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RDK X3 Robot📖
01. About RDK-X3-Robot
1. Instructions
  • 1. Introduction
  • 2. FAQ
  • 3. Battery and charger use precautions
  • 4.TF card expand capacity
2. Common problem analysis
02. Assembly video
  • Part1-Install Motor
  • Part2-Install Battert Fixing Column
  • Part3-Install Motor Coupling
  • Part4-Install Mecanum wheel
  • Part5-Install Expansion Board
  • Part6-Wiring Show
  • Part7-Install Main Control Board
  • Part8-Install Car Top Plate and Antenna
  • Part9-Install OLED Screen
  • Part10-Install Depth Camera(Optional)
  • Part11-Install OLED Screen
  • Part12-Install HD Camera
  • Part13-Install Top Plate
  • Part14-Install Right Side Plate
  • Part15-Motor Wiring Show
  • Part16-lnstall Car Body
  • Part17-Install Battery
  • Part18-Install Lidar
03. Remote control tutorial
  • 1. The phone APP remote tutorial
  • 2. USB wireless controller remote tutorial
04. ROS functional tutorial
  • 1. Introduction of extension board
  • 2. Set up STM32 development environment
  • 3. Key control buzzer sound
  • 4. FreeRTOS application
  • 5. Serial communication
  • 6. SBUS model remote control
  • 7. CAN bus communication
  • 8. RGB color light strip
  • 9. Timer interrupt control PWM servo
  • 10. Control serial steering gear
  • 11. Nine-axis attitude sensor to obtain data
  • 12. Control motor forward and reverse
  • 13. The timer captures encoder data
  • 14. Theory of robot kinematics analysis
  • 15. PID control robot motion
05. Basic control tutorial
  • 1. Update the firmware of the expansion module
  • 2. Install the Python driver library
  • 3. Set the type of bottom car
  • 4. Open and close the APP program control
  • 5. Turn hotspot mode on and off
  • 6. The buzzer blows
  • 7. Control the motor forward and reverse
  • 8. Control robot movement
  • 9. OLED display
  • 10. Control fan and lamp effect
06. Development environment setup
  • 1. Virtual Machine
  • 2. Linux Basics
  • 3. Remote connection
  • 4. Multi-computer communication configuration
  • 5. Bind the device ID
  • 6. Image installation and backup
07. 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
08. Robot chassis control
  • 1. PID algorithm theory
  • 2. Robot information release
  • 3. Robot control
  • 4. Robot state estimation
  • 5. Robot calibration
  • 6. Robot trajectory tracking
  • 7. URDF model
09. Lidar courses
  • 1. Introduction and use of lidar
  • 2. Lidar obstacle avoidance
  • 3. Lidar following
  • 4. Lidar guard
  • 5. Patrol
  • 6. gmapping algorithm
  • 7. cartographer algorithm
  • 8. Navigation and obstacle avoidance
  • 9. App mapping and navigation
10. OpenCV courses
  • 1. Introduction to OpenCV
  • 2. OpenCV geometric transformation
  • 3. OpenCV image processing
  • 4. OpenCV image beautification
  • 5. Qr code creation and identification
11. MIPI camera course
  • 1. Camera driver
  • 2. Adjust the color HSV value
  • 3. Color recognition
  • 4. Color tracking
  • 5. Color follow
  • 6. Qr code command
  • 7. Face detection
  • 8. Object detection
  • 9. Visual Inspection -OpenCV
  • 10. Visual inspection - Deep learning
  • 11. Human tracking
  • 12. Gesture control
12. Depth Camera courses
  • 1. Use depth camera
  • 2. Calibration of camera internal reference
  • 3. ROS+OpenCV Foundation
  • 4. AR vision
  • 5. Color tracking
  • 6. Object tracking
13. Multi vehicle control
  • 1. Multi-vehicle synchronous control
  • 2. Multi-vehicle navigation
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
Download
  • RemoteCtrl_APP(iOS/Android))
  • Mapping_APP(iOS_Android)
  • Code
  • System File
  • VM_File
  • Manual
  • Software_File
  • Hardware_File
  • ROS2_Basic_VM
Download ZIP

Welcome to RDK X3 Robot repository

6. Qr code command

6. QR code instructions

6. QR code instructions6.1 Introduction to gameplay6.2 Core content analysis6.3 Gameplay operations

6.1 Introduction to gameplay

This course mainly uses the CSI camera of the RDK X3 board to obtain the picture of the camera, identify the two-dimensional code information, and control the car movement according to the two-dimensional code information.

 

6.2 Core content analysis

Import the QR code parsing library pybar

import pyzbar.pyzbar as pyzbar
from PIL import Image

If pybar is not installed, open the terminal and run the following command to install it.

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pip3 install pyzbar
sudo apt install libzbar-dev

The gray image is analyzed, and the information of two-dimensional code and image position in the image are extracted. If there is no QR code in the image, the message is None.

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def detect_qrcode(image):
    # 转为灰度图像
    # Convert to grayscale image
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    barcodes = pyzbar.decode(gray)
    for barcode in barcodes:
        # 提取二维码的数据和边界框的位置 The data of the QR code and the position of the bounding box are extracted
        (x, y, w, h) = barcode.rect
        barcodeData = barcode.data.decode("utf-8")
        barcodeType = barcode.type
        # print("[INFO] Found {} barcode: {}".format(barcodeType, barcodeData))
        car_control(barcodeData)
        return barcodeData, (x, y, w, h)
    return None, (0, 0, 0, 0)

Control the car movement according to the string command of info. car_speed is the speed of the car, which can be adjusted according to actual needs.

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car_speed = 0.3
def car_control(info):
    # print(info)
    global g_car_runtime
    if g_car_runtime >= 0:
        return
    g_car_runtime = 100
    if info == "forward": # 前进forward
        g_car.set_car_run(1, car_speed*100)        
    elif info == "back": # 后退back
        g_car.set_car_run(2, car_speed*100)       
    elif info == "left": # 左平移left
        g_car.set_car_run(3, car_speed*100)
    elif info == "right": # 右平移right
        g_car.set_car_run(1, car_speed*100)
    elif info == "turnleft": # 左旋转turnleft
        g_car.set_car_run(5, car_speed*100)
    elif info == "turnright": # 右旋转turnright
        g_car.set_car_run(6, car_speed*100) 
    elif info == "stop": # 停车stop
        g_car.set_car_run(7, 0)
        g_car_runtime = -1

Define a task_timeout task to stop the car automatically and not execute other QR code commands during the car movement. g_car_runtime is measured in 10 milliseconds. When g_car_runtime is greater than 0, it automatically decreases by 1 every 10 seconds. When g_CAR_Runtime expires, it automatically stops.

​x
g_car_runtime = -1

def task_timeout():
    global g_car_runtime
    while True:
        if g_car_runtime > 0:
            print("g_car_runtime:", g_car_runtime)
            g_car_runtime = g_car_runtime - 1
        elif g_car_runtime == 0:
            print("auto stop")
            g_car.set_car_run(7, 0)
            g_car_runtime = -1
        time.sleep(.01)

 

6.3 Gameplay operations

Open the jupyterLab client and find the code path:

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/root/sunriseRobot/Samples/2_AI/06_qrcode_movement/qrcode_movement.ipynb

Click Run All Cells, and then drag to the bottom to see the generated controls.

image-20220810163917767

Click the Start button below to open the QR code and execute the command. At present, the QR code that can be recognized in the routine is QRCode, and the information is "forward" for forward, "back" for backward, "left" for left translation, "right" for right translation, "turnleft" for left rotation, "turnright" for right rotation, and "stop" for stop.

image-20230602155251468

Finally click the Close_Camera button to close the camera.

Color follow
Face detection

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