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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。

2. Color follows

2. Color follows

2. Color follows

2. Color follows2.1. Experimental Objectives2.2. Experimental Code2.3. Experimental phenomenon

2.1. Experimental Objectives

Previously, we used the color object to track the camera image at different x and y positions through the gimbal. Next, we can modify it based on this. The x direction is changed to follow the left and right movement of the vehicle body. Then, we control the forward movement according to the size of the recognized image circumscribed circle. The two are superimposed to control the overall movement of the car motor.

2.2. Experimental Code

Source code path:

/home/pi/project_demo/08.AI_Visual_Interaction_Course/02.Color_follows/02_Color_follows.ipynb

import sys
sys.path.append('/home/pi/project_demo/lib')
#导入麦克纳姆小车驱动库 Import Mecanum Car Driver Library
from McLumk_Wheel_Sports import *
sys.path.append('/home/pi/software/oled_yahboom/')
from yahboom_oled import *
# 创建oled对象 Create an oled object
oled = Yahboom_OLED(debug=False)
​x
#bgr8转jpeg格式 bgr8 to jpeg format
import enum
import cv2

def bgr8_to_jpeg(value, quality=75):
    return bytes(cv2.imencode('.jpg', value)[1])
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#显示摄像头组件 Display camera components
import traitlets
import ipywidgets.widgets as widgets
from IPython.display import display
import time
# 线程功能操作库 Thread function operation library
import threading
import inspect
import ctypes
import numpy as np

image_widget = widgets.Image(format='jpeg', width=640, height=480)
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def _async_raise(tid, exctype):
    """raises the exception, performs cleanup if needed"""
    tid = ctypes.c_long(tid)
    if not inspect.isclass(exctype):
        exctype = type(exctype)
    res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(exctype))
    if res == 0:
        raise ValueError("invalid thread id")
    elif res != 1:
        # """if it returns a number greater than one, you're in trouble,
        # and you should call it again with exc=NULL to revert the effect"""
        ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, None)
        
def stop_thread(thread):
    _async_raise(thread.ident, SystemExit)
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image = cv2.VideoCapture(0)

image.set(3, 320)
image.set(4, 240)
image.set(5, 30)  #设置帧率 Setting the frame rate
# image.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter.fourcc('M', 'J', 'P', 'G'))
# image.set(cv2.CAP_PROP_BRIGHTNESS, 62) #设置亮度 -64 - 64  0.0 Set Brightness -64 - 64 0.0
# image.set(cv2.CAP_PROP_CONTRAST, 63) #设置对比度 -64 - 64  2.0 Set Contrast -64 - 64 2.0
# image.set(cv2.CAP_PROP_EXPOSURE, 4800) #设置曝光值 1.0 - 5000  156.0  Set the exposure value 1.0 - 5000 156.0
ret, frame = image.read()

# from picamera2 import Picamera2, Preview
# import libcamera
# picam2 = Picamera2()  
# camera_config = picam2.create_preview_configuration(main={"format":'RGB888',"size":(320,240)})
# camera_config["transform"] = libcamera.Transform(hflip=1, vflip=1)
# picam2.configure(camera_config) 
# # picam2.stop_preview() #停止相机预览,防止占用资源,从而开启相机失败 Stop camera preview to prevent resources from being occupied, which may cause camera startup failure
# # picam2.start_preview(True) #开启相机预览  Open camera preview
# picam2.start() 
# frame = picam2.capture_array()

image_widget.value = bgr8_to_jpeg(frame)
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global g_mode
g_mode = 0
global color_x, color_y, color_radius
color_x = color_y = color_radius = 0
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global color_lower
#color_lower = np.array([0, 43, 46])
global color_upper
#color_upper = np.array([10, 255, 255])
color_lower = np.array([0,70,72])
color_upper = np.array([7, 255, 255])
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Redbutton = widgets.Button(     
    value=False,     
    description='red',     
    disabled=False,     
    button_style='', # 'success', 'info', 'warning', 'danger' or ''     
    tooltip='Description',     
    icon='uncheck' )
Greenbutton = widgets.Button(     
    value=False,     
    description='green',     
    disabled=False,     
    button_style='', # 'success', 'info', 'warning', 'danger' or ''     
    tooltip='Description',     
    icon='uncheck' )
Bluebutton = widgets.Button(     
    value=False,     
    description='blue',     
    disabled=False,     
    button_style='', # 'success', 'info', 'warning', 'danger' or ''     
    tooltip='Description',     
    icon='uncheck' )
Yellowbutton = widgets.Button(     
    value=False,     
    description='yellow',     
    disabled=False,     
    button_style='', # 'success', 'info', 'warning', 'danger' or ''     
    tooltip='Description',     
    icon='uncheck' )
Orangebutton = widgets.Button(     
    value=False,     
    description='orange',     
    disabled=False,     
    button_style='', # 'success', 'info', 'warning', 'danger' or ''     
    tooltip='Description',     
    icon='uncheck' )
Closebutton = widgets.Button(     
    value=False,     
    description='close',     
    disabled=False,     
    button_style='', # 'success', 'info', 'warning', 'danger' or ''     
    tooltip='Description',     
    icon='uncheck' )
output = widgets.Output()

def ALL_Uncheck():
    Redbutton.icon = 'uncheck'
    Greenbutton.icon = 'uncheck'
    Bluebutton.icon = 'uncheck'
    Yellowbutton.icon = 'uncheck'
    Orangebutton.icon = 'uncheck'
    
def on_Redbutton_clicked(b):
    global color_lower, color_upper, g_mode 
    global target_valuex, target_valuey
    ALL_Uncheck()
    b.icon = 'check'
    #color_lower = np.array([0, 43, 46])
    #color_upper = np.array([10, 255, 255])
    color_lower = np.array([0,43,89])
    color_upper = np.array([7, 255, 255])
    g_mode = 1
    with output:
        bot.Ctrl_WQ2812_ALL(1,0)#红色 red
        oled.clear()
        oled.add_line("Color_Follow", 1)
        oled.add_line("color: red", 3)
        oled.refresh()
        bot.Ctrl_Servo(1,90)
        bot.Ctrl_Servo(2,25)
        print("RedButton clicked.")

def on_Greenbutton_clicked(b):
    global color_lower, color_upper, g_mode 
    global target_valuex, target_valuey
    ALL_Uncheck()
    b.icon = 'check'
    #color_lower = np.array([35, 43, 46])
    #color_upper = np.array([77, 255, 255])
    color_lower = np.array([54,104,64])
    color_upper = np.array([78, 255, 255])
    g_mode = 1
    with output:
        bot.Ctrl_WQ2812_ALL(1,1)#绿色 green
        oled.clear()
        oled.add_line("Color_Follow", 1)
        oled.add_line("color: green", 3)
        oled.refresh()
        bot.Ctrl_Servo(1,90)
        bot.Ctrl_Servo(2,25)
        print("GreenButton clicked.")
        
def on_Bluebutton_clicked(b):
    global color_lower, color_upper, g_mode 
    global target_valuex, target_valuey
    ALL_Uncheck()
    b.icon = 'check'
    #color_lower=np.array([100, 43, 46])
    #color_upper = np.array([124, 255, 255])
    color_lower = np.array([92,100,62])
    color_upper = np.array([121, 255, 255])
    g_mode = 1
    with output:
        bot.Ctrl_WQ2812_ALL(1,2)#蓝色
        oled.clear()
        oled.add_line("Color_Follow", 1)
        oled.add_line("color: blue", 3)
        oled.refresh()
        bot.Ctrl_Servo(1,90)
        bot.Ctrl_Servo(2,25)
        print("Bluebutton clicked.")   

def on_Yellowbutton_clicked(b):
    global color_lower, color_upper, g_mode 
    global target_valuex, target_valuey
    ALL_Uncheck()
    b.icon = 'check'
    #color_lower = np.array([26, 43, 46])
    #color_upper = np.array([34, 255, 255])
    color_lower = np.array([26,100,91])
    color_upper = np.array([32, 255, 255])
    g_mode = 1
    with output:
        bot.Ctrl_WQ2812_ALL(1,3)#黄色 yellow
        oled.clear()
        oled.add_line("Color_Follow", 1)
        oled.add_line("color: yellow", 3)
        oled.refresh()
        bot.Ctrl_Servo(1,90)
        bot.Ctrl_Servo(2,25)
        print("Yellowbutton clicked.")
        
def on_Orangebutton_clicked(b):
    global color_lower, color_upper, g_mode 
    global target_valuex, target_valuey
    ALL_Uncheck()
    b.icon = 'check'
    color_lower = np.array([11, 43, 46])
    color_upper = np.array([25, 255, 255])
    g_mode = 1
    with output:
        bot.Ctrl_WQ2812_brightness_ALL(255, 48, 0)
        oled.clear()
        oled.add_line("Color_Follow", 1)
        oled.add_line("color: orange", 3)
        oled.refresh()
        bot.Ctrl_Servo(1,90)
        bot.Ctrl_Servo(2,25)
        print("Orangebutton clicked.")
        
def on_Closebutton_clicked(b):  
    global g_mode 
    ALL_Uncheck()
    g_mode = 0
    with output:
        bot.Ctrl_WQ2812_ALL(0,0)
        oled.clear()
        oled.add_line("Color_Follow", 1)
        oled.add_line("color: none", 3)
        oled.refresh()
        bot.Ctrl_Servo(1,90)
        bot.Ctrl_Servo(2,10)
        print("CloseButton clicked.")
Redbutton.on_click(on_Redbutton_clicked)
Greenbutton.on_click(on_Greenbutton_clicked)
Bluebutton.on_click(on_Bluebutton_clicked)
Yellowbutton.on_click(on_Yellowbutton_clicked)
Orangebutton.on_click(on_Orangebutton_clicked)
Closebutton.on_click(on_Closebutton_clicked)
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import PID

direction_pid = PID.PositionalPID(0.8, 0, 0.2)

yservo_pid = PID.PositionalPID(0.8, 0.4, 0.01)

speed_pid = PID.PositionalPID(1.1, 0, 0.2)
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# 定义 target_servox 和 target_servoy 在外部 Define target_servox and target_servoy externally
target_servox = 90
target_servoy = 25
def servo_reset():
    bot.Ctrl_Servo(1,90)
    bot.Ctrl_Servo(2,25)
servo_reset()
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def Color_Recongnize():
    oled.init_oled_process() #初始化oled进程 Initialize oled process
    global color_lower, color_upper, g_mode, first_read, while_cnt
    global color_x, target_servox,target_servoy,picture,speed_value
    t_start = time.time()
    fps = 0
    ret, frame = image.read()
    #frame = picam2.capture_array()
    #frame = cv2.resize(frame, (300, 300))
    frame = cv2.GaussianBlur(frame,(5,5),0) 
    first_read = 1
    while_cnt = 0
    speed=30
    time.sleep(1)
    while True:
        ret, frame = image.read()  
        #frame = picam2.capture_array()
        #frame = cv2.resize(frame, (300, 300))
        #frame = cv2.GaussianBlur(frame,(3,3),0)  
        hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
        mask = cv2.inRange(hsv,color_lower,color_upper)   
        mask = cv2.erode(mask,None,iterations=2)
        mask = cv2.dilate(mask,None,iterations=2)
        mask = cv2.GaussianBlur(mask,(5,5),0)
        cnts = cv2.findContours(mask.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[-2]
        if g_mode == 1: # 按钮切换开关 Push button switch
            if len(cnts) > 0:
                cnt = max (cnts, key = cv2.contourArea)
                (color_x,color_y),color_radius = cv2.minEnclosingCircle(cnt)

                if color_radius > 10:
                    # 将检测到的颜色用原形线圈标记出来 Mark the detected color with a prototype circle
                    cv2.circle(frame,(int(color_x),int(color_y)),int(color_radius),(255,0,255),2)  
                    direction_pid.SystemOutput = color_x
                    direction_pid.SetStepSignal(250)
                    direction_pid.SetInertiaTime(0.01, 0.05)
                    target_valuex = int(direction_pid.SystemOutput+65)
                    #print("color_x %f", color_x)                         
                    #print("target_valuex %d", target_valuex)   
                    # 将云台转动至PID调校位置 Turn the gimbal to the PID adjustment position

                    if math.fabs(180 - color_y) > 75:
                        # 输入Y轴方向参数PID控制输入 Input Y-axis direction parameter PID control input
                        yservo_pid.SystemOutput = color_y
                        yservo_pid.SetStepSignal(250)
                        yservo_pid.SetInertiaTime(0.01, 0.1)
                        target_valuey = int(1150+yservo_pid.SystemOutput)
                        target_servoy = int((target_valuey-500)/10)                         
                        #print("target_servoy %d", target_servoy)  
                        if target_servoy > 110:
                            target_servoy = 110
                        if target_servoy < 0:
                            target_servoy = 0
                        #print(target_servoy)


                    speed_pid.SystemOutput = int(color_radius)
                    speed_pid.SetStepSignal(80)
                    speed_pid.SetInertiaTime(0.01, 0.1)               
                    speed_value = int(speed_pid.SystemOutput)
                    #print("color_radius %d", color_radius)

                    if speed_value > 255:
                        speed_value = 255
                    if speed_value < 0:
                        speed_value = 0
                        
                    if(target_valuex>70):
                        rotate_left(int(speed/5))# speed
                    elif(target_valuex<-70):
                        rotate_right(int(speed/5))
                    elif(65<color_radius<90):#调试目标半径70~90 Debug target radius 70~90
                        stop_robot()
                    elif(color_radius>90):#调试目标半径90 Debug target radius 90
                        if(abs(target_valuex)<30):
                            move_backward(speed)
                    elif(20<color_radius<75):
                        if(abs(target_valuex)<30):
                            move_forward(speed_value)
                    else:stop_robot()

                    bot.Ctrl_Servo(2,target_servoy)
                
                else:
                    stop_robot()
                    
Color tracking
QR code recognition to control movement

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