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Raspbot V2📖
1.About Raspbot V2
  • 1. First trial
  • 2. Expansion board interface distribution
  • 3. About battery and charging
  • 4. Install servo PTZ
  • 5.Servo Gimbal Installation
  • 6. Important Notes (Read Before Starting)
2.Assembly
  • Installation Video
3.Car basic course
  • 0. Preparation before development
  • 1.Buzzer control
  • 2.Key reading
  • 3.RGB control
  • 4.Servo control (PTZ control)
  • 5.Motor control
  • 6.Printing ultrasonic data
  • 7.Tracking module status printing
  • 8.IR control key value printing
4.Car motion control course
  • 0.Mecanum wheel motion principle
  • 1.Car vertical movement
  • 2.Car diagonal movement
  • 3.Car sideways movement
  • 4.Car rotation movement
  • 5.Car patrol
5.Car advanced courses
  • 1.Infrared patrol car
  • 2.Ultrasonic avoid
  • 3.Ultrasonic follow
  • 4.Infrared tracking+ ultrasonic avoid
  • 5.Restricting
  • 6.Infrared remote control car
6.OpenCV courses
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 text line drawing
  • 1. Grayscale processing
  • 2. Image Binarization
  • 3. Edge Detection
  • 4. Line drawing
  • 5. Rectangle and circle drawing
  • 6. Text and image drawing
D. Image beautification
  • 1. Color Image Histogram
  • 2. Histogram Equalization
  • 3. Image repair
  • 4. Brightness enhancement
  • 5. Smooth and whiten
  • 6. Gaussian mean filtering
  • 7. Median Filter
E. Machine Learning
  • 1. KNN
  • 2. SVM
7.AI vision recognition course
  • 1.Camera driver tutorial
  • 2.Color recognition
  • 3.HSV value test
  • 4.Object Recognition
  • 5.QR code recognition
  • 6.Face recognition
  • 7.License Plate Recognition
  • 8. Human Pose Estimation
  • 9. Target detection
  • 10.yolov5-lite
  • 11. Gesture Recognition
  • 12. Face Detection
  • 13. Face effects
  • 14. 3D Object Recognition
  • 15. Paintbrush
  • 16. Finger control
8.AI vision interaction module
  • 1. Color tracking
  • 2. Color follows
  • 3. QR code recognition to control movement
  • 4. Face tracking
  • 5. Face following
  • 6. Visual tracking
  • 7. Garbage identification
  • 8. Track map Autopilot(purchased separately)
  • 9. Gesture following
9.Voice control basic course(For Superior Kit)new
  • 1.Voice control car movement
  • 2.Voice control RGB light
  • 3.Voice control color recognition
  • 4.Voice control autonomous driving
  • 5.Voice control car tracking
10.AI large model knowledge(For Superior Kit)new
  • 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
  • 5.Configure AI large model(Required)
11.AI Large Model Development(For Superior Kit & Reference)new
  • 1.Register a model service provider account
  • 2. Configuring API-KEY(Optional)
  • 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
  • 9. Custom wake-up response
  • 10. Core module testing tools
12.AI large basic course(For Superior Kit)new
  • 1.Free conversation
  • 2.Text-to-picture
  • 3.Scene description
  • 4.Video description
  • 5.Intelligent action choreography
  • 6.Dual-model agent application
13.ROS2-Robot chassis control course
  • 1. Robot information release
  • 2. Robot keyboard control
  • 3. URDF Model
14.ROS2-OpenCV course
  • 1.ROS+Opencv application
  • 2. AR Vision
  • 3. Mediapipe fun gameplay
  • 4. Gesture control car movement
  • 5. Gesture control car actions
  • 6. Palm control car movement
  • 7. Palm control servo PTZ
  • 8. Visual tracking
  • 9. AprilTag code recognition
  • 10. AprilTag tag code tracking
  • 11. AprilTag tag code follow
15.Development environment course
  • 1. Introduction to Raspberry Pi 5
  • 2. Image writing and backup
  • 3. Start the Raspberry Pi 5
  • 4. Remote Access
  • 5. Remote file transfer
  • 6. Common Linux commands and use of vim editor
  • 7. Install Raspbot V2 driver library
  • 8. Jupyter Lab environment construction
  • 9. Jupyter Lab plugin installation
  • 10. Basic use of Jupyter Widgets
16.Raspberry Pi basic settings
  • 1.Update and upgrade the operating system
  • 2. Introduction to raspi-config tool
  • 3. config.txt file description
  • 4. Network Configuration
  • 5. Set display resolution and rotation
  • 6. Set screen sleep
  • 7. Get real-time temperature of RPi
  • 8. Play audio and video
  • 9. Use USB Camera
  • 10.Use MIPI camera
17.Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. Understand and publish images
  • 4. Docker data processing
  • 5. Enter docker container
18.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
Download
  • APP(iOS/Android)
  • Code
  • System_File
  • Instruction Manual
  • Hardware_Info
  • 3D_Model_File
  • ROS2_Basic_VM
Download ZIP

Welcome to Raspbot V2 repository

当製品の日本語版マニュアル資料は、こちらからご取得ください。

1.Infrared patrol car

1.Infrared patrol car

1.Infrared patrol car1. Learning objectives2. Experimental preparation3. Implementation principle4. Code Analysis5. Experimental results

1. Learning objectives

By combining the four-way line patrol module with the car, the car can patrol the black line.

2. Experimental preparation

  1. The car wiring has been installed
  2. Debug the four-way patrol module. Adjust the knob of the four-way tracking module so that the indicator light is on when encountering a black line; when it is not a black line, the indicator light is off.

3. Implementation principle

When detecting tracks of different shapes, the status of the four-way patrol sensor is as shown in the figure below. Control the car to perform different movements according to the sensor status.

4. Code Analysis

Source code path:

/home/pi/project_demo/05.Comprehensive_gameplay/1.infrared_patrol_line.ipynb

​x
import sys
sys.path.append('/home/pi/project_demo/lib')
#Import Mecanum Car Driver Library
from McLumk_Wheel_Sports import *

speed =30#30
try:
while True:
# Read line sensor data from I2C
track_data = bot.read_data_array(0x0a, 1)
track = int(track_data[0])

# Analyze the status of the line patrol sensor
x1 = (track >> 3) & 0x01
x2 = (track >> 2) & 0x01
x3 = (track >> 1) & 0x01
x4 = track & 0x01
"""
X2 X1 X3 X4
| | | |
L1 L2 R1 R2
"""
lineL1=x2
lineL2=x1
lineR1=x3
lineR2=x4

if lineL1 == 0 and lineL2 == 0 and lineR1 == 0 and lineR2 == 0: # All black, speed up
print("1")
print(lineL1,lineL2,lineR1,lineR2)
move_forward(int(speed))
elif( (lineL2 == 0 or lineL1 == 0) and lineR2 == 0):#Right acute angle: right big bend, 0 means black line is detected
print("2")
print(lineL1,lineL2,lineR1,lineR2)
rotate_right(speed)
time.sleep(0.05)
elif lineL1 == 0 and (lineR2 == 0 or lineR1 == 0): # Left sharp angle or left sharp bend
print("3")
print(lineL1,lineL2,lineR1,lineR2)
rotate_left(int(speed*1.5)) # Sharp left turn
time.sleep(0.15)
elif lineL1 == 0: # Left outermost detection
print("4")
print(lineL1,lineL2,lineR1,lineR2)
rotate_left(speed) # Sharp left turn
time.sleep(0.02)
elif lineR2 == 0: # Right outermost detection
print("5")
print(lineL1,lineL2,lineR1,lineR2)
rotate_right(speed)
time.sleep(0.01)
elif lineL2 == 0 and lineR1 == 1: # The sensor on the middle black line fine-tunes the car to turn left
print("6")
print(lineL1,lineL2,lineR1,lineR2)
rotate_left(int(speed)) # Turn left
elif lineL2 == 1 and lineR1 == 0: # The sensor on the middle black line fine-tunes the car to turn right
print("7")
print(lineL1,lineL2,lineR1,lineR2)
rotate_right(int(speed)) # Turn right
elif lineL2 == 0 and lineR1 == 0: # All black, speed up
print("8")
print(lineL1,lineL2,lineR1,lineR2)
move_forward(speed)

# Wait for a while before the next test
time.sleep(0.01)

except KeyboardInterrupt:
# Ensure that all motors stop when the user interrupts the program
stop()
print("Ending")

5. Experimental results

We put the car on the patrol track and confirmed that the module knob has been adjusted. When it encounters a black line, the indicator light is on, and when it is not a black line, the indicator light is off. After running the code block, the car will patrol the black line.

Car patrol
Ultrasonic avoid

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