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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
  • APP(Android/iOS)
  • SystemFile_OrinNANOSUPER
  • SystemFile_OrinNXSUPER
  • SystemFile_NANO4GB_SUB
  • VM_File
  • Code
  • Instruction_Manual
  • Hardware_Info
  • 3D_Model_File
  • ROS2_Basic_VM
  • Tools
Download ZIP

Welcome to DOFBOT Pro repository

5. Multimodal Large Model+robotic arm gripping

Multimodal Large Model+robotic arm gripping(Voice 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, wake up the voice module and input robotic arm gripping commands by voice. Based on the type of object to be gripped, the large model will start external programs to control the robotic arm to grip the target object.

2. Startup

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

ros2 launch largemodel largemodel_control.launch.py

The robotic arm gripping has the following action commands:

  • Pick by Machine Code ID: Sort Machine Codes 1, 2, 3, and 4. Blocks used: 30x30x30mm blocks.
  • Pick by Machine Code Height: Remove Machine Codes exceeding a height of x cm (where x denotes height). Example: Remove Machine Codes exceeding 5 cm in height. Blocks used: 30x30x30mm blocks, 30x30x60mm blocks.
  • Pick by Color Block Height: Remove color blocks of color y exceeding a height of x cm (where x denotes height and y denotes color—specifically Red, Green, Yellow, or Blue). Example: Remove red blocks exceeding 5 cm in height. Blocks used: 30x30x30mm blocks, 30x30x60mm blocks.
  • Pick Other Objects: Pick up the small yellow duck on the tabletop; pick up the blue rectangular block on the tabletop. Blocks used: 40x40x40mm blocks.

2.1. Grip by Machine Code ID

2.1.1. Startup

After waking up the module, input by voice:

xxxxxxxxxx
Sort machine code 2

The program will open two terminals, starting the machine code recognition program and gripping program respectively. After recognizing machine code 2, the gripping program will control the robotic arm to descend and grip machine code 2, then place it at the set position, and finally return to the machine code recognition posture to prepare for the next gripping. This continues until no more machine code 2 is recognized, then it reports back to the large model and the task ends.

2.1.2. Task Planning

Plan the action function apriltag_sort(2), where the parameter 2 represents the ID of the machine code to be gripped.

2.1.3. Core Code Analysis

You can refer to the content in 2.1.3. Core Code Analysis from tutorial [17. AI Model - Text Version] - [Multimodal Large Model+robotic arm gripping]. The voice version and text version have the same action functions, only the task command input method is different.

2.2. Grip by Machine Code Height

2.2.1. Startup

After waking up the module, input by voice:

xxxxxxxxxx
Remove machine codes with height higher than 3 cm

Then two terminals will open, starting the machine code recognition height calculation program and gripping program respectively. After recognizing machine codes with height higher than 3 cm, the gripping program will control the robotic arm to descend and grip the abnormal height machine codes, then place them at the set position, and finally return to the machine code recognition posture to prepare for the next gripping. This continues until no more abnormal height machine codes are recognized, then it reports back to the large model and the task ends.

2.2.2. Task Planning

Plan the action function apriltag_remove_higher(30.0), where the parameter 30 represents the height threshold. Machine codes with height higher than this value will be removed, unit is millimeters mm.

2.2.3. Core Code Analysis

You can refer to the content in 2.2.3. Core Code Analysis from tutorial [17. AI Model - Text Version] - [Multimodal Large Model+robotic arm gripping]. The voice version and text version have the same action functions, only the task command input method is different.

2.3. Grip by Color Block Height

2.3.1. Startup

After waking up the module, input by voice:

xxxxxxxxxx
Remove green blocks with height higher than 3 cm

Then two terminals will open, starting the color block recognition height calculation program and gripping program respectively. After recognizing green blocks with height higher than 3 cm, the gripping program will control the robotic arm to descend and grip these blocks, then place them at the set position, and finally return to the recognition posture to prepare for the next gripping. This continues until no more abnormal height green blocks are recognized, then it reports back to the large model and the task ends.

2.3.2. Task Planning

Plan the action function color_remove_higher('green',30.0), 'green' indicates the color block to be sorted is green blocks, the parameter 30 represents the height threshold. Machine codes with height higher than this value will be removed, unit is millimeters mm.

2.3.3. Core Code Analysis

You can refer to the content in 2.3.3. Core Code Analysis from tutorial [17. AI Model - Text Version] - [Multimodal Large Model+robotic arm gripping]. The voice version and text version have the same action functions, only the task command input method is different

2.4. Grip Other Objects

2.4.1. Startup

After waking up the module, input by voice:

xxxxxxxxxx
Grip the small yellow duck on the desktop

The program will first take a photo to determine the position of the small yellow duck, then open two terminals, starting the KCF tracking positioning program and object gripping program respectively. After calculation, the robotic arm will descend to grip the small yellow duck and finally return to the initial posture.

2.4.2. Task Planning
  1. Call seehat() to check the position of the small yellow duck;
  2. Call grasp_obj(x1,y1,x2,y2) gripping function, where x1,y1,x2,y2 represent the top-left and bottom-right corner coordinates of the small yellow duck's outer bounding box.
2.4.3. Core Code Analysis

You can refer to the content in 2.4.3. Core Code Analysis from tutorial [17. AI Model - Text Version] - [Multimodal Large Model+robotic arm gripping]. The voice version and text version have the same action functions, only the task command input method is different

Multimodal Large Model+video understanding
Multimodal Large Model+robotic arm tracking

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