

Distance Maximum Speed

530mm 2400mm/min

Size

610mm × 100mm × 50mm

Weight

2.5kg

7

Curriculum Resources

08

Robotics Planning, Control and Innovation ­ Manual of

09

Experiments Based on Mirobot

Developing Robot With ROS

10

Learning Robots with WLKATA Mirobot

11

WLKATA Mirobot Robotic Arm Programming And Control

13

8

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Robotics Planning, Control and Application ­ Manual of Experiments Based on Mirobot

Content Description
“Robotics Planning, Control and Application ­ Manual of Experiments Based on Mirobot” combines with the Mirobot robotic arm, includes the principle of robotics in the development process of the six-axis robot. It covers experimental projects such as the mathematical basis of robots, the forward kinematic analysis of robots, the calculation and control of robot inverse kinematics, and robot dynamics and control.
Course Catalog

Content

Chapter

Chapter 1 Introduction

1.1 Initial Knowledge on Industrial Robots 1.2 Robot Simulation System

2.1 Transformation in Virtual Laboratory

Chapter 2 Transformation

2.2 Transformation Matrix into Euler Angles 2.3 Painting Demonstration and Frame Transformation in 2-Dimensional Space

2.4 Frame Transformation by Changing the Frame of the End-effector

3.1 Forward Kinematics

Chapter 3 Kinematics

3.2 Co-simulation of Forward Kinematics with MATLAB and V-REP 3.3 Establishment and Computation of Forward Kinematics 3.4 Inverse Kinematics Modeling

3.5 Inverse Kinematics Computation and Co-simulation in MATLAB

3.6 Inverse Kinematics Solution and Co-simulation

Chapter 4 Static

4.1 Static Computation Frame in 3D Deduction 4.2 Statics Computation of Manipulator

Chapter 5 Dynamics

5.1 Dynamics Computation Frame 3D Deduction 5.2 Dynamics Computation of the Manipulator

Chapter 6 Motion Control

6.1 Design of Driving Joint of Manipulator 6.2 Stepper Motor

7.1 Motion Planning for Given Initial and Final Point

Chapter 7 Motion Planning

7.2 Motion Planning Given Initial Point, Final point and Intermediate Point 7.3 Example on Motion Planning of the Manipulator

7.4 Continuous Trajectory Motion Planning

Chapter 8 Application of control algorithm for 6-axis desktop manipulator

8.1 Grasping Object Experiment Base on Inverse Kinematics 8.2 Desktop Robotic Arm Painting Using Motion Trajectory Planning 8.3 Laser Engraving via Robotic Arm 8.4 Grasp Objects Based on Color Recognition

Features
The supporting content includes the experimental purpose, experimental principle, experimental steps, and experimental summary

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Developing Robot With ROS

Content Description
“Developing Robot With ROS ­ Based On WLKATA Mirobot” covers the basics of ROS tutorial, software framework, and basic functions of ROS, together with the development process of Mirobot robotic arm in ROS by introducing the function cases of robot arm motion control, machine voice, machine vision, etc., and is equipped with ROS charts, codes, etc.
Course Catalog

Content

Chapter

Chapter 1 Getting to Know
ROS
Chapter 2 Installation of ROS

The Origin Of ROS, The Design Goals Of ROS, The Characteristics Of ROS Install Ubuntu in Virtual Machine and Install ROS In Ubuntu

3.1 ROS Architecture

3.2 Create A ROS Feature Package

3.3 ROS Node

Chapter 3 The Fundamentals
of ROS

3.4 Learn about ROS Topics, ROS Services and Parameters 3.5 Use roslaunch 3.6 Create ROS Msg and Srv

3.7 Write A Simple Publisher and Subscriber in C++

3.8 Run Publishers and Subscribers

3.9 Write A Simple Service and Client In C++

Chapter 4 ROS Robotic Arm
Modeling
Chapter 5 Mirobot Robotic Arm Controls in
ROS

4.1 Introduction to URDF Models 4.2 3D Model Export URDF 4.3 Processing of URDF Files Exported by Mirobot Robotic Arm in Solidworks 5.1 Mirobot Communication Protocols 5.2 ROS and Mirobot Communication Implementation 6.1 Introduction to Moveit

Chapter 6 Controlling Mirobot with
Moveit

6.2 Moveit Configuration – Setup Assistant 6.3 Import Mirobot Model into Gazebo Simulation Environment 6.4 Use Moveit to Control Robotic Arm 6.5 Simulating Motion Using The Moveit Control Model (Python)

6.6 Controlling Really Robotic Arm Movements With Moveit (C++)

7.1 Recording and Playback of Robotic Arm Motion Data

7.2 Add an End Effector to Model

Chapter 7 Mirobot Feature
Expansion

7.3 Add A Camera to Model to Get Image Information 7.4 Add Kinect to Model to Get Point Cloud Information

7.5 Add A Force Transducer to The Model to Collect Simulation Data

7.6 Add Speech Recognition for Robotic Arms

Features
Source code, 3D models, courses PPT for educators, and supporting files of the experiments in the book are all include.
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Learning Robots with WLKATA Mirobot
Content Description
“Learning Robots with WLKATA Mirobot” focuses on K-12 STEM Education. It mainly covers fundamentals knowledge of robotics and practical experiment using Mirobot.

Course Catalog

Content

Chapter

Chapter 1

1.1 Introduction of WLKATA Mirobot

Introduction of Mirobot robot arm 1.2 The Use of WLKATA Studio

Chapter 2 What is Robot?

2.1 The Development History of Robots 2.2 Definition of Robot

Chapter 3 Robots of All Kinds

3.1 Classification by Application Field of Robot 3.2 Classification by Degree of Development of Robot 3.3 Classification by Robot Motion Form

Chapter 4 Move, Mirobot!

4.1 The Structure of Mirobot 4.2 Degree of Freedom 4.3 Move, Mirobot!

Chapter 5 The Position of the “Hand”

5.1 Cartesian Coordinate System 5.2 Coordinate Control Mode

Chapter 6 Signature of Mirobot

6.1 Locate The Drawing Plane 6.2 Signature of Mirobot

7.1 Drawing Interface

Chapter 7 Creative Painting

7.2 Menu Bar 7.3 Canvas

7.4 Toolbar

Chapter 8 Drawing Rectangles
Chapter 9 Drawing Magic Star
Chapter 10 Draw A Chessboard

8.1 Blockly 8.2 Draw A Rectangle 9.1 Task Overview 10.1 Program Structure 10.2 Draw Chessboard

Chapter 11 Forklift Driver

11.1 Teaching Mode 11.2 Coordinate System of The Tool 11.3 Forklift Driver

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Course Catalog
Content
Chapter 12 Excavator
Chapter 13 Palletizer
Chapter 14 Dominoes
Chapter 15 Bricklayer

12.1 Working Principle of Excavator 12.2 Excavation, Loading and Unloading 13.1 Gripper 13.2 Palletizing 14.1 Variables 14.2 Placing Dominoes 15.1 Pneumatic Kit 15.2 Brickwork

Chapter

12

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WLKATA Mirobot Robotic Arm Programming And Control

Content Description
“WLKATA Mirobot Robotic Arm Programming And Control” mainly covers the Kinematics Algorithm of 6-axis Manipulator with various control method including Blockly, Python Programming, ROS-Based Motion Control. The book also covers the SDK of the robot arm and develops robotic visual sorting in OpenCV.
Course Catalog

Content

Chapter

Chapter 1 Introduction to WLKATA Mirobot
Six-axis Robot Arm

1.1 Mechanical Structure of Manipulator 1.2 Electrical Principle of Manipulator 1.3 Technical Parameters of Manipulator

Chapter 2 Kinematics Algorithm of Six-axis
Manipulator

2.1 Spatial Description and Transformation 2.2 Forward Kinematics of Robot Arm 2.3 Inverse Kinematics of Robot Arm

3.1 Introduction of WLKATA Studio

3.2 Installation of WLKATA Studio

Chapter 3 Use of Mirobot 6-Axis Robot Arm

3.3 Robotic Arm Connection 3.4 Debugging of Robotic Arm

3.5 Robot Firmware Upgrade

3.6 Basic Control of The Robotic Arm

Chapter 4 “Teaching & Replay” Mode Of
Robotic Arm

4.1 The Introduction of Motion Modes 4.2 Use of “Teaching & Replay” Mode 4.3 Robotic Arm Move Blocks

Chapter 5 Blockly Programming Control Of
Robotic Arm

5.1 Introduction To WLKATA Studio Blockly Programming Instructions 5.2 Blockly Programming Application

Chapter 6 Python Programming Control Of
Robotic Arm

6.1 The Origin of Python 6.2 WLKATA Studio Python Programming Guide 6.3 Python Controlled Robotic Arm Palletizing

Chapter 7 Mirobot Motion Control Based On
ROS

7.1 ROS Introduction 7.2 The Principle of Communication Between Mirobot and ROS 7.3 Move End Effector via ROS(C++)

Chapter 8 SDK of Robot Arm

8.1 Introduction of API Functions 8.2 Application of Mirobot SDK

Chapter 9 Robotic Arm Control Based on OpenCV

9.1 Introduction to Visual Set 9.2 Camera Debugging and Image Processing 9.3 Visual Garbage Classification

13

Additional Set

14

WLkata AI Vision Set

15

Deep Learning Vision Set

17

Robot Arm Vehicle

19

WLkata Mirobot IOA Virtual Factory Set

21

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AI Vision Set
Product Description
AI Vision Set is a Python-based programming machine vision suite. Compared to the more complex Ubuntu-based machine vision, the AI vision suite is an entry- level machine vision product.
AI vision Set can achieve color recognition, contour recognition, picture recognition, digital recognition, QR code recognition, face recognition, etc. It can be combined with the Mirobot robotic arm to realize the automatic identification and grasping.

Selection Guide
| Product Name |
AI Vision Set AI Vision Set Cell
Experiment Content
No.
1 2 3 4 5 6 7 8 9 10 11 12 13

Model
WL-AC-ViMV-Re300 WL-EAS-AIViMV-Re300

What Is Included
AI Vision Set1 AI Vision Set1; Mirobot Education Kit1; WLkata Production Line Smart Base – S1

Experiment Content
Understanding of Robotic Arm Structure Understanding of Electrical Principles of Robotic Arm
Understanding of Robotic Arm D-H Parameters Understanding of Robotic Arm Coordinate Mode
Understanding of Robotic Arm End Effector Understanding of Electrical Parameters of Robotic Arm Understanding of Robotic Arm Basic Control Command
Understanding of Robotic Arm Movement Robot Arm Programming Control Logic Robotic Arm Application Development Fundamentals of Python Programming
Fundamentals of Robotics and Visual Communication Camera Calibration: Master Calibration Method of Visual Camera, Calculation Methods of Robot Coordinate System, and Visual Coordinate System

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Product Parameters

Product Name

Number of Axes Limit Loads Workspace Net Weight
Communication Interface
Base Dimensions

Mirobot Education Kit

Axis Motion Parameters (Load 160g)
Pen Holder Servo Gripper
Pneumatic Suction Cups
Three-finger Soft Gripper
Multifunctional Extender Box
Application

Camera Module

AI Vision Set Lens

Display Screen

6+1 600g 315mm 1.5Kg

Detailed Parameters

USB/Wi-Fi/Bluetooth/RS485

Diameter 160mm 1 axis: -110° ~ +160° maximum speed 85°/s 2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s 5-axis: -200° ~ +30° maximum speed 200°/s 6-axis: -360° ~ +360° maximum speed 450°/s Range: 7~10mm Range: 0~30mm Torque: 0.6 Kg/cm Suction Cup Diameter: 12mm Pressure: -60Kpa Range: 5~40mm Pressure: -60/120Kpa Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming Color: Colour Pixels: 640×480 Processor: ARM 32-bit Cortex-M7 CPU Operating Temperature: -20°C ~ +70°C Focal length: 1.2mm/3.6mm Aperture: F2.0 Installation Dimensions: M12*0.5 Screen Type: 1.8″TFT LCD Resolution: 160×128 Color: 64k RGB565

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Deep Learning Vision Set
Product Description
Deep Learning Vision Set is a Jetson Nano based machine learning vision set; using open-source deep learning framework PyTorch, and with cross platform computer vision library OpenCV.
It can be combined with Mirobot to realize AI functions such as target detection and image recognition.

Selection Guide

| Product Name |

Model

What Is Included

Deep Learning Vision Set WL-AC-MeCV-Re1080 Deep Learning Vision Set *1

Deep Learning Static Objects Sorting Set

WL-PL-AiGS-CV

Deep Learning Vision Set 1; Mirobot Education Kit1

Deep Learning Static Objects

Deep Learning Vision Set 1; Mirobot Education Kit1;

WL-EAS-MeCV-Re1080

Sorting Set Cell

WLkata Production Line Smart Base – S*1

Experiment Content

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Electrical Principles of Robotic Arm

3

Understanding of Robotic Arm D-H Parameters

4

Understanding of Robotic Arm Coordinate Mode

5

Understanding of Robotic Arm End Effector

6

Understanding of Electrical Parameters of Robotic Arm

7

Understanding of Robotic Arm Basic Control Command

8

Understanding of Robotic Arm Movement

9

Robot Arm Programming Control Logic

10

Robotic Arm Application Development

11

Fundamentals of Python Programming

12

Fundamentals of Robotics and Visual Communication

13

Camera Calibration: Master Calibration Method of Visual Camera, Calculation Methods of Robot Coordinate System, and Visual Coordinate System

14

Image Annotation and Dataset Creation

15

YoloV5 Model Training and Deployment

17

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Product Parameters

Product Name

Number of Axes Limit Loads Workspace Net Weight
Communication Interface
Base Dimensions

Mirobot Education Kit

Axis Motion Parameters (Load 160g)
Pen Holder Servo Gripper
Pneumatic Suction Cups
Three-finger Soft Gripper
Multifunctional Extender Box
Application

Camera Module

Deep Learning Vision Set

Controller

IPS Display

6+1 600g 315mm 1.5Kg

Detailed Parameters

USB/Wi-Fi/Bluetooth/RS485

Diameter 160mm 1 axis: -110° ~ +160° maximum speed 85°/s 2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s 5-axis: -200° ~ +30° maximum speed 200°/s 6-axis: -360° ~ +360° maximum speed 450°/s Range: 7~10mm Range: 0~30mm Torque: 0.6 Kg/cm Suction Cup Diameter: 12mm Pressure: -60Kpa Range: 5~40mm Pressure: -60/120Kpa Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming Color: Colour Resolution: 2952×1944 Supply voltage: 3.6V~5V Operating Temperature: -20°C ~ +70°C Adjustable Parameters: brightness, contrast, hue, saturation, sharpness, white balance, exposure value CPU: Quad-core ARM -A57@1.43GHz GPU: 128-core Maxwell Video Encoder: 4K @ 30 | 4 x 1080p @ 30 Interfaces: 4USB3.0, USB 2.0 Micro-B, HDMI, DP Resolution: 1024600 Interfaces: HDMI, AV, VGA Size: B701-GM 7 inch

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Robot Arm Vehicle

Product Description
WLkata Robot Arm Vehicle – The AGV Mecanum mobile base, which can be equipped with a robotic arm, expands the application scenarios of the robotic arm. AGV Mecanum omnidirectional mobile vehicle is compatible with maker creations and has rich sensing features. It support Bluetooth, Wi-Fi connection mode and secondary development.

Selection Guide

| Product Name |
Wlkata Vehicle Base Wlkata Robot Vehicle In One

Model
WL-AC-Mac-55MM WL-EA-Mac-55ReMM

What Is Included
Wlkata Mecanum Vehicle Base1 Wlkata Mecanum Vehicle Base1; Mirobot Vehicle Version*1

Experiment Content
No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Experiment Content
Understanding of Robotic Arm Structure Understanding of Electrical Principles of Robotic Arm
Understanding of Robotic Arm D-H Parameters Understanding of Robotic Arm Coordinate Mode
Understanding of Robotic Arm End Effector Understanding of Electrical Parameters of Robotic Arm Understanding of Robotic Arm Basic Control Command
Understanding of Robotic Arm Movement Robot Arm Programming Control Logic Robotic Arm Application Development
Omnidirectional Mobile Car Line Follower Algorithm Omnidirectional Mobile Car Movement Principle Robotic Arm Communicates With Base
Fundamentals of Arduino Microcontroller Programming Mobile Robotic Arm Automatic Grasping

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Product Parameters

Product Name

Detailed Parameters

Number of Axes

6+1

Limit Loads

600g

Workspace

315mm

Net Weight

1.5Kg

Communication Interface

USB/Wi-Fi/Bluetooth/RS485

Base Dimensions

Diameter 160mm

1 axis: -110° ~ +160° maximum speed 85°/s

Axis Motion Parameters (Load 160g)

2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s

5-axis: -200° ~ +30° maximum speed 200°/s

6-axis: -360° ~ +360° maximum speed 450°/s

Mirobot Vehicle Version

Pen Holder Servo Gripper

Range: 7~10mm Range: 0~30mm Torque: 0.6 Kg/cm

Pneumatic Suction Cups

Suction Cup Diameter: 12mm Pressure: -60Kpa

Three-finger Soft Gripper

Range: 5~40mm Pressure: -60/120Kpa

Multifunctional Extender Box

Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED

Image Sensor: OV2640 (2.0 Megapixel Camera)

Camera Module

Processor: Kendryte K210 Display: 2.0-inch IPS screen with 320*240 resolution

Supply Voltage: 3.3~5.0V

Application

WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming

Controller

ATMega 2560

Product Size

290mmx220mmx90mm

Net Weight

3.5Kg

WLkata Robot Arm Vehicle

Limit Load Battery Capacity Operating Voltage

10Kg 8000mAh 12V

Control Method

APP, PS2 Controller

Wheel Diameter

3 inch

Rated Speed

105rpm

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IOA Virtual Factory

Product Description
Mirobot IOA Virtual Factory Set –IOA Virtual Factory Software combined with Mirobot can achieve 1:1 virtualization simulation, provides custom drag-and- drop for robot workstation production line design; 1:1 digital twin control simulation; includes physical workstation to realize real life simulation application of smart factory.
IOA Virtual Factory Software supports the establishment of student learning management systems to facilitate learning progress tracking and grading.
Selection Guide

| Product Name |
IOA Virtual Factory Software Mirobot IOA Virtual Factory Set

Model
WL-AC-IOA-3D WL-MiroIOA-6R200-3D

What Is Included
IOA Virtual Factory Software1 IOA Virtual Factory Software1; Mirobot Professional Kit*1

Experiment Content

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Electrical Principles of Robotic Arm

3

Understanding of Robotic Arm D-H Parameters

4

Understanding of Robotic Arm Coordinate Mode

5

Understanding of Robotic Arm End Effector

6

Understanding of Electrical Parameters of Robotic Arm

7

Understanding of Robotic Arm Basic Control Command

8

Understanding of Robotic Arm Movement

9

Robot Arm Programming Control Logic

10

Robotic Arm Application Development

11

Smart Factory Structure Design and Construction

12

IOA Virtual Electrical Wiring

13

Industrial Robot Integration and Programming Simulation

14

IOA Intelligent Control Integration and Simulation

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Product Parameters
Product Name
Number of Axes Limit Loads Workspace Net Weight
Communication Interface
Base Dimensions

Axis Motion Parameters (Load 160g)

Mirobot Professional Kit

Pen Holder
Servo Gripper
Pneumatic Suction Cups
Three-finger Soft Gripper

Multifunctional Extender Box

Bluetooth Teach Pendant
Application

6+1 600g 315mm 1.5Kg

Detailed Parameters

USB/Wi-Fi/Bluetooth/RS485

Diameter 160mm 1 axis: -110° ~ +160° maximum speed 85°/s 2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s 5-axis: -200° ~ +30° maximum speed 200°/s 6-axis: -360° ~ +360° maximum speed 450°/s Range: 7~10mm Range: 0~30mm Torque: 0.6 Kg/cm Suction Cup Diameter: 12mm Pressure: -60Kpa Range: 5~40mm Pressure: -60/120Kpa Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED Connection: Bluetooth Function: Angle/Coordinate control of the robotic arm, supports point teaching control WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming

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Product Parameters
Product Name
Digital Twin System
Virtual Electrical Wiring
Virtual Teaching Programming

IOA Virtual Factory Software

Virtual Controller XR Virtual Simulation
Virtual Simulation

Virtual Control
Integrated Control Simulation

Detailed Parameters
Include robot model library, logistics model library, sensor library, electromechanical control library, and mechanical library
Support robot controller virtual electrical IO wiring, support Excel electrical wiring table exporting
Realize virtual teach-in programming of robots and support a variety of virtual teach-in programming of industrial robots, including NRT motion control system, Eft Robox teach pendant, AUBO robot teach pendant, etc.
A variety of virtual controllers, including Siemens S7-1200, S7-1500 series PLC, Mitsubishi PLC, ZMC308 motion controller, VPLC machine vision controller, Python virtual controller, etc.
Support multi-user collaborative software for mobile APP, VR, and AR virtual simulation
Include Virtual robot controller and 3D robot body, implement virtual teaching programming and integrated control
Support 1:1 access of real robots to realize twin control simulation of virtual 3D and real robots
Support the combination of PLC motion controller to achieve multi-robot system integration control simulation

23

Comprehensive Teaching And

Training Platform

24

Fruit Picking Line

25

Logistic Warehousing Sorting Line

26

AI Static Garbage Sorting Production Line

28

AI Automatic Sorting Production Line

29

Automobile Assembly Line

30

Deep Learning Moving Garbage Sorting Line

31

Robotics Integrated Training Station

32

Chess Manufacturing Line

35

Automotive Manufacturing Simulation Line

36

24

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Fruit Picking Line

Product Description
At present, many national research institutes and universities are conducting research on agricultural harvesting. The fruit picking production line mainly combines the small industrial prototype 6-axis desktop robot arm and color recognition module and realizes the fruit picking and sorting process through the mechanical arm picking and sensor recognition.
This set of production lines mainly cultivates the application thinking of robot and sensor technology in the field of agriculture and provides support for learning and research in the field of smart agriculture.

Selection Guide

Product Name
WLkata Mirobot Fruit Picking Line
WLkata Mirobot Fruit Picking Line Cell
Experiment Content

Model
WL-PL-FP-RGB3 WL-PL-EAS-FP-RGB3

What Is Included
Mirobot Education Kit1; Accessory Package of Wlkata Mirobot Fruit Picking Line1 Mirobot Education Kit1; Accessory Package of Wlkata Mirobot Fruit Picking Line1; WLkata Production Line Smart Base – S*1

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Electrical Principles of Robotic Arm

3

Understanding of Robotic Arm D-H Parameters

4

Understanding of Robotic Arm Coordinate Mode

5

Understanding of Robotic Arm End Effector

6

Understanding of Electrical Parameters of Robotic Arm

7

Understanding of Robotic Arm Basic Control Command

8

Understanding of Robotic Arm Movement

9

Robot Arm Programming Control Logic

10

Robotic Arm Application Development

11

Principles of Color Sensor Technology

12

Robot Communication with Microcontroller

25

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Logistic Warehousing Sorting Line

Product Description
Logistic Warehousing Sorting Line simulates the intelligent logistics scenario of the whole process of warehouse including loading, palletizing, loading, etc. This scenario teaches the programming control of the Mirobot robotic arm and multi-device collaboration. The palletizing robotic arm places the goods on the shelves on the pallet, and then the conveyor belt transports the goods to the workstation of the 3-axis handling robotic arm. After that, the handling robotic arm transports the goods to the front of the shelf, and the palletizing robotic arm places the goods back on the shelves.
The production line simulates the intelligent logistics warehousing system of the demonstration industry through the cycle of the above steps.
Selection Guide

Product Name
WLkata Mirobot Logistic Warehousing Sorting Line
Wlkata Mirobot Logistic Warehousing Sorting Line Cell
Experiment Content

Model
WL-PL-LW-Miro1 WL-PL-EAM-LW-Miro1

What Is Included
Mirobot Education Kit1; 3-Axis Robotic Arm1; Conveyor Belt Set1; Accessory Package of Wlkata Mirobot Logistic Warehousing Sorting Line1 Mirobot Education Kit1; 3-Axis Robotic Arm1; Conveyor Belt Set1; Accessory Package of Wlkata Mirobot Logistic Warehousing Sorting Line1; WLkata Production Line Smart Base – M*1

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Robotic Arm D-H Parameters

3

Understanding of Robotic Arm Coordinate Mode

4

Understanding of Robotic Arm End Effector

5

Understanding of Electrical Parameters of Robotic Arm

6

Understanding of Robotic Arm Basic Control Command

7

Understanding of Robotic Arm Movement

8

Robot Arm Programming Control Logic

9

Robotic Arm Application Development

10

3-axis Robotic Arm Programming and Control

11

Conveyor Belt Programming and Control

12

Principles of Photoelectric Sensor Technology

13

Fundamentals of Multi-device Collaborative Communication

26

®

Product Parameters

Product Name

Number of Axes Limit Loads Workspace Net Weight
Communication Interface
Base Dimensions

Mirobot Education Kit

Axis Motion Parameters (Load 160g)
Pen Holder
Servo Gripper
Pneumatic Suction Cups Three-finger Soft
Gripper

Multifunctional Extender Box

Application

Controller

Number of Axes

Limit Loads

Workspace

Net Weight

WLkata 3-Axis Robotic Arm

Interface

Base Dimensions

Axis Parameters

Application

6+1 600g 315mm 1.5Kg

Detailed Parameters

USB/Wi-Fi/Bluetooth/RS485

Diameter 160mm 1 axis: -110° ~ +160° maximum speed 85°/s 2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s 5-axis: -200° ~ +30° maximum speed 200°/s 6-axis: -360° ~ +360° maximum speed 450°/s Range: 7~10mm Range: 0~30mm Torque: 0.6 Kg/cm Suction Cup Diameter: 12mm Pressure: -60Kpa Range: 5~40mm Pressure: -60/120Kpa Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming Desktop-grade robotic arm based on the ATMega 2560 open-source hardware chip 3 500g 320mm 2.85Kg USBWiFiBluetoothRS485 158mm x 158mm 1 Axis: -195° ~ +135° 2 Axis: -20° ~ +90° Maximum speed 60°/s 3 Axis: 0° ~ +90° Maximum speed 65°/s Studio, Grblcontroller 3.6, Blockly graphical interface programming

27

®
AI Static Garbage Sorting Production Line

Product Description

WLkata AI Static Garbage Sorting Production Line combines Mirobot robotic arm and AI vision suite to realize different types of garbage identification and robotic arm sorting tasks. Students can improve Python programming, robotic arm programming and collaborative work by completing the entire workflow of the production line. The AI Vision Set can also realize more visual recognition functions such as shape or code scanning to build more complex logistics and automation scenarios by adding conveyor belt and sliding rail sets.
Selection Guide

Product Name
WLkata Mirobot AI Static Garbage Sorting Production Line
WLkata Mirobot AI Static Garbage Sorting Production Line Cell
Experiment Content

Model

What Is Included

WL-PL-GS-RGB3 WL-PL-EAM-GS-RGB3

Mirobot Education Kit2; AI Vision Set1; Accessory Package of Wlkata Mirobot AI Static Garbage Sorting Production Line1
Mirobot Education Kit2; AI Vision Set1; Accessory Package of Wlkata Mirobot AI Static Garbage Sorting Production Line1; WLkata Production Line Smart Base – M*1

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Electrical Principles of Robotic Arm

3

Understanding of Robotic Arm D-H Parameters

4

Understanding of Robotic Arm Coordinate Mode

5

Understanding of Robotic Arm End Effector

6

Understanding of Electrical Parameters of Robotic Arm

7

Understanding of Robotic Arm Basic Control Command

8

Understanding of Robotic Arm Movement

9

Robot Arm Programming Control Logic

10

Robotic Arm Application Development

28

®
AI Automatic Sorting Production Line

Product Description
AI Automatic Sorting Production Line is composed of AI vision Set, robotic arm, transmission unit, and sensor unit. The target object is dynamically identified. The vision set performs sorting tasks with the robotic arm, enabling the robotic arm intelligent sorting. The production line improves students’ practical ability to build systems during experiments. The identification type can be changed to create more complex application scenarios and improve the ability of innovation and development.
Selection Guide

Product Name
WLkata Mirobot AI Automatic Sorting Production Line
WLkata Mirobot AI Automatic Sorting Production Line Cell
Experiment Content

Model
WL-PL-AiGS-RGB3 WL-PL-EAM-AiGS-RGB3

What Is Included
Mirobot Education Kit2; AI Vision Set1; Conveyor Belt Set1; Accessory Package of Wlkata Mirobot AI Automatic Sorting Production Line1 Mirobot Education Kit2; AI Vision Set1; Conveyor Belt Set1; Accessory Package of Wlkata Mirobot AI Automatic Sorting Production Line1; WLkata Production Line Smart Base – M*1

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Robotic Arm D-H Parameters

3

Understanding of Robotic Arm Coordinate Mode

4

Understanding of Robotic Arm End Effector

5

Understanding of Electrical Parameters of Robotic Arm

6

Understanding of Robotic Arm Basic Control Command

7

Understanding of Robotic Arm Movement

8

Robot Arm Programming Control Logic

9

Robotic Arm Application Development

10

Fundamentals of Multi-device Collaborative Communication

11

Fundamentals of Python Programming

12

Fundamentals of Robotics and Visual Communication

13

Camera Calibration: Master Calibration Method of Visual Camera, Calculation Methods of Robot Coordinate System, and Visual Coordinate System

29

®
Automobile Assembly Line

Product Description
Industrial robots are most widely used in the automotive manufacturing industry. The smart factory for automobile production integrates a variety of artificial intelligence technologies such as intelligent control and sensors. The production line based on the real car production scene, vividly showing the car assembly, welding, assembly, and other processes.
Automobile Assembly Line is an effective combination of man and machine, and fully reflects the flexibility of the equipment. It combines conveyor systems, accompanying end-effectors, and measuring equipment to meet the assembly requirements of auto parts.
Selection Guide

Product Name
Wlkata Mirobot Automobile Assembly Line
Wlkata Mirobot Automobile Assembly Line Cell
Experiment Content

Model
WL-PL-Aa-Tec3 WL-PL-EAM-Aa-Tec3

What Is Included
Mirobot Education Kit3; Sliding Rail Accessory Set1; Accessory Package of Wlkata Mirobot Automobile Assembly Line1 Mirobot Education Kit3; Sliding Rail Accessory Set1; Accessory Package of Wlkata Mirobot Automobile Assembly Line1; WLkata Production Line Smart Base – M*1

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Electrical Principles of Robotic Arm

3

Understanding of Robotic Arm D-H Parameters

4

Understanding of Robotic Arm Coordinate Mode

5

Understanding of Robotic Arm End Effector

6

Understanding of Electrical Parameters of Robotic Arm

7

Understanding of Robotic Arm Basic Control Command

8

Understanding of Robotic Arm Movement

9

Robot Arm Programming Control Logic

10

Robotic Arm Application Development

11

Linear Guide Program Control

12

Automobile Assembly and Welding Process Simulation

13

Multi-device Collaborative Programming Control

30

®
Deep Learning Moving Garbage Sorting Line

Product Description
WLkata Deep Learning Moving Garbage Sorting Line is a sorting system based on Jetson Nano’s multifunctional AI chip and 6-axis intelligent robotic arm. It adopts the open-source deep learning framework PyTorch with the cross-border platform computer vision library OpenCV. It also has AI functions such as object detection and image recognition and can be combined with conveyor belts to achieve intelligent garbage classification.
Selection Guide

Product Name

Model

What Is Included

Wlkata Mirobot Deep Learning Moving Garbage Sorting Line
WLkata Mirobot Deep Learning Moving Garbage Sorting Line Cell
Experiment Content

WL-PL-AiGSM-CV

Mirobot Education Kit2; Deep Learning Vision Set 1; Conveyor Belt Set1; Accessory Package of Wlkata Mirobot Deep Learning Moving Garbage Sorting Line1

Mirobot Education Kit2; Deep Learning Vision Set 1; Conveyor Belt Set*1;

WL-PL-EAM-AiGSM-CV

Accessory Package of Wlkata Mirobot Deep Learning Moving Garbage Sorting Line*1;

WLkata Production Line Smart Base – M*1

No.

Experiment Content

1

Understanding of Robotic Arm Structure

2

Understanding of Robotic Arm D-H Parameters

3

Understanding of Robotic Arm Coordinate Mode

4

Understanding of Robotic Arm End Effector

5

Understanding of Robotic Arm Basic Control Command

6

Robot Arm Programming Control Logic

7

Robotic Arm Application Development

8

Fundamentals of Python Programming

9

Fundamentals of Robotics and Visual Communication

10

Camera Calibration: Master Calibration Method of Visual Camera, Calculation Methods of Robot Coordinate System, and Visual Coordinate System

11

Image Annotation and Dataset Creation

12

YoloV5 Model Training and Deployment

31

®
Robotics Integrated Training Station

Product Description
WIOA Robotics Integrated Training Station includes machine vision control system, machine vision simulation system, sixaxis robot, industrial computer system and 3D digital twin system. The platform is composed of modular methods and is supported by digital display boards and training platforms which forms a practical training simulation platform for advanced integration and comprehensive application of robots.
Selection Guide

Product Name
WLkata WIOA Robotics 3-in-1 Training Station
Experiment Content

Model
WL-PL-Mevision-3D

What Is Included
Mirobot Education Kit1; WIOA Machine Vision Set1; Training Station System 1; IOA Virtual Factory Software1; Training Station Accessory Package1; User Manual and Study With Cases1

No.

Experiment Content

1

Understanding of Robotic Arm Structure and Electrical Principles

2

Understanding of Robotic Arm D-H Parameters

3

Understanding of Robotic Arm Coordinate Mode

4

Understanding of Robotic Arm End Effector

5

Understanding of Electrical Parameters of Robotic Arm

6

Robot Arm Programming Control Logic

7

Basic Applications for Machine Vision and Automatic Control

8

Visual Simulation and Automation Integration

9

Position Recognition and Grasping Automation Based WLKATA 6-axis Robotic Arm

10

Integration of Vision Applications for Mirobot 6-axis Robotic Arm

14

Extended Applications for Machine Vision and Industrial Intelligence

32

®

Product Parameters

Product Name
Mirobot Education Kit
IOA Virtual Factory Software

Number of Axes Limit Loads Workspace Net Weight
Communication Interface
Base Dimensions
Axis Motion Parameters (Load 160g)
Pen Holder
Servo Gripper
Pneumatic Suction Cups
Three-finger Soft Gripper
Multifunctional Extender Box
Application Digital Twin System
Virtual Electrical Wiring
Virtual Teaching Programming
Virtual Controller
XR Virtual Simulation Virtual Simulation
Virtual Control Integrated Control
Simulation

6+1 600g 315mm 1.5Kg

Detailed Parameters

USB/Wi-Fi/Bluetooth/RS485

Diameter 160mm
1 axis: -110° ~ +160° maximum speed 85°/s 2-axis: -35° ~ +70° maximum speed 60°/s 3-axis: -120° ~ +60° maximum speed 65°/s 4-axis: -180° ~ +180° maximum speed 200°/s 5-axis: -200° ~ +30° maximum speed 200°/s 6-axis: -360° ~ +360° maximum speed 450°/s Range: 7~10mm
Range: 0~30mm
Torque: 0.6 Kg/cm
Suction Cup Diameter: 12mm
Pressure: -60Kpa
Range: 5~40mm
Pressure: -60/120Kpa
Chip: Xtensa® 32-bit LX6 Single-Core Processor 168MHz Operating Temperature: 5~45 Screen Size: 1.3 inch OLED
WLKATA Studio, Grblcontroller3.6, Blockly Graphical Programming
Include robot model library, logistics model library, sensor library, electromechanical control library, and mechanical library
Support robot controller virtual electrical IO wiring, support Excel electrical wiring table exporting
Realize virtual teach-in programming of robots and support a variety of virtual teach-in programming of industrial robots, including NRT motion control system, Eft Robox teach pendant, AUBO robot teach pendant, etc.
A variety of virtual controllers, including Siemens S7-1200, S7-1500 series PLC, Mitsubishi PLC, ZMC308 motion controller, VPLC machine vision controller, Python virtual controller, etc.
Support multi-user collaborative software for mobile APP, VR, and AR virtual simulation
Include Virtual robot controller and 3D robot body, implement virtual teaching programming and integrated control
Support 1:1 access of real robots to realize twin control simulation of virtual 3D and real robots
Support the combination of PLC motion controller to achieve multi-robot system integration control simulation

33

®

Product Parameters

Product Name
WIOA Machine Vision Set

camera Visual light source
Stand Accessory
system
interface

Deep learning framework

Training Station System

CPU parameters
GPU parameters
memory power supply LCD touchscreen Driver installation
package

Detailed Parameters
Color camera, 300 color CMOS image pixels, configurable focus lens
Equipped with a visual ring light source, adjustable light source power adapter
Adjustable aluminum alloy bracket, height 450mm, angle, adjustable height
Configure manual fixing brackets, light source fixing brackets, and manual adjustment nut accessories
Pre-installed with the Linux operating system and embedded deep learning framework Tengine, supports Andriod 8.1
Equipped with USB, HDMI, RJ45, Wi-Fi, BT, MIPI, eDP and other conventional interfaces, supports rich embedded expansion interfaces as GPIO, I2C, SPI, and TT
Supports direct deployment of training framework models such as Caffe/TensorFlow/Pytorch/MxNet/ONNX/Darknet Supports network performance optimization strategies such as layer fusion and quantization, provides a unified API (C/Python/JNI) interface Provides custom operators for extended interfaces
RK3399, 2xA72@1.8GHz+4xA53@1.4GHz
Mali-T860MP4, supports OpenGL ES1.1/2.0/3.0/3.1, OpenVG1.1, OpenCL, DX11, AFBC (Frame Buffer Compression)
LPDDR3 4GB
Input 100VAC~240VAC, 50Hz; Output 12VDC, 2A
5.5-inch touchscreen, MIPI interface, resolution 1280 * 720
Machine vision control case drive package includes virtual simulation machine vision API and machine vision training API development package

User Manual and Study With Cases

Machine vision complete development manual, including IO driver, image import, contour extraction, QR code recognition, image training and other videos together with training case development packages; 3D Virtual Simulation Development Kit, can links with the vision controller through virtual 3D robot system to achieve digital twin simulation resource packs including garbage sorting, logistics sorting, shape matching, etc.

34

®
Chess Manufacturing Line

Product Description
Chess Manufacturing Line completely present the application of robots in intelligent manufacturing. The complete production line includes a chess raw material unit, a laser engraving production unit, a Mirobot robotic arm handling unit, a conveyor belt handling unit, and an assembly and storage unit. In actual intelligent manufacturing, the whole set of solutions adopts integrated control and the form of project functional unitization. The integrated control ensures that the production scheme is smooth and functional unitization facilitates production commissioning.
Extended Application: Industrial customization of as bookmarks and business cards production can be realized by changing the production process.

Selection Guide
Product Name
Wlkata Chess Manufacturing Line
Experiment Content

Model
WL-PL-CM-CD24

What Is Included
Mirobot Education Kit4; 3-Axis Robotic Arm1; AI Vision Set1; Conveyor Belt Set1; Engraving Machine1; Accessory Package1 Chess Manufacturing Line Base*1

No.

Experiment Content

1

Understanding of Intelligent Manufacturing System

2

Understanding of Robot System

3

Understanding of Robotic Arm D-H Parameters

4

Understanding of Robotic Arm Movement

5

Understanding of Robotic Arm End Effector

6

Understanding of Robotic Arm Coordinate Mode

7

Understanding of Mobile Robots

8

Sensor Connection

9

Fundamentals of Configuration Software Custom Programming

10

Fundamentals of Python Programming

11

Camera Calibration: Master Calibration Method of Visual Camera, Calculation Methods of Robot Coordinate System, and Visual Coordinate System

12

Understanding of Automotive Automated Production System

13

CNC Machining Process

14

Automated Packaging Process

35

®
Automotive Manufacturing Simulation Line

Product Description
In order to better realize industrial flexible production and restore the automatic production process flow of “assembly, welding, solder joint detection, grinding” in the automobile production process and form a complete set of automobile production line production program, the production line is based on unit equipment. At the same time, real-time integrated control, visual inspection, data collection and processing are carried out, and feedback is obtained through visual inspection and data backhaul of the node. It is dispatched by the master and assigned to AGVs for retrieval or repair. The code can be stored in the multi-function control box through WLKATA Studio, which is convenient for students to modify according to the scene, and provides a safe, open and friendly platform for students to learn robot programming and control and intelligent manufacturing system engineering.
Selection Guide

Product Name
WLKATA Mirobot Automotive Manufacturing Simulation Production Line
Experiment Content
No.
1 2 3 4 5 6 7 8 9 10
11
12 13 14 15

Model
WL-PL-AS-Tec5

What Is Included
Mirobot Education Kit5; Wlkata Robot Vehicle In One2; Short Conveyor Belt5; AI Vision Set1; Display Screen1; Accessory Package1

Experiment Content
Understanding of Intelligent Manufacturing System Understanding of Robot System
Understanding of Robotic Arm D-H Parameters Understanding of Robotic Arm Movement Understanding of Robotic Arm End Effector
Understanding of Robotic Arm Coordinate Mode Understanding of Mobile Robots Sensor Connection
Fundamentals of Configuration Software Custom Programming Fundamentals of Python Programming
Camera Calibration: Master Calibration Method of Visual Camera, Calculation Methods of Robot Coordinate System, and Visual Coordinate System
Understanding of Automotive Automated Production System Mobile Car Movement and Control Principle Mobile Robotic Arm Automatic Grasping
Integration of Robotics, Vision, Sensor Technology Applications
36

®
Production Process

9
Process Description:

2

1

1. The robotic arm sends the car model from the supply shelf (1) to the conveyor unit and enters the production line;

2. Car model goes through the conveyor unit (2), (3), (4), (5), (6)

to complete the assembly, welding, solder joint testing, grinding

and other processes;

3. AGV mobile robots transport the good/defective products

from (6) to (7) and (8) shelf;

4. Roof material is removed and replenished from (9) by AGV

mobile robots to (10).

5

Scenario Description:

1. Each process can be tested independently as an experimental

project;

6

2. There is a three-color indicator light indication in the operation

of the process;

3. The production line supports WIFI, 5G, edge computing

8

research and development.

37

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Robotics Training Solution For AI and IoT Education

Professional ·

Safe · Desktop

®
A Global Provider of AI and IoT Education Solution
www.wlkata.com

WLKATA Robotics

USA Office:
Wristline Inc. 140 Route 17 North Suite 313,Paramus, NJ USA 07652 Phone: +1 201 682 9753 WhatsApp: +1 201 682 9753 hello@wristline.com

China Office:
Room 1603, Zhongguancun Energy & Security Science Park,Building 3, Qinghua East Road 16, Haidian District, Beijing, China. Landline: +86-10-82363060 Phone +86-186 1150 3201 wlkata_service@tsinew.com

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