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DOGZILLA-Lite📖
1. Get started quickly
  • 0. Notes (Must Read)new
  • 1. Main interface function experience (cm5)new
  • 1. Main interface function experience(cm4)
  • 2. APP control experience
  • 3. Web page image transmission control
  • 4. LLM-Embodied Intelligence Capabilities
  • 5. LLM-Smart Dog Capabilities
2. Basic operations of Raspberry Pi system
  • 1.SSH remote login
  • 2.VNC remote login desktop
  • 3.Remote file transfer
  • 4.JupyterLab environment construction and use
  • 5.Burn the system image
  • 6.Connect to WiFi
  • 7.Close large programs
  • 8.Raspberry Pi system expansion
3. Basic control of the dogzilla
  • 0. Introduction to DOGZILLA-Lite
  • 1. Screen display control
  • 2. Record Audio
  • 3. Play Audio
  • 4. Text to audio
  • 5. Voice to text
  • 6. Record Video
  • 7. Play Video
  • 8. Video recording function
  • 9. Read the posture angle
  • 10. Battery level reading
  • 11. Read the servo angle
  • 12. Screen display of expressions
  • 13. Calibration of the robot dog
  • 14. Burn the firmware
  • 15. Analysis of common problems
4. Motion control of the dogzilla
  • 1. The dog's forward, backward, left, and right movements and gait
  • 2. Dog Spin
  • 3. The dog adjusts its height and posture
  • 4. Dog periodic translation and rotation
  • 5. Self-balancing mode
  • 6. The dog performs preset actions
  • 7. Single Leg Control
  • 8. Robotic arm control
  • 9. Teaching mode
  • 10. Group Control Performance
  • 11. Teaching demonstration onlinenew
5. Open Source CV
A. Getting started with OpenCV
  • 1. Introduction to OpenCV
  • 2. OpenCV image reading and display
  • 3. OpenCV image writing
  • 4. OpenCV Image Quality
  • 5.OpenCV pixel operations
B. OpenCV geometric transformation
  • 1. Image scaling
  • 2. Image cutting
  • 3. Image translation
  • 4. Image mirroring
  • 5. Affine Transformation
  • 6. Image Rotation
  • 7. Perspective Transformation
C. OpenCV image processing and drawing text segments
  • 1. Grayscale processing
  • 2. Image Binarization
  • 3. Edge Detection
  • 4. Line drawing
  • 5. Rectangle and circle drawing
  • 6. Text and picture drawing
D. Image beautification
  • 1. Color Image Histogram
  • 2. Histogram Equalization
  • 3. Image repair
  • 4. Brightness enhancement
  • 5. Skin whitening
  • 6. Gaussian mean filtering
  • 7. Median Filter
6. AI recognition of the dogzilla
  • 1. Camera driver tutorial
  • 2. Color recognition
  • 3. HSV value test
  • 4. Object Recognition
  • 5. QR code recognition
  • 6. License Plate Recognition
  • 7. Human Pose Estimation
  • 8. Yolo detection
  • 9. Face Detection
  • 10. Human face mask
  • 11. Face effects
  • 12. 3D Object Recognition
  • 13. Paintbrush
  • 14. Finger recognition
  • 15. Gesture Recognition
  • 16. Age and gender identification
  • 17. Background Segmentation
  • 18. Facial Recognitionnew
  • 19. Emotion Recognitionnew
  • 20. Motion Detectionnew
7. Dogzilla AI Interaction
  • 1. Color patrol
  • 2. Line patrol and obstacle removal
  • 3. Color tracking
  • 4. Ball tracking
  • 5. The ball follows
  • 6. QR code recognition exercise
  • 7. Face tracking
  • 8. Remote control
  • 9. Gesture tracking
  • 10. Gesture-controlled movement
  • 11. You Drop, I Pick
  • 12. Independent football exercise
  • 13. Human Body Followingnew
8. AI large model interaction
  • 0.AI large model principle foundation
  • 1.Large model premise use configuration
  • 2.Q&A
  • 3.Embodied intelligence
  • 4.Smart dog
  • 5.Picture to text
  • 6.Intelligent interaction
  • 7.Voice intelligent vision
  • 8.Playing football
  • 9.Block gripping
  • 10.Line tracking and obstacle removal
  • 11.Control object tracking
Download
  • System_File
  • Code
  • Firmware
  • Communication interface
  • Instruction Manual
  • Appendix
Download ZIP

Welcome to DOGZILLA-Lite repository

11. Teaching demonstration online

Teaching online

This tutorial is specific to the CM5 version and will not work directly with the CM4 version.

Teaching online1. Experimental Objective2. Experimental Procedure3. Experimental Results4. Experimental Source Code AnalysisNotes:

1. Experimental Objective

Learn to manually control the robotic arm of a single robot dog, thereby enabling control of multiple robot arms.

2. Experimental Procedure

Log in to the robot dog's system, exit the robot dog program, and enter "ip (where ip is the robot dog's IP address):8888 in your browser. Once logged in, enter the password "yahboom."

image-2024112100001

Then log in. Go to cd ~/DOGZILLA_Lite_class/3.Dog Base Control/11.Teaching online and run Teching_UDP.ipynb.

3. Experimental Results

  1. After running the source code, a mode selection window will appear, and the screen will display "Teaching Class!!!"

image-2024112100005

  1. Next, select a mode. There are two modes: Master and Slave. In Master mode, you can manually control the angle of the robot's arm, so that the slave's arm can rotate to the master's position.

image-2024112100002

Master mode selection page:

image-2024112100004

Slave mode selection page

image-2024112100003

  1. Master mode: Only one robot dog is required. All robot dogs that wish to be controlled by the master mode can be selected as slaves.

4. Experimental Source Code Analysis

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def host_mode():
    """主机模式  Host mode"""
    time.sleep(1)
    dog.unload_motor(5)
    while True:
        # 显示界面 display interface
        draw.rectangle((0, 0, mydisplay.height, mydisplay.width), fill="BLACK")
        draw.text((20, 80), "Host Mode Running", fill="CYAN", font=font1)
        draw.text((20, 120), "B:Force Exit", fill="WHITE", font=font1)
        mydisplay.ShowImage(splash)
        
        # 业务逻辑 business logic
        motor_data = dog.read_motor()
        print(type(motor_data))
        if motor_data:
            send_arm_angles(motor_data[-3:])
        # 按钮检测 Button detection
        if check_exit_buttons():
            break  
        time.sleep(0.1)
​
def client_mode():
    """从机模式  slave mode"""
    dog.load_allmotor()
    while True:
        # display interface
        draw.rectangle((0, 0, mydisplay.height, mydisplay.width), fill="BLACK")
        draw.text((20, 80), "Client Mode Running", fill="CYAN", font=font1)
        draw.text((20, 120), "B:Force Exit", fill="WHITE", font=font1)
        mydisplay.ShowImage(splash)
        
        # Business logic (non blocking)
        angles, status = receive_arm_angles()
        if status == "success":
            dog.motor([51, 52, 53], angles)
        if check_exit_buttons():
            break
        time.sleep(0.1)

host_mode(): The main business logic is the host mode control dog.unload_motor(5): Unload the robot arm servo on the robot dog client_mode(): The main business logic is the slave mode control receive_arm_angles(): Receives the slave mode robot arm angles sent by the host mode, and then drives the dog.motor function to control the robot arm to reach the angle

Notes:

  1. This experiment requires two or more dogs to run properly
  2. To exit this experiment, it is best to use the button in the lower left corner of the screen. Other exit methods will cause the slave dog robot arm to be unloaded, causing other robot arm-related routines to run and the robot arm to not move normally.

 

Group Control Performance
Introduction to OpenCV

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