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MicroROS Robot📖
01. Introduction
  • 0.Unpacking and reviewing video
  • 1. ReadMe - learning route
  • 2. Introduction to lidar
  • 3. Introduction to microROS control board
  • 4. FAQ
  • 5. About charging
02. Assembly course
  • Assembly steps
03. Preparation
  • First Trial
  • 1. Write firmware
  • 2. How to install and use VM
  • 3. microROS control board configuration
  • 4. Connect to microROS agent
04. VM Remote control course
  • 1. VM keyboard remote control
  • 2. VM handle remote control
05.ROS-WiFi module configuration
  • 0. Serial port configuration WiFi instructions
  • 1.Module usage in car(ReadMe)
  • 2.Connection module proxy
  • 3.Camera picture correction(ReadMe)
  • 4.Calibrate servo PTZ(ReadMe)
06.ROS+OpenCV course
  • 1.OpenCV Getting started
  • 2.Geometric transformation
  • 3.Image processing and drawing text line segments
  • 4.Image beautification
07.Mediapipe course
  • 1. Hand detection
  • 2. Posture detection
  • 3. Overall inspection
  • 4. Face detection
  • 5. Face recognition
  • 6. Facial effects
  • 7. 3D object recognition
  • 8. Brush
  • 9. Finger control
  • 10. Gesture recognition
08. Robot basic course
  • 1. Robot information release
  • 2. Robot keyboard control
  • 3. Robot handle control
  • 4. Robot state estimation
  • 5. Linear speed calibration
  • 6. Angular velocity calibration
  • 7. Robot URDF model
09. Lidar course
  • 1. Lidar avoid
  • 2. Lidar following
  • 3. Lidar guard
  • 4. Lidarpatrol
  • 5. Gmapping mapping
  • 6. Cartographer mapping
  • 7. Navigation2 navigation avoid
  • 8. ROS Robot APP mapping
  • 9. ROS Robot APP navigation
10. Multi-machine course
  • 1. Multi-machine handle control
  • 2.Multi-machine keyboard control
  • 3. Multi-machine navigation
11.Robot visual interaction
  • 1. Color tracking
  • 2. Object recognition and tracking
  • 3.Face recognition tracking
  • 4.Autonomous driving line patrol
  • 5.QR code motion control
  • 6.Gesture control car movement
  • 7.Palm control car movement
  • 8.Gesture control car action group
  • 9.Palm control 2DOF servo PTZ
12. Linux basic course
  • 1. Introduction to Linux system
  • 2. Ubuntu file system
  • 3. Ubuntu common commands
  • 4. Ubuntu common editors
  • 5. Ubuntu software operation commands
  • 6. Virtual machine installation
  • 7. SSH remote control
  • 8. VNC remote control
  • 9. Remote file transfer
  • 10. Driver library and communication
  • 11. Static IP and hotspot mode
  • 12. Bind device ID
  • 13. Capacity expansion and resource allocation
  • 14. Update system software source
  • 15. set root password
  • 16. sudo free password
  • 17. Connect to WiFi network
  • 18. View system version
  • 19. Customized service management
  • 20. Back up system image
13. Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. In-depth understand and publishing images
  • 4. Hardware interaction and data processing
  • 5. Enter robot 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
15. microROS control board development environment
  • 1. Introduction to microROS control board
  • 2. Set up ESP32-IDF development environment
  • 3. ESP32-IDF configuration tool
  • 4. Install ESP32-microros components
  • 5. Install and start microROS agent
  • 6. Flash-tool burning firmware
16. ESP32 basic course
  • 1. Turn on the LED light
  • 2. Button function
  • 3. Drive the buzzer
  • 4. Serial communication
  • 5. Battery voltage detection
  • 6. Drive PWM servo
  • 7. Drive motor
  • 8. Read motor encoder data
  • 9. PID controls car speed
  • 10. Read IMU data
  • 11. Read radar data
  • 12. Flash access data
  • 13. Partition table and memory
  • 14. Bluetooth communication
  • 15. WiFi networking
  • 16. Robot kinematics analysis
  • 17. ROS-WiFi camera module
17. microros basic course
  • 1. Publish topic
  • 2. Subscribe topic
  • 3. Multi-topic subscribe and publish
  • 4. Subscribe buzzer topics
  • 5. Subscribe PWM servo topics
  • 6. Subscribe speed control topics
  • 7. Release speed topic
  • 8. Release IMU data topic
  • 9. Publish lidar data topics
  • 10. Customized transmission method
Download
  • Mapping_APP(iOS_Android)
  • Code and firmware
  • Hardware info and driver software
  • VM image file
  • Instruction manual
  • SystemFile_RPi
  • SystemFile_JetsonNANO
  • 3D_Model_File
  • ROS2_Basic_VM
Download ZIP

Welcome to MicroROS Robot repository

9.Palm control 2DOF servo PTZ

Palm control 2DOF servo PTZ

Note: The VM and ROS-wifi image transfer module must be consistent with the microROS control board ROS_DOMAIN_ID and set the value to 20. You can check [MicroROS control board Parameter configuration] to set the microROS control board ROS_DOMAIN_ID. Check the tutorial Connecting to MicroROS Agents to see if the ids are the same.

1、synopsis

MediaPipe is an open source and data stream processing machine learning application development framework developed by Google. It is a graph-based data processing pipeline for building data sources that use many forms, such as video, audio, sensor data, and any time series data. MediaPipe is cross-platform and can run on embedded platforms (Raspberry PI, etc.), mobile devices (iOS and Android), workstations and servers, and supports GPU acceleration on mobile. MediaPipe provides cross-platform, customizable ML solutions for live and streaming media.

2、Program specification

After the program starts, after the camera captures the image, the two-dimensional head of the car will follow the movement of the palm in the picture. The moving speed of the palm movement here should not be too fast, otherwise the image processing can not keep up, which will cause a lag.

2.1、Program code reference path

/home/yahboom/yahboomcar_ws/src/yahboom_esp32ai_car/yahboom_esp32ai_car/control_shape.py

3、Program initiation

3.1、Start command

Terminal input,

xxxxxxxxxx
ros2 run yahboom_esp32ai_car control_shape 

If the Angle of the camera is not at this Angle, please press CTRL+C to end the program and run again, this is because the network delay causes the Angle of sending the steering gear to lose packets image-202405100001

If the camera picture image appears upside down, you need to see 3. Camera picture correction (must see) document itself correction, the experiment is no longer described.

After the function is turned on, the two-dimensional head of the car will follow the palm movement.

image-20240125184857513

4、Code parsing

4.1、control_shape.py

xxxxxxxxxx
/home/yahboom/yahboomcar_ws/src/yahboom_esp32ai_car/yahboom_esp32ai_car/control_shape.py
  • Code parsing

    1)、Import important library files

    xxxxxxxxxx
    from media_library import *

    2)、Check the hand, get finger information

    ​x
    frame, lmList, bbox = self.hand_detector.findHands(frame)
    
    
    angle = self.hand_detector.ThumbTOforefinger(lmList)
    
    

    3)、Calculate the Angle of each steering gear

    xxxxxxxxxx
    point_x = lmList[9][1]
    point_y = lmList[9][2]
    if point_y >= 200: self.y -= 1
    elif point_y <= 100: self.y += 1
    
    
    if point_x >= 420: self.x -= 1
    elif point_x <= 300: self.x += 1
    
    
    if self.x <= -45: self.x = -45
    elif self.x >= 45: self.x=45
    if self.y <= -90: self.y = -90
    elif self.y >=40: self.y = 40

    It can be seen that indexX and indexY are the coordinates of the center point of the picture frame, and the Angle of rotation of the steering gear should be calculated through judgment. The parameters of each Angle calculation method are calibrated according to the actual rotation Angle and the visual range of the camera.

4.2、Flow chart

image-20240201150432326

 

Gesture control car action group
Introduction to Linux system

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