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DOFBOT SE📖
1.First Trial
  • 1.First Trial
  • 2.Analysis of common problems
  • 3.Calibration offset
  • 4.Precautions for DIY Robotic Arm
  • 5.Robotic arm gripping anomaly solutions
2.Assembly Course
  • 1.Installation video
  • 2.Calibrate the Robotic Arm
  • 3.Install the map
3.Remote Control Course
  • 1.Mobile APP control
  • 2.USB handle control
  • 3.PC software control
4.Preparation
  • 1.Manage APP control service
  • 2.Manage JupyterLab service
  • 3.Write STM32 firmware
  • 4.Introduction to expansion board
5.Basic Control Course
  • 1.Control RGB light
  • 2.Control buzzer
  • 3.Control single servo
  • 4.Read servo angle
  • 5.Control all servo
  • 6.DOFBOT up down left right
  • 7.DOFBOT dancing
  • 8.DOFBOT memory action
  • 9.DOFBOT grab block
  • 10.Porter
  • 11.Stack block
  • 12.USB camera display
  • 13.Synchronous action
6.AI Vision Basic Course
  • 1.Gesture Recognition
  • 2.Color threshold adjustment Color calibration
  • 3.Color recognition
  • 4.Face recognition
  • 5.Garbage recognition
  • 6.Yolo object recognition
  • 7.Real-time web view
7.2D Visual Tracking Course
  • 1.PID algorithm basics
  • 2.Color block positioning
  • 3.Color block tracking
  • 4.Face positioning
  • 5.Face tracking
  • 6.Gesture recognition fixed action
8.2D Visual Grasping Course
  • 0.Visual positioning
  • 1.Gesture recognition stack blocks
  • 2.Color recognition grab blocks
  • 3.Catch game
  • 4.Color sorting and stacking
  • 5.Garbage sorting
  • 6.Color interaction
9.2D Mediapipe Course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall inspection
  • 4.Face detection
  • 5.Face recognition
  • 6.Face effects
  • 7.3D object recognition
  • 8.Paintbrush
  • 9.Finger control
  • 10.Gesture recognition
  • 11.Gesture control robotic arm action group
  • 12.Arm posture control robotic arm
  • 13.Palm Targeting
  • 14.Robotic arm tracks the palm
  • 15.Fingertip trajectory recognition
  • 16.Fingertip trajectory control robotic arm
  • 17.Gesture Grasp and Release Objects
  • 18.Finger Control Robot Arm
10.AI Large Model Voice Module (Must Read)
  • 1. Introduction to AI Large Model Voice Module
  • 2. Flash the firmware (Must read)
  • 3. Modify the wake-up word and command word
11.2D Voice Control Course
  • 1.Simple Voice Control
  • 2.Smart Voice Control
  • 3.Voice Action Control
  • 4.Memory Learning Mode
  • 5.Color Recognition with Voice Broadcast
  • 6.Color Recognition and Grasping with Voice Broadcast
  • 7.Color Recognition and Sorting with Voice Broadcast
  • 8.Voice Recognition Target Tracking
  • 9.Voice Control Stacking
  • 10.Voice Control Color Sorting
  • 11.Garbage Recognition with Voice Broadcast
  • 12.Garbage Sorting with Voice Broadcast
12.Robotic Arm Control and Inverse Kinematics
  • 1. Robotic arm ROS control
  • 2. Inverse solution
13.3D Sorting and Grasping Course
  • 1.AprilTag ID sorting
  • 2.MediaPipe Gesture-AprilTag ID sorting
  • 3.MediaPipe Gesture-AprilTag distance sorting
  • 4.Block color sorting
  • 5.Block different shape sorting
  • 6.Yolov11 garbage sorting
14.3D Tracking Course
  • 1.AprilTag Tracking
  • 2.Color Block Tracking
  • 3.KCF Object Tracking
15.3D Voice Control for Sorting & Tracking Course
  • 1.Voice Control AprilTag ID Sorting
  • 2.Voice Control Color Block Sorting
  • 3.Voice Control Yolov11 Garbage Recognition Sorting
  • 4.Voice Control AprilTag Tracking
  • 5.Voice Control Color Block Tracking
  • 6.Voice Control Object Tracking
16.AI Model Basics
  • 1.AI large model types and principles
  • 2.RAG retrieval enhancement and model training samples
  • 3.Embodied intelligent robot system architecture
  • 4.Embodied intelligent functions core source code
17.AI Model Development
  • 1. Register a model service provider account
  • 2. Configure API-KEY
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. AI Large Model Development - chatbot
  • 6. Deploy the RAG knowledge base
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
18.AI Model – Text Version
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Text Large Model + robotic arm control
  • 4.Multimodal Large Model+video understanding
  • 5.Multimodal Large Model+robotic arm gripping
  • 6.Multimodal Large Model+robotic arm tracking
  • 7.Multimodal Large Model+robotic arm sorting
  • 8.Multimodal Large Model+robotic arm handling
  • 9.Multimodal Large Model+Color Blocks Back In Place
  • 10.Multimodal Large Model + Intent Prediction + Robotic Arm Gripping
  • 11.Text Large Model + YOLOv11 + Intelligent Garbage Classification
19.AI Model – Voice Version
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Text Large Model + robotic arm control
  • 4.Multimodal Large Model+video understanding
  • 5.Multimodal Large Model+robotic arm gripping
  • 6.Multimodal Large Model+robotic arm tracking
  • 7.Multimodal Large Model+robotic arm sorting
  • 8.Multimodal Large Model+robotic arm handling
  • 9.Multimodal Large Model+Color Blocks Back In Place
  • 10.Multimodal Large Model + Intent Prediction + Robotic Arm Gripping
  • 11.Text Large Model + YOLOv11 + Intelligent Garbage Classification
20.AI Model – Fun Applications
  • 1.AI Butler-Intent Inference
  • 2.AI Encyclopedia-Arithmetic Master
  • 3.AI Encyclopedia-You asked I Pointed
  • 4.AI Encyclopedia-Nutritional Analysis
  • 5.AI Encyclopedia-Problem Solving Expert
  • 6.AI Encyclopedia-English Spelling
  • 7.AI Butler-Garbage Sorting
  • 8.AI Top Chef
21.MoveIt2 Course
  • 1. MoveIt Configuration
  • 2. MoveIt Usage
  • 3. MoveIt Drive Real Robot
  • 4. MoveIt Random Movement
  • 5. MoveIt Forward Kinematics Design
  • 6. MoveIt Inverse Kinematics Design
  • 7. MoveIt Cartesian Path
  • 8. MoveIt Scene Design
  • 9. MoveIt Trajectory Planning
  • 10. MoveIt Collision Detection
22.YOLOv11 Development Course
  • 1. YOLO Environment Setup
  • 2. CLI Usage
  • 3. Object Detection
  • 4. Instance Segmentation
  • 5. Pose Estimation
  • 6. Image Classification
  • 7. Oriented Bounding Boxes Object Detection
  • 8. Model Conversion
  • 9. Model Prediction
23. Linux Operating System
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
24.OpenCV Course
  • 1.Introduction to Open Source CV
  • 2.Image reading and display
  • 3.Picture writing
  • 4.Image Quality
  • 5.Pixel operations
  • 6.Image zoom
  • 7.Picture cut
  • 8.Picture pan
  • 9.Picture mirroring
  • 10.Affine transformation
  • 11.Picture rotation
  • 12.perspective transformation
  • 13.Grayscale processing
  • 14.Binary image
  • 15.Edge green detection
  • 16.Line segment drawing
  • 17.Rectangular circle drawing
  • 18.Text and picture drawing
25.Advanced Visuals Course
  • 1. QR Code
  • 2. Human Pose Estimation
  • 3. Object Detection
  • 4. AR Vision
  • 5. ROS + OpenCV Basics
26.ROS2 Basic Course
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
27.Jupyter Lab Usage Course
  • 0.Read the document before operation
  • 1.Jupyter Lab environment construction
  • 2.Basic use of Jupyter Widgets
  • 3.Launch JupyterLab
  • 4.How to Use JupyterLab
Download
  • APP(iOS/Android)
  • VM File
  • Instruction manual
  • Hardware_3DModelFile
  • PC_Software
  • Code
  • Communication Protocol-Python Library
  • Tools
Download ZIP

Welcome to DOFBOT SE repository

1. QR Code

1. QR Codes

Access the Docker container, and then execute the tutorial commands within Docker to launch the application.

1.1. Introduction to QR Codes

A QR code is a type of two-dimensional barcode. "QR" stands for "Quick Response"—a name derived from the inventor's desire to create a code whose contents could be decoded rapidly. QR codes offer not only high data capacity, high reliability, and low cost, but they can also encode various types of textual information—including Chinese characters and images. Furthermore, they possess strong security and anti-counterfeiting capabilities, and are extremely convenient to use. Most importantly, the technology behind QR codes is open source.

1.2. Structure of a QR Code

ImageDescription
imgPositioning Markings: Indicate the orientation of the QR code.
imgAlignment Markings: If the QR code is large, these additional elements assist in positioning.
imgTiming Pattern: Through these lines, a scanner can determine the dimensions of the matrix.
imgVersion Information: Specifies the version number of the QR code being used; currently, there are 40 different QR code versions. Versions 1 through 7 are typically used within the retail sector.
imgFormat Information: The format pattern contains information regarding error correction levels and data masking patterns, making the code easier to scan.
imgData and Error Correction Keys: These patterns store the actual data.
imgQuiet Zone: This area is crucial for scanners; its function is to isolate the QR code from its surrounding environment.

1.2.1: Characteristics of QR Codes

The data contained within a QR code includes redundant information. Consequently, even if up to 30% of the QR code's structure is damaged, its readability remains unaffected. A QR code offers a storage capacity of up to 7,089 bits or 4,296 characters; this includes punctuation marks and special characters, all of which can be encoded into the QR code. In addition to numbers and individual characters, entire words and phrases—such as URLs—can also be encoded. As more data is added to a QR code, the physical size of the code increases, and its structural complexity grows.

1.2.2: QR Code Generation and Recognition

Path to the provided source code package:

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/home/yahboom/dofbot_ws/src/yahboom_vision/yahboom_vision/create_qrcode.py
  • Creation

Create a QRCode object.

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    '''
    Parameter Definitions:
    version: An integer value ranging from 1 to 40, controlling the size of the QR     code (the minimum value is 1, which corresponds to a 12×12 matrix). 
    If you wish for the program to determine this automatically, set the value to     None and use the 'fit' parameter. 
    error_correction: Controls the error correction capability of the QR code. It     accepts one of the following four constants:
    ERROR_CORRECT_L: Approximately 7% or fewer errors can be corrected. 
    ERROR_CORRECT_M (Default): Approximately 15% or fewer errors can be corrected. 
    ERROR_CORRECT_H: Approximately 30% or fewer errors can be corrected. 
    box_size: Controls the number of pixels contained within each individual "box"     (module) of the QR code. 
    border: Controls the number of boxes (modules) constituting the border (the         distance between the QR code and the image's edge). (The default is 4, which is the minimum value specified by the relevant standards.)
    '''
    qr = qrcode.QRCode(
    version=1,
    error_correction=qrcode.constants.ERROR_CORRECT_H,
    box_size=10,
    border=4
)

Add a Logo to a QR Code

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    # If the logo URL exists, add the logo image.
    my_file = Path(logo_path)
    if my_file.is_file(): img = add_logo(img, logo_path)

Note: When using Chinese, Chinese characters must be included.

Launch Method 1:

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python3 /home/yahboom/dofbot_ws/src/yahboom_vision/yahboom_vision/create_qrcode.py

Launch Method 2:

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ros2 run yahboom_vision create_qrcode 

After launching, enter 5555 and press Enter.

  • Identification
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def decodeDisplay(image, font_path):
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
    # The output Chinese characters must first be converted into Unicode encoding form.
    barcodes = pyzbar.decode(gray)
    for barcode in barcodes:
        # Extract the bounding box position of the QR code
        (x, y, w, h) = barcode.rect
        # Draw bounding boxes around the barcodes in the image.
        cv.rectangle(image, (x, y), (x + w, y + h), (225, 0, 0), 5)
        encoding = 'UTF-8'
        # To render it, you first need to convert it into a string.
        barcodeData = barcode.data.decode(encoding)
        barcodeType = barcode.type
       # Plot Data and Types on the Image
        pilimg = Image.fromarray(image)
       # Create a Brush
        draw = ImageDraw.Draw(pilimg) 
        # Parameter 1: Font file path, Parameter 2: Font size
        fontStyle = ImageFont.truetype(font_path, size=12, encoding=encoding)
       # Parameter 1: Print Coordinates, Parameter 2: Text, Parameter 3: Font Color, Parameter 4: Font
        draw.text((x, y - 25), str(barcode.data, encoding), fill=(255, 0, 0), font=fontStyle)
       # Convert PIL Image to OpenCV Image
        image = cv.cvtColor(np.array(pilimg), cv.COLOR_RGB2BGR)
        # Print barcode data and barcode type to the terminal
        print("[INFO] Found {} barcode: {}".format(barcodeType, barcodeData))
    return image

Launch Method 1:

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python3 /home/yahboom/dofbot_ws/src/yahboom_vision/yahboom_vision/create_qrcode.py

Launch Method 2:

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ros2 run yahboom_vision create_qrcode 

Effect Demonstration

Text and picture drawing
Human Pose Estimation

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