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DOFBOT Pro📖
1. Get started quickly
  • 0.Unboxing introduction video
  • 1. First Trial
  • 2. Analysis of common problems
  • 3. Calibration offset
  • 4. Jetpack old system upgraded to SUPER system
  • 5. Precautions for DIY Robotic Arm
  • 6. Jetson Nano Version – Must Read
  • 7.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 web page programming
4. Preparation
  • 1. Manage APP control services
  • 2. Manage JupyterLab services
  • 3. Manage OLED services
  • 4. Modifying ROS_DOMAIN_ID for Multi-Machine
5. 2D visual tracking course
  • 1. Color block positioning
  • 2. Color block tracking
  • 3. Face positioning
  • 4. Face tracking
  • 5. Label code positioning
  • 6. Label code tracking
6. 2D visual grabbing course
  • 1. Identify grab color block
  • 2. Catch game
  • 3. Color sorting
  • 4. Color stacking
  • 5. Label code sorting
  • 6. Label code stacking
  • 7. Identify gesture grab color block
  • 8. Gesture stacking
  • 9.1 Single garbage sorting(Jetson-Nano)
  • 9.2 Single garbage sorting(Orin)
  • 10.1 Garbage sorting(Jetson-Nano)
  • 10.2 Garbage sorting(Orin)
  • 11. Tracking game
7. 2D Mediapipe course
  • 1. Hand detection
  • 2. Posture detection
  • 3. Overall detection
  • 4. Facial Detection
  • 5. Face Detection
  • 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
  • 14.1 Robotic arm tracks the palm(Jetson-Nano)
  • 14.2 Robotic arm tracks the palm(Orin)
  • 15. Fingertip trajectory recognition
  • 16. Fingertip trajectory control robotic arm
  • 17. Gesture Grasp and Release Objects
  • 18. Finger Control Robot Arm
8. AI Large Model Voice Module (Must Read)new
  • 1. Introduction to AI Large Model Voice Module
  • 2. Flash the firmware (Must read)
  • 3. Modify the wake-up word and command word
9. 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
  • 11.1 Garbage Recognition with Voice Broadcast(Jetson Nano)
  • 11.2 Garbage Recognition with Voice Broadcast(Orin)
  • 12.1 Garbage Sorting with Voice Broadcast(Jetson Nano)
  • 12.2 Garbage Sorting with Voice Broadcast(Orin)
10. 3D Depth Camera Course
  • 1. Dabai_DCW2 camera
  • 2. Deep Pseudo-Color Image
  • 3. Depth camera ranging
  • 4. Color block volume measurement
11. 3D Robotic Arm Control and Inverse Kinematics
  • 1. Robotic arm ROS control
  • 2. Inverse solution
12. 3D Sorting and Grasping Course
  • 1. AprilTag ID sorting
  • 2. AprilTag abnormal height sorting
  • 3. MediaPipe Gesture-AprilTag ID sorting
  • 4. MediaPipe Gesture-AprilTag height sorting
  • 5. MediaPipe Gesture-AprilTag distance sorting
  • 6. Block color sorting
  • 7. Block abnormal height sorting
  • 8. Block different shape sorting
  • 9. Block shape abnormal height sorting
  • 10. Yolov11 garbage sorting(Orin)
13. 3D Tracking and Grasping Course
  • 1. AprilTag Tracking and Grasping
  • 2. Color Block Tracking and Grasping
  • 3. KCF Object Tracking and Grasping
14. 3D Voice Control for Grasping Course (Sorting & Tracking)
  • 1. Voice Control AprilTag ID Sorting
  • 2. Voice Control Remove Height Abnormal AprilTag
  • 3. Voice Control Tracking and Grasping AprilTag
  • 4. Voice Control Color Block Sorting
  • 5. Voice Control Remove Height Abnormal Color Block
  • 6. Voice Control Tracking and Grasping Color Block
  • 7. Voice Control Yolov11 Garbage Recognition Sorting
  • 8. Voice Control Object Tracking and Grasping
15. AI Model Basicsnew
  • 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
16. AI Model Developmentnew
  • 1.Register a model service provider account
  • 2. Configure API-KEY
  • 3. Introduction to Dify
  • 4. Basic Dify Features
  • 5. Deploy the RAG knowledge base
  • 6. AI Large Model Development - chatbot
  • 7. RAG knowledge base + chatbot
  • 8. AI agent workflow
17. AI Model – Text Versionnew
  • 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
18. AI Model – Voice Versionnew
  • 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 – Fun Applicationsnew
  • 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
20. MoveIt 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
21. YOLOv11 Development Course (ORIN)
  • 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. Dataset Annotation
  • 10. Model Training_Conversion
  • 11. Model Prediction
22. YOLOv11 Development Course (Jetson Nano)
  • 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. Basic Control Course
  • 1. Control RGB Light
  • 2. Control Buzzer
  • 3. Control Single Servo
  • 4. Read Servo Angle
  • 5. Control All Servos
  • 6. DOFBOT Up Down Left Right Movement
  • 7.DOFBOT dancing
  • 8. DOFBOT Memory Actions
  • 9. DOFBOT Grab Blocks
  • 10. Porter
  • 11. Stack Blocks
  • 12. Two DOFBOT Synchronized Actions
25. Jetson Board Basic Course
  • 1. Jetson board Introduction
  • 2. Write system image
  • 3. Re-write system image
  • 4. System startup
  • 5. System and desktop introduction
  • 6. System expansion
  • 7. Network Configuration
  • 8. SSH remote login and file transfer
  • 9. VNC Remote Login
  • 10. System backup
  • 11. Increased swap space
  • 12. Use of Jtop
26. GPIO Hardware Control Course
Jetson Nano
  • 1.GPIO library API usage
  • 2. Hardware library configuration
  • 3. Pin reading function
  • 4. Pin level output control
  • 5. Control LED
  • 6. External device serial communication
  • 7.I2C communication
Jetson Orin Nano_NX
  • 1.GPIO description
  • 2.GPIO library installation
  • 3.GPIO reading
  • 4.GPIO output
  • 5.Serial communication
  • 6.I2C communication
27. OpenCV Course
  • 1. Introduction to Open Source CV
  • 2. Image reading and display
  • 3. Image writing
  • 4. Image quality
  • 5. Pixel Operation
  • 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
28. Visual Basics Course
  • 1. Camera display
  • 2. Color Calibration
  • 3. Color recognition
  • 4. Face Detection
  • 5.1 Garbage Identification(Jetson-Nano)
  • 5.2 Garbage Identification(Orin)
  • 6.1 Object Recognition(Jetson-Nano)
  • 6.2 Object Recognition(Orin)
  • 7. Label code recognition
  • 8.PID algorithm basics
29. 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
30. Visual Advanced Course
  • 1.QR code
  • 2.Human pose estimation
  • 3.Target Detection
  • 4.AR vision
  • 5.ROS+Opencv basics
  • 6.AR QR code
  • 7.Face recognition
  • 8.harris corner detection
  • 9.Target tracking algorithm
  • 10.Contour moment
  • 11.Polygon outline
  • 12.Discrete fourier transform algorithm
  • 13.Edge detection algorithm
  • 14.Face detection algorithm
  • 15.Optical flow detection algorithm
  • 16.Contour detection
  • 17.General contour detection
  • 18.Feature point tracking
  • 19.HLS color filtering
  • 20.Hough circle detection
  • 21.Hough linear detection
  • 22.HSV color filtering
  • 23.LK optical flow algorithm
  • 24.detection algorithm
  • 25.Phase dependent displacement detection
  • 26.Image pyramid sampling algorithm
  • 27.RGB color filtering
  • 28.Clear background detection algorithm
  • 29.Simplified optical flow algorithm
  • 30.Simple filter
  • 31.Threshold image processing
  • 32.Watershed segmentation algorithm
31. Jupyter Lab Usage Course
  • 1. Read the document before operation
  • 2. Jupyter lab environment construction tutorial
  • 3. Basic tutorial of Jupyter lab
  • 4. Jupyter widgets configuration tutorial
  • 5. Getting Started Tutorial for JupyterWidgets Controls
Download
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  • Hardware_Info
  • 3D_Model_File
  • ROS2_Basic_VM
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Welcome to DOFBOT Pro repository

7. Multimodal Large Model+robotic arm sorting

Multimodal Large Model + Robotic Arm Color Block Sorting(Text Version)

Before running the function, you need to close the App and large programs. For the closing method, refer to [4. Preparation] - [1. Manage APP control services].

1. Function Description

After the program runs, input the color block sorting order through the terminal. The large model will plan the steps to complete the color block sorting task, then the program will control the robotic arm to sort the color blocks according to the order and place them at the set positions.

The wooden blocks used in this lesson: 30x30x30mm blocks.

2. Startup

Users with Jetson-Nano board version need to enter the docker container and input the following command. Orin board users can directly open the terminal and input the following command:

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

Then open a second terminal and input the following command:

xxxxxxxxxx
ros2 run text_chat text_chat

Then specify the color block sorting order in the terminal, you can refer to the following example:

xxxxxxxxxx
Sort the color blocks on the desktop in the order of yellow, red, blue, green

image-20251129095416783

As shown in the figure above, before sorting the yellow color block, first check if it is in the removal list. If it is, then directly grip it from the removal list and place it at the yellow color block placement point; if not, then determine if there are other color blocks on top of the yellow color block. If there are, first remove the other color blocks above the yellow color block. If there are none, then directly grip it and place it at the yellow color block placement point. Other color blocks are also sorted according to this execution order until the task is completed.

3. Task Planning

  1. Call check_remove(color) function to check if the current target color block to be sorted exists in the removal list (where color is the color of the current target color block to be sorted, value range is red, blue, green or yellow);
  2. If the current target color block to be sorted exists in the removal list, execute the following operations: (1) Call grasp_from_rm_list(color) function to grip the current target color block to be sorted from the removal list (meaning of color parameter is the same as above); (2) Call arm_stack(color) to place the target color block at the specified position (where color parameter meaning is the same as above).
  3. If the target color block does not exist in the removal list, follow these steps to sort the current color block to be sorted (only output one action function at a time): (1) Call seewhat() function to find the current target color block to be sorted; (2) Call seewhat() function to determine if there are other objects on top of the current target color block to be sorted; (3) If there are no other objects on top of the current target color block to be sorted, execute the following steps (only output one action function at a time): ① Call grasp_obj(x1, y1, x2, y2) function to grip the current target color block to be sorted (where (x1, y1, x2, y2) are the top surface border coordinates of the current target color block to be sorted); ② Call arm_stack(color) to place the current target color block to be sorted at the specified position (where color parameter meaning is the same as above). (4) If there are other objects on top of the current target color block to be sorted, execute the following steps to first remove that object then sort the current target color block to be sorted, here only one action function can be output at a time: ① Call remove_obj(x1, y1, x2, y2, color) function to remove that object (where (x1, y1, x2, y2) are the top surface border coordinates of that object, color is the color of that object, value range is red, blue, green or yellow); ② Call seewhat() function to observe the environment; ③ If there are no other objects on top of the current target color block to be sorted, call grasp_obj(x1, y1, x2, y2) function to grip the current target color block to be sorted (where (x1, y1, x2, y2) are the top surface border coordinates of the current target color block to be sorted); ④ Call arm_stack(color) to place the target color block at the specified position (where color parameter meaning is the same as above).

4. Core Code Analysis

4.1. check_remove(color) Function

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

xxxxxxxxxx
def check_remove(self,color):
    #Get current color parameter
    check_color = color.strip("'\"")
    #If the current color is in the self.cur_rm_pose dictionary, it means it's in the removal list, otherwise, it was not found in the removal list
    if check_color in self.cur_rm_pose:
        self.action_status_pub("color is in the rm_list")
    else:
        self.action_status_pub("color is not in the rm_list")
#You can see what content color is in the rm_list and color is not in the rm_list return to the large model respectively
"color is in the rm_list" : "Color block exists in removal list, grip this color block from removal list",
"color is not in the rm_list" : "Color block does not exist in removal list, determine if there are other objects on top of this color block"

4.2. grasp_from_rm_list Function

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

xxxxxxxxxx
def grasp_from_rm_list(self,color):
    #Get current color parameter
    tar_color = color.strip("'\"")
    #Find corresponding key value in dictionary based on current color parameter, assign to tar_joints
    tar_joints = self.cur_rm_pose.get(tar_color)
    #Control robotic arm six servos
    Arm.Arm_serial_servo_write6(tar_joints[0], tar_joints[1], tar_joints[2], tar_joints[3], tar_joints[4], tar_joints[5],2000)
    time.sleep(2.0)
    Arm.Arm_serial_servo_write(6, 140, 1000)
    time.sleep(2.0)
    Arm.Arm_serial_servo_write6(90,120,10,10,90,140,2000)
    time.sleep(2.0)
    #Feedback to large model that gripping color block from removal list is complete
    self.action_status_pub("grasp_from_rm_list_done")

4.3. arm_stack Function

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

xxxxxxxxxx
def arm_stack(self,color):
    #Get current color parameter
    tar_color = color.strip("'\"")
    #Select robotic arm placement posture based on current color parameter
    if tar_color == 'red':
        Arm.Arm_serial_servo_write6(117, 19, 66, 56, 90,self.grasp_joint,2000)
        time.sleep(2.0)
    elif tar_color == 'green':
        Arm.Arm_serial_servo_write6(136, 66, 20, 29, 90,self.grasp_joint,2000)
        time.sleep(2.0)
    elif tar_color == 'blue':
        Arm.Arm_serial_servo_write6(44, 66, 20, 28, 90,self.grasp_joint,2000)
        time.sleep(2.0)
    elif tar_color == 'yellow':
        Arm.Arm_serial_servo_write6(65, 22, 64, 56, 90,self.grasp_joint,2000)
        time.sleep(2.0)
    Arm.Arm_serial_servo_write(6, 30, 1500)
    time.sleep(1.5)
    Arm.Arm_serial_servo_write6(90,120,10,10,90,30,2000)
    time.sleep(2.0)
    #Feedback to large model that color block placement is complete
    self.action_status_pub("arm_stack_done", color=color)

4.4. remove_obj Function

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

​x
def remove_obj(self, x1, y1, x2, y2,color):
    #Get current color parameter
    cur_rm_name = color.strip("'\"")  # Remove single and double quotes
    self.cur_rm_name = cur_rm_name
    #Create a key in the dictionary
    self.cur_rm_pose[self.cur_rm_name] = []
    self.remove_cnt = -self.remove_cnt 
    """
    Grip object
    x1,y1,x2,y2: Object outer border coordinates
    """
    #Gripping object program
    cmd1 = "ros2 run largemodel_arm KCF_Grap_Move"
    #KCF tracking positioning program
    cmd2 = "ros2 run largemodel_arm ALM_KCF_Tracker"
    subprocess.Popen(
        [
            "gnome-terminal",
            "--title=ALM_KCF_Tracker",
            "--",
            "bash",
            "-c",
            f"{cmd2}; exec bash",
        ]
    )
    time.sleep(5.0) #Wait for ALM_KCF_Tracker to start up
    subprocess.Popen(
        [
            "gnome-terminal",
            "--title=grasp_desktop",
            "--",
            "bash",
            "-c",
            f"{cmd1}; exec bash",
        ]
    )
    time.sleep(2.0)
    if self.stack_flag == True:
        self.get_logger().info('Publish the stack_step topic...') 
        step_ = Int16()
        step_.data = self.step
        self.step_pub.publish(step_)
        self.step = self.step + 1
    #Publish outer border coordinate information topic data, ALM_KCF_Tracker node will subscribe to this topic
    x1 = int(x1)
    y1 = int(y1)
    x2 = int(x2)
    y2 = int(y2)
    self.object_position_pub.publish(Int16MultiArray(data=[x1, y1, x2, y2]))
​
    while not self.grasp_obj_future.done():
        if self.interrupt_flag:
            self.check_close_grasp_obj()
            #self.pubSix_Arm(self.init_joints)  # Robotic arm retract
            #Arm.Arm_serial_servo_write6(90,150,12,20,90,30,1000)
            self.stop()
            return
        time.sleep(0.1)
    self.check_close_remove_obj()
    
    
    tmp_joint1 = 90 + self.remove_cnt*60 #30 150
    #Add the calculated joint values for placing removed color blocks to the dictionary as the key value of self.cur_rm_pose[self.cur_rm_name]
    self.cur_rm_pose[self.cur_rm_name] = [tmp_joint1,50,40,20,90,30]
    self.get_logger().info(f"self.cur_rm_pose:{self.cur_rm_pose}")
    #Control robotic arm to move to specified posture to place removed color blocks
    Arm.Arm_serial_servo_write6(tmp_joint1,50,40,20,90,140,2000)
    time.sleep(2.0)
    Arm.Arm_serial_servo_write6(tmp_joint1,50,40,20,90,30,2000)
    time.sleep(2.0)
    Arm.Arm_serial_servo_write6(90,120,10,10,90,30,2000)
    time.sleep(2.0)
    #Feedback to large model that color block removal is complete
    self.action_status_pub("remove_obj_done", x1=x1, y1=y1, x2=x2, y2=y2, color=color)

KCF_Grap_Move and ALM_KCF_Tracker nodes have been analyzed in previous content, you can refer to section 2.4.3 in [17.AI Model-Text Version]-[Multimodal Large Model+Robotic Arm Gripping].

4.5. grasp_obj(x1, y1, x2, y2) Function

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

grasp_obj(x1, y1, x2, y2) function has been analyzed in previous content, you can refer to section 2.4.3 in [17.AI Model-Text Version]-[Multimodal Large Model+Robotic Arm Gripping].

 

Multimodal Large Model+robotic arm tracking
Multimodal Large Model+robotic arm handling

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