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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.Semantic understand instruction following

Semantic Understand Instruction Following

Function Description

After the program runs, input a sequence of action commands through the terminal. The large model will plan the action functions corresponding to the action commands and execute all commands in sequence.

Startup

Open the terminal and enter the following command:

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ros2 launch largemodel largemodel_control.launch.py text_chat_mode:=True

Then open a second terminal and enter the following command:

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ros2 run text_chat text_chat

Then input the action commands you want to execute in the text_chat terminal. You can refer to the following examples:

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Move the robotic arm up 3 centimeters, then move the robotic arm forward 3 centimeters, then turn on the red light, wait 3 seconds, then turn on the green light, and finally have the robotic arm perform a dance.

image-20251127144128521

As shown in the figure above, the large model will plan a series of action command functions, corresponding to the above action commands respectively: "arm_move('up',3)", "arm_move('forward',3)", "light_on('red')", 'wait(3)', "light_on('green')", 'arm_dance()'.

The robotic arm end effector will first move forward 3 centimeters, then light up the red LED on the driver board, after waiting for three seconds, the driver board LED will light up green, and finally the robotic arm will execute the dance action.

Core Code Analysis

arm_move Function

Source code path: LargeModel_ws/src/largemodel/largemodel/action_service.py

​x
#Dir indicates the direction to adjust, Dist indicates the distance to adjust
def arm_move(self,Dir,Dist):
    self.arm_move_flag = True
    cur_joints = [0.0,0.0,0.0,0.0,0.0,0.0]
    #Read the current angle values of six servos
    for i in range(1,7):
        cur_joints[i-1] = Arm.Arm_serial_servo_read(i)
        self.get_logger().info(f"cur_joints[i-1]: {cur_joints[i-1]}")
        if cur_joints[i-1] == None:
            cur_joints[i-1] = 0
            #self.get_logger().info('Servo Reading...')
    self.cur_joints = cur_joints
    Dir = Dir.strip("'\"")  # Remove single and double quotes
    self.Dir = Dir
    Dist = int(Dist)
    self.get_logger().info(f"Dir: {Dir}")
    self.get_logger().info(f"Dist: {Dist}")
    self.get_logger().info(f"cur_joints: {cur_joints}")
    self.cur_joints[0] = float(self.cur_joints[0])
    self.cur_joints[1] = float(self.cur_joints[1])
    self.cur_joints[2] = float(self.cur_joints[2])
    self.cur_joints[3] = float(self.cur_joints[3])
    self.cur_joints[4] = float(self.cur_joints[4])
    self.cur_joints[5] = float(self.cur_joints[5])
    #Get the end effector position of the current robotic arm pose
    self.get_current_end_pos()
    time.sleep(2)
    self.get_logger().info(f"CurEndPos: {self.CurEndPos}")
    #Call the move function to calculate the adjustment
    self.move(Dir,Dist)

def move(self,Dir,Dist):
    while not self.client.wait_for_service(timeout_sec=1.0):
        self.get_logger().info('Service not available, waiting again...')        
    request = Kinemarics.Request()
    #Determine direction and calculate the target end position of the robotic arm based on direction and distance
    if Dir == 'left': 
        request.tar_x = self.CurEndPos[0] - Dist*0.01 
    elif Dir == 'right':
        request.tar_x = self.CurEndPos[0] + Dist*0.01 
    else:
        request.tar_x = self.CurEndPos[0]
    if Dir == 'forward':
        request.tar_y = self.CurEndPos[1]  + Dist*0.01
    elif Dir == 'backwards':
        request.tar_y = self.CurEndPos[1]  - Dist*0.01
    else:
        request.tar_y = self.CurEndPos[1] 
    if Dir == 'up':
        request.tar_z = self.CurEndPos[2] + Dist*0.01 
    elif Dir == 'down':
        request.tar_z = self.CurEndPos[2] - Dist*0.01 
    else:
        request.tar_z = self.CurEndPos[2]
    request.kin_name = "ik"
    request.roll = self.CurEndPos[3] 
    request.pitch = self.CurEndPos[4]
    request.yaw = math.atan(request.tar_x/request.tar_y)
    self.get_logger().info(f"request: {request}")
    future = self.client.call_async(request)
    
#Call the inverse kinematics service to calculate the target pose of the robotic arm    
 def get_ik_respone_callback(self, future):        
    try:
        response = future.result()
        joints = [0.0, 0.0, 0.0, 0.0, 0.0,0.0]
        joints[0] = int(response.joint1) #response.joint1
        joints[1] = int(response.joint2) 
        joints[2] = int(response.joint3) 
        if response.joint4>90:
            joints[3] = 90 
        else:
            joints[3] = int(response.joint4)
        joints[4] = 90 
        joints[5] = 30
        time.sleep(1.5)
        #If adjusting left/right, only change servo 1 value, keep other values unchanged
        if self.Dir == 'left' or self.Dir == 'right':
            joints[1] = self.cur_joints[1]
            joints[2] = self.cur_joints[2]
            joints[3] = self.cur_joints[3]
         #If adjusting up/down/forward/backward, keep servo 1 value unchanged, change other values
        elif  self.Dir == 'down' or self.Dir == 'up' or self.Dir == 'forward' or self.Dir == 'backwards':
            joints[0] = self.cur_joints[0]             
        self.get_logger().info(f"joints: {joints}")
        if self.return_flag == True:
            Arm.Arm_serial_servo_write6(joints[0], joints[1], joints[2], joints[3], 90, self.grasp_joint,2000)
            time.sleep(2.0)
            Arm.Arm_serial_servo_write(6, 0, 2000)
            time.sleep(2.0)            
        else:
            #Communicate with the bottom control board to control robotic arm movement
            Arm.Arm_serial_servo_write6(joints[0], joints[1], joints[2], joints[3], 90, self.grasp_joint,2000)
            time.sleep(2.0)
            for i in range(6):
                if joints[i] <0:
                    joints[i] = 0
            self.cur_joints = joints
        if self.arm_move_flag == False:
            Arm.Arm_serial_servo_write6(90,120,10,10,90,30,2000)
            time.sleep(2.0)
            if self.back_list == False:
                self.action_status_pub("return_to_orin_done")
            self.return_done = True
        else:
            #time.sleep(2.0)
            self.get_logger().info("Moving.")
            self.get_logger().info(f"self.combination_mode: {self.combination_mode}")
            self.get_logger().info(f"self.interrupt_flag: {self.interrupt_flag}")
            if not self.combination_mode and not self.interrupt_flag:
                self.get_logger().info("Move done.")
                self.action_status_pub("arm_move_done") 
    except Exception:
       pass 

light_on Function

Source code path: LargeModel_ws/src/largemodel/largemodel/action_service.py

xxxxxxxxxx
def light_on(self,color):
    color = color.strip("'\"")  # Remove single and double quotes
    self.get_logger().info("Trun on the RGB Light.")
    if color == "red":
        self.get_logger().info("Trun on the Red Light.")
        Arm.Arm_RGB_set(50, 0, 0) #RGB lights up red
    elif color == "green":
        self.get_logger().info("Trun on the Green Light.")
        Arm.Arm_RGB_set(0, 50, 0) #RGB lights up green
    elif color == "blue":
        self.get_logger().info("Trun on the Blue Light.")
        Arm.Arm_RGB_set(0, 0, 50) #RGB lights up blue   
    if not self.combination_mode and not self.interrupt_flag:
        self.action_status_pub("light_on_done")

wait Function

Source code path: LargeModel_ws/src/largemodel/largemodel/action_service.py

xxxxxxxxxx
def wait(self, duration):
    duration = float(duration)
    #Sleep for duration seconds
    time.sleep(duration)
    if not self.combination_mode and not self.interrupt_flag:
        self.action_status_pub("wait_done", duration=duration)

arm_dance Function

Source code path: LargeModel_ws/src/largemodel/largemodel/action_service.py

#Robotic arm dance - directly communicates with the bottom control board to control the robotic arm to move to the specified pose
def arm_dance(self):  
    Arm.Arm_serial_servo_write6(90,90,90,90,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,60,120,60,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,45,135,45,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,60,120,60,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,90,90,90,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,100,80,80,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,120,60,60,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90, 135, 45, 45, 90, 90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90,90,90,90,90,90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90, 90, 90, 20, 90, 150,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90, 90, 90, 90, 90, 90,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90, 90, 90, 20, 90, 150,1000)
    time.sleep(1.0)
    Arm.Arm_serial_servo_write6(90, 130, 0, 5, 90, 0,1000)
    if not self.combination_mode and not self.interrupt_flag:
        self.action_status_pub("arm_dance_done") 
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