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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

4.Color sorting and stacking

Color Sorting And Stacking

Gameplay Introduction

ros2 run dofbot_info dofbot_server # Start server node
Color sorting gameplay path: dofbot_ws/src/dofbot_color_identify/scripts/颜色分拣color_sort.ipynb
Color stacking gameplay path: dofbot_ws/src/dofbot_color_stacking/scripts/颜色堆叠color stacking play.ipynb

(1)HSV Calibration: Since different environments produce different color recognition results, it is best to perform HSV calibration before playing color sorting. For specific methods, refer to [Color Calibration].

(2)Frame Calibration: After color calibration is complete, frame calibration needs to be performed to obtain the position information of blocks within the frame. For specific calibration methods, refer to [Visual Positioning].

(3)Select Color: Players can freely choose the color to grab according to their needs. The robotic arm will sort according to the color selected by the player.

(4)Grab Sorting: After the camera recognizes the block, click the grab button to sort it.

(5)Clear Color: If the player wants to change the selected color, simply clear the selected color and reselect for recognition.

(6)Exit Program: To close this gameplay, click the exit button to release resources.

Color Recognition

Note: Effective only after frame calibration is complete.

  • Operation process

(1) After calibration is complete, select a color in the color option box on the right side (no color selected by default), as shown in the figure above.

(2) After color selection is complete, click the [target_detection] button to call the color recognition function to mark the detected blocks.

(3) Click the [grap] button to sort out the recognized blocks.

(4) Click the [reset_color_list] button to clear the selected color sequence. The color selection bar still shows the previous selection order, just replace it. Repeat steps (2), (3).

  • Code design

Color selection sequence, generate color sequence after selection is complete

​x
def color_list_one_Callback(value):
    pass
​
def color_list_two_Callback(value):
    pass
​
def color_list_three_Callback(value):
    pass
​
def color_list_four_Callback(value):
    pass
​
color_list_one.observe(color_list_one_Callback)
color_list_two.observe(color_list_two_Callback)
color_list_three.observe(color_list_three_Callback)
color_list_four.observe(color_list_four_Callback)

Click the [target_detection] button to call the color recognition function select_color()

xxxxxxxxxx
def select_color(self, image, color_hsv, color_list):
    '''
    Select recognition color
    :param image: Input image
    :param color_hsv: Example {color_name:((lowerb),(upperb))}
    :param color_list: Color sequence:['0': none   '1': red '2': green '3': blue '4': yellow]
    :return: Output processed image, (color, position)
    '''
    pass

Parse the passed color sequence and color information. Detect blocks in the color sequence respectively. Return block coordinates

xxxxxxxxxx
def get_Sqaure(self,color_hsv):
'''
Color recognition, get block coordinates
'''
pass

For detailed code introduction, see dofbot_ws/src/dofbot_color_identify/scripts/颜色分拣color_sort.ipynb

Get Inverse Solution Results

  • Operation process

After detecting the block, click the [grap] button to grab

  • Code design

Send the obtained block coordinate information through ROS server communication. Solve the angle each joint should rotate through inverse kinematics. Obtain joint angles to drive the robotic arm to grab.

xxxxxxxxxx
def server_joint(self,posxy):
    '''
    Publish position request, get joint rotation angle
    :param posxy: Position point x, y coordinates
    :return: Rotation angle of each joint
    '''
    # Wait for server to start
    self.client.wait_for_service()
    # Create message packet
    request = kinemaricsRequest()
    request.tar_x = posxy[0]
    request.tar_y = posxy[1]
    request.kin_name = "ik"
    try:
       # Get inverse solution response result
       response =   self.client.call(request)
        pass
  except Exception:  rospy.loginfo("arg error")

For detailed code, see the identify_target.py and identify_grap.py under dofbot_ws/src/dofbot_color_identify/scripts/

  • Grab design process

Lift robotic arm -> Release gripper -> Move to block position -> Grip -> Lift -> Move to target position -> Release gripper -> Reset robotic arm.

Color Stacking

Color stacking gameplay is similar to color sorting, except that the robotic arm stacks the blocks vertically according to the selected color at the end.

Note: Effective only after frame calibration is complete. Color stacking not only requires the ability to grip the blocks, but the gripping position should be as consistent as possible. The positioning requirement is very high. Users can adjust the gripping position and pose according to actual situations. For specific adjustment methods, please refer to the [Visual Positioning] section.

  • Example image

  • Operation process

(1) After calibration is complete, select a color in the color option box on the right side (no color selected by default), as shown in the figure above.

(2) After color selection is complete, click the [target_detection] button to call the color recognition function to mark the detected blocks.

(3) Click the [grap] button to sort the recognized blocks, then stack them into the gray frame. The stacking order is the same as the color selection order in the figure above.

(4) Click the [reset_color_list] button to clear the selected color sequence. The color selection bar still shows the previous selection order, just replace it. Repeat steps (2), (3). For detailed code introduction, see dofbot_ws/src/dofbot_color_stacking/scripts/颜色堆叠color stacking play.ipynb

 

 

 

 

 

Catch game
Garbage sorting

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