WLKATA Mirobot 6DoF Mini Industrial Robotic Arm User Manual
- June 9, 2024
- WLKATA
Table of Contents
Mirobot 6DoF Mini Industrial Robotic Arm
®
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
3
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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.
4
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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.
5
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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
6
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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
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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.
10
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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
11
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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
14
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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
16
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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
18
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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
19
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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
20
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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
21
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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
22
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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
®
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