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Raspberry Pi 4B📖
1.Preparation before use
  • 1.1 Download image
  • 1.2 Write image into SD card
  • 1.3 Start up Raspberry Pi
  • 1.4 Linux common commands
  • 1.5 Precautions
2.Basic course
  • 2.1 Log into Raspberry Pi system
  • 2.2 Change password and root account
  • 2.3 Remote transfer file
  • 2.4 Backup image file
  • 2.5 Fixing Raspberry Pi IP
  • 2.6 Set screen keep on
  • 2.7 Get Pi temperature
  • 2.8 Connect WIFI
  • 2.9 Modify Pi time
  • 2.10 Set the boot self-starting program
3.Expand course
  • 3.1 Serial port communicates with external devices
  • 3.2 2.Serial port login Pi
  • 3.3 Configured as a router
  • 3.4 Install Jupyter Lab
  • 3.5 Install Jupyter Widgets
  • 3.6 More Detail for Widgets
  • 3.7 Install OpenCV
  • 3.8 Install Tensorflow
4.Programming course
C language
  • 1.Development environment
  • 2.Print Hello World
  • 3.Pin output level
  • 4.Read pin level
  • 5.PWM output
Python language
  • 1.Development environment
  • 2.Print basic usage
  • 3.Pin output level
  • 4.Read pin level
  • 5.PWM output
5.AI vision course
A.Getting started with OpenCV
  • 6.Picture Rotation
  • 1.Introduction of OpenCV
  • 2.OpenCV image read and display
  • 3.OpenCV image write
  • 4.OpenCV image quality
  • 5.OpenCV pixel operation
B.OpenCV Geometric transformat
  • 1.Picture Zoom
  • 2.Picture Cut
  • 3.Picture Shift
  • 4.Picture Mirroring
  • 5.Affine Map
  • 7.Perspective Transformation
C.OpenCV picture processing
  • 1.Grayscale processing
  • 2.Image Binarization
  • 3.Edge detection
  • 4.Drawing line segment
  • 5.Drawing rectangle circle
  • 6.Drawing text picture
D.OpenCV image beautification
  • 1.Histogram of color pictures
  • 2.Histogram equalization
  • 3.Image restoration
  • 4.Brightness enhancement
  • 5.Skin whitening
  • 6.Gaussian mean filtering
  • 7.Median filtering
F.AI Advanced Course (Ubuntu system)
  • 1. QR code
  • 2. Human posture estimation
  • 3. Target detection
  • 4. Mediapipe development
  • 5. yolov4-tiny
E.Install TensorFlow
  • Install TensorFlow
6.ROS1 coursenew
Basic Course
  • 1.ROS introduction
  • 2.Project file structure
  • 3.Common commands and tools
  • 4.Publisher
  • 5.Subscribers
  • 6.Customize topic messages and use
  • 7.Client
  • 8.Server
  • 9.Custom service messages and usage
  • 10.TF release and monitoring
Visual Image Processing
  • 1. AR vision
  • 2. AR QR code
  • 3. ROS+Opencv foundation
  • 4. ROS+Opencv application
  • 5. MediaPipe development
7.ROS2 coursenew
Docker Course
  • 1.Overview and installation
  • 2.Common commands
  • 3.Understand and publish images
  • 4.Hardware interaction data processing
  • 5.Enter docker container
  • 6.Update docker images
Basic Course
  • 1.Introduction to ROS2
  • 2.Commands and tools
  • 3.ROS2 Topic communications
  • 4.ROS2 service communications
  • 5.ROS2launch file starts
OpenCV Course
  • 1.OpenCV Basic Course
  • 2.ROS+opencv application
  • 3.QR code recognition
  • 4.AR Vision
  • 5.Mediapipe
8.Accessories installation
  • 1. Installation of heat sink
  • 2. Wiring of cooling fan
  • 3. Double fan armor case Installation
  • 4. Argon NEO aluminum case installation
  • 5. Argon ONE aluminum alloy case installation
  • 6. Metal shell with built-in fan installation
  • 7. Acrylic case with cooling fan installation
  • 8. White-red ABS protective case installation
Download
  • Tools
  • C_code
  • Python code
  • ROS System
Download ZIP

Welcome to Raspberry Pi 4B repository

8.Server

8 Server

8 Server 8.1 C++ language implementation 8.1.1 Implementation steps 8.1.2 Switch to the ~/catkin_ws/src/learning_server/src directory, create a new .cpp file, name it turtle_vel_command_server, and paste the code below into it 8.2 Python language implementation 8.2.1 Switch to the ~/catkin_ws/src/learning_server directory, create a new script folder, cut it in, create a new py file, name it turtle_vel_command_server, and paste the code below into it

In the last lesson, we talked about the client requesting the service, and then the server providing the service. In this lesson, we will talk about how the server implements the service.

8.1 C++ language implementation

8.1.1 Implementation steps

  1. initialize the ROS node
  2. create a Server instance
  3. wait for the service request in a loop, enter the callback function
  4. complete the functional processing of the service in the callback function, and feedback the response data

8.1.2 Switch to the ~/catkin_ws/src/learning_server/src directory, create a new .cpp file, name it turtle_vel_command_server, and paste the code below into it

turtle_vel_command_server.cpp

​x
/** 
 * This routine will execute the /turtle_vel_command service, service data type std_srvs/Trigger 
 */ 
 
#include <ros/ros.h> 
#include <geometry_msgs/Twist.h> 
#include <std_srvs/Trigger.h> 

ros::Publisher  turtle_vel_pub; 
bool  pubvel  =  false; 

// service callback function, input parameter req, output parameter res 
bool  pubvelCallback(std_srvs::Trigger::Request   & req, 
                    std_srvs::Trigger::Response  & res) 
{ 
    pubvel  =  !pubvel; 

        ROS_INFO("Do you want to publish the vel?: [%s]", pubvel == true ? "Yes" : "No"); // print client request data 

    // set feedback data 
    res.success  =  true; 
    res.message  =  "The status is changed!"; 

    return  true; 
} 

int  main(int  argc, char  ** argv) 
{ 
    
    ros::init(argc, argv, "turtle_vel_command_server"); 

  
    ros::NodeHandle  n; 

    // Create a server named /turtle_vel_command and register the callback function pubvelCallback 
    ros::ServiceServer  command_service  =  n.advertiseService("/turtle_vel_command", pubvelCallback); 

    // Create a Publisher, publish a topic named /turtle1/cmd_vel, the message type is geometry_msgs::Twist, and the queue length is 8 
    turtle_vel_pub  =  n.advertise < geometry_msgs::Twist >("/turtle1/cmd_vel", 8); 

    ros::Rate  loop_rate(10); // set the frequency of the loop 

    while(ros::ok()) 
    { 
        
        ros::spinOnce(); // View the callback function queue once 
        
        // Judging that pubvel is True, issue the small turtle speed command 
        if(pubvel) 
        { 
            geometry_msgs::Twist vel_msg; 
            vel_msg.linear.x  =  0.6; 
            vel_msg.angular.z  =  0.8; 
            turtle_vel_pub.publish(vel_msg); 
        } 

        loop_rate.sleep(); //Delay according to the loop frequency 
    } 

    return  0; 
} 
  1. program flow chart

image-20220427143845105

  1. configure in CMakelist.txt, under the build area, add the following content
xxxxxxxxxx
add_executable(turtle_vel_command_server src/turtle_vel_command_server.cpp) 
target_link_libraries(turtle_vel_command_server ${catkin_LIBRARIES}) 
  1. Compile the code in the workspace directory
xxxxxxxxxx
cd ~/catkin_ws 
catkin_make 
source devel/setup.bash #Environment      variables need to be configured, otherwise the system cannot find the running program 
  1. run the program
xxxxxxxxxx
roscore 
rosrun turtlesim turtlesim_node 
rosrun learning_server turtle_vel_command_server 
  1. Screenshot of running effect

image-20220225114532861

  1. program description

First, after running the little turtle node, you can enter rosservice list in the terminal to see what the current services are. The results are as follows

image-20220219112052144

Then, we run the turtle_vel_command_server program, and then enter the rosservice list, we will find an additional turtle_vel_command_server, as shown in the following figure

image-20220225114746807

Then, we call this service by entering rosservice call /turtle_vel_command_server in the terminal, and we will find that the small turtle moves in a circle. If the service is called again, the small turtle stops moving. This is because in the service callback function, we invert the value of pubvel, and then feed it back. The main function will judge the value of pubvel. If it is True, it will issue a speed command, and if it is False, no command will be issued.

8.2 Python language implementation

8.2.1 Switch to the ~/catkin_ws/src/learning_server directory, create a new script folder, cut it in, create a new py file, name it turtle_vel_command_server, and paste the code below into it

turtle_vel_command_server.py

xxxxxxxxxx
# !/usr/bin/env python 
# -*- coding: utf-8 -*- 
# This routine will execute the /turtle_command service, service data type std_srvs/Trigger 

import  rospy 
import  thread, time 
from  geometry_msgs.msg  import  Twist 
from  std_srvs.srv  import  Trigger, TriggerResponse 

pubvel  =  False; 
turtle_vel_pub  =  rospy.Publisher('/turtle1/cmd_vel', Twist, queue_size = 8) 

 def pubvel_thread():     
    while  True : 
        if  pubvel : 
            vel_msg  =  Twist() 
            vel_msg.linear.x  =  0.6 
            vel_msg.angular.z  =  0.8 
            turtle_vel_pub.publish(vel_msg) 
            
        time.sleep(0.1) 

 def pubvelCallback(req): 
    global  pubvel 

    pubvel  =  bool(1 - pubvel) 

    rospy.loginfo("Do you want to publish the vel?[%s]", pubvel) # Display request data 

    return  TriggerResponse(1, "Change state!") # Feedback data 

 def turtle_pubvel_command_server(): 
    
    rospy.init_node('turtle_vel_command_server') # ROS node initialization 

    # Create a server named /turtle_command and register the callback function pubvelCallback 
    s  =  rospy.Service('/turtle_vel_command', Trigger, pubvelCallback) 

    # loop waiting for the callback function 
    print  "Ready to receive turtle_pub_vel_command." 

    thread.start_new_thread(pubvel_thread,()) 
    rospy.spin() 

if  __name__  ==  "__main__" : 
    turtle_pubvel_command_server() 
  1. program flow chart

image-20220427143957140

  1. run the program
xxxxxxxxxx
roscore 
rosrun turtlesim turtlesim_node 
rosrun learning_server turtle_vel_command_server.py 
  1. The program operation effect and program description are consistent with the effect realized by C++.
Client
Custom service messages and usage

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