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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。

9. Gesture following

9. Gesture following

9. Gesture following9.1. Experimental objectives9.2. Experimental code9.3. Experimental phenomenon

9.1. Experimental objectives

Previously, we introduced the use of MediaPipe to implement gesture recognition. In this section, we use MediaPipe to combine gesture recognition with the control of the microphone wheel and the gimbal to achieve the function of the car following the hand and controlling the movement of the car with gestures

9.2. Experimental code

Source code path:

/home/pi/project_demo/08.AI_Visual_Interaction_Course/09_Gesture_follows/09_Gesture_follows.ipynb

​x
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 *
import cv2
import ipywidgets.widgets as widgets
import time
import sys
import math
from Raspbot_Lib import Raspbot
import threading
​
​
speed = 25
image_widget = widgets.Image(format='jpeg', width=640, height=480)
xxxxxxxxxx
global target_valuex
target_valuex = 1500
global target_valuey
target_valuey = 850
​
​
bot = Raspbot()
​
# 初始化云台 Init Servo
target_servox = 90
target_servoy = 60
def servo_reset():
    bot.Ctrl_Servo(1,target_servox)
    bot.Ctrl_Servo(2,target_servoy)
servo_reset()
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import PID
direction_pid = PID.PositionalPID(0.9, 0, 0.2)
yservo_pid = PID.PositionalPID(0.9, 0.2, 0.01)
​
from gesture_action import handDetector
hand_detector = handDetector(detectorCon=0.8)
cap = cv2.VideoCapture(0)
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# 线程功能操作库 Thread function operation library
import inspect
import ctypes
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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def Gesture_follow():
    try:
        while True:
            global bot
            ret, frame = cap.read()
            img_height, img_width, _ = frame.shape
            hand_detector.findHands(frame, draw=False) 
            if len(hand_detector.lmList) != 0:
                # 转向控制部分
                # Turning control section
                # MediaPipe中, 手部最中心的指关节的编号为9
                # In MediaPipe, the index of the central finger joint is 9
                x,y = hand_detector.findPoint(9)
                cv2.circle(frame,(int(x),int(y)),5,(0,255,255),10)
                # 在x轴上控制麦轮
                # Control the mouse wheel on the x-axis
                direction_pid.SystemOutput = x
                direction_pid.SetStepSignal(int(img_width/2))
                direction_pid.SetInertiaTime(0.01, 0.05)
                target_valuex = int(direction_pid.SystemOutput) 
    
                # 在y轴上控制云台, 摄像头中心与指关节9在竖直方向的差值<25时不调节,减少抖动
                # Control the pan/tilt in the y-axis; if the difference between the camera center and finger joint 9 in the vertical direction is <25, do not adjust to reduce jitter
                if math.fabs(int(img_height/2) - y) > 25:
                    yservo_pid.SystemOutput = y
                    yservo_pid.SetStepSignal(int(img_height/2))
                    yservo_pid.SetInertiaTime(0.01, 0.05)
                    target_valuey = int(850+yservo_pid.SystemOutput)
                    target_servoy = int((target_valuey-500)/10)                    
                    if target_servoy > 110:
                        target_servoy = 110
                    if target_servoy < 0:
                        target_servoy = 0        
                    bot.Ctrl_Servo(2, target_servoy)
    
                # 前进控制部分
                # Forward control section
                finger_number = hand_detector.get_gesture()
                finger_str=f"Number:{finger_number}"
    
                # 手势 0 控制小车停止
                # Gesture 0 controls the robot to stop
                if(finger_number == "Zero"):
                    stop_robot()
                else:
                    if -40 < target_valuex < 40:
                        target_valuex = 0   
                    move_param_forward(speed, target_valuex) 
            else:
                stop_robot()
            try:
                image_widget.value = bgr8_to_jpeg(frame)
            except:
                continue
    finally:
        stop_robot()
        cap.release()
        del bot
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display(image_widget)
thread1 = threading.Thread(target=Gesture_follow)
thread1.daemon=True
thread1.start()

9.3. Experimental phenomenon

After the code block is run, place the hand within the visible range of the car camera. When any gesture other than gesture "0" is made, the car will track the movement of the hand center point. When the gesture "0" is made, the car will not follow the hand movement

Track map Autopilot(purchased separately)
Voice control car movement

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