How to compile a node file？如何编译一个节点文件？

Ubuntu16.04，ros Kinetic

最近几次遇到的问题都是，给你一个写好的ros node文件，没有给你其他的东西，你如何编译它？

以从ros中提取rgb图像和深度图像为例，示例源代码extract_images.cpp如下：

/* Este es un nodo de ROS Indigo para guardar imagenes de /camera/depth_registered/image_rect_raw
 * y de /camera/rgb/color/image_rect_raw de un Turtlebot1 para luego procesarlas con otro programa.
 * Las de profundidad se guardan como unsigned int de 16 bits
 * y 1 canal, las de color se guardan como unsigned int de 8 bits en 3 canales.
 * Se utiliza un suscriptor sincronizado para guardar el par de imagenes que estén más
 * cercanas en el tiempo.
 * LAS IMAGENES SE GUARDAN ADONDE SE EJECUTE EL NODO.
 * ---------------------------------------------------------
 * Creado por Fabricio Emder y Pablo Aguado en el 2016 */

/* This is a ROS Indigo node for saving Turtlebot images from the /camera/depth_registered/image_rect_raw
 * and /camera/rgb/color/image_rect_raw topics, for further processing outside of the program.
 * Depth images are saved as 1 channel 16 bit unsigned int PNGs (CV_16UC1), and
 * RGB images are saved as 3 channel 8 bit unsigned int PNGs (CV_8UC3).
 * A synchronized subscriber is used, for saving the pair of images that are most closer in time.
 * THE IMAGES ARE SAVED WHEREVER THE NODE IS RUN.
 * Created by Fabricio Emder and Pablo Aguado - 2016
 * */

#include <ros/ros.h>
#include <cv_bridge/cv_bridge.h>    // OpenCV
#include <sensor_msgs/Image.h>
#include <sensor_msgs/image_encodings.h>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

#include <message_filters/subscriber.h>
#include <message_filters/synchronizer.h>

/* La política de sincronización exacta NO FUNCIONA para los topics seleccionados, ya
 * que la Kinect o sus drivers no los están publicando con la misma marca temporal.
 * Ver más en http://wiki.ros.org/message_filters
 *
 * Exact sychronization policy IS NOT WORKING for the topics used, because the kinect
 * is not publishing them with the same timestamp.
 * See more in http://wiki.ros.org/message_filters  */

//#define EXACT
#define APPROXIMATE

#ifdef EXACT
#include <message_filters/sync_policies/exact_time.h>
#endif
#ifdef APPROXIMATE
#include <message_filters/sync_policies/approximate_time.h>
#endif

using namespace std;
//using namespace sensor_msgs;
using namespace message_filters;

// Contador para la numeración de los archivos.
// Counter for filenames.
unsigned int cnt = ;

// Handler / callback
void callback( const sensor_msgs::ImageConstPtr& msg_rgb , const sensor_msgs::ImageConstPtr& msg_depth )
{
        //ROS_INFO_STREAM("Adentro del callback\n");
      cv_bridge::CvImagePtr img_ptr_rgb;
        cv_bridge::CvImagePtr img_ptr_depth;
    try{
        img_ptr_depth = cv_bridge::toCvCopy(*msg_depth, sensor_msgs::image_encodings::TYPE_16UC1);
    }
    catch (cv_bridge::Exception& e)
    {
        ROS_ERROR("cv_bridge exception:  %s", e.what());
        return;
    }
    try{
        img_ptr_rgb = cv_bridge::toCvCopy(*msg_rgb, sensor_msgs::image_encodings::TYPE_8UC3);
    }
    catch (cv_bridge::Exception& e)
    {
        ROS_ERROR("cv_bridge exception:  %s", e.what());
        return;
    }

    cv::Mat& mat_depth = img_ptr_depth->image;
        cv::Mat& mat_rgb = img_ptr_rgb->image;

        char file_rgb[];
        char file_depth[];

        sprintf( file_rgb, "%04d_rgb.png", cnt );
        sprintf( file_depth, "%04d_depth.png", cnt );

        vector<int> png_parameters;
        png_parameters.push_back( CV_IMWRITE_PNG_COMPRESSION );
        /* We save with no compression for faster processing.
         * Guardamos PNG sin compresión para menor retardo. */
        png_parameters.push_back(  ); 

        cv::imwrite( file_rgb , mat_rgb, png_parameters );
        cv::imwrite( file_depth, mat_depth, png_parameters );

        ROS_INFO_STREAM(cnt << "\n");
        ROS_INFO_STREAM("Imágenes guardadas - "
                        "Images saved\n");

        cnt++;

}

int main(int argc, char** argv)
{
    // Initialize the ROS system and become a node.
  ros::init(argc, argv, "guardar_imagenes");
  ros::NodeHandle nh;

    message_filters::Subscriber<sensor_msgs::Image> subscriber_depth( nh , "/camera/depth_registered/hw_registered/image_rect_raw" ,  );
    message_filters::Subscriber<sensor_msgs::Image> subscriber_rgb( nh , "/camera/rgb/image_rect_color" ,  );

#ifdef EXACT
    typedef sync_policies::ExactTime<sensor_msgs::Image, sensor_msgs::Image> MySyncPolicy;
#endif
#ifdef APPROXIMATE
    typedef sync_policies::ApproximateTime<sensor_msgs::Image, sensor_msgs::Image> MySyncPolicy;
#endif

  // ExactTime or ApproximateTime take a queue size as its constructor argument, hence MySyncPolicy(10)
  Synchronizer<MySyncPolicy> sync(MySyncPolicy(), subscriber_rgb, subscriber_depth );
  sync.registerCallback(boost::bind(&callback, _1, _2));

    while(ros::ok())
    {
        char c;

        ROS_INFO_STREAM("\nIngrese 'a' para guardar un par de imágenes o 'b' para guardar 300 imágenes\n"
                        "Enter 'a' to save a pair of images or 'b' to automatically save 300 images\n");
        cin.get(c);
        cin.ignore();
        c = tolower(c);
        ROS_INFO_STREAM("You entered " << c << "\n");

        if( c == 'a' )
        {
                /* Le damos el control a la función callback cuando haya imágenes.
                * We give control to the callback function.*/
                ros::spinOnce();
        }

        else if( c == 'b' )
        {
            unsigned int cnt_init = cnt;
            while( cnt - cnt_init <  )
            {
                ros::spinOnce();
            }
        }

        else break;

    }
    ROS_INFO_STREAM("Cerrando nodo\nClosing node\n");

  return ;
}

——————现在开始我们的ros编译之旅——————

主要分为几大步：

1. 确认头文件，观察.cpp文件中，哪些属于ros内部库，哪些是外部库。示例中，除了opencv2的库是外部库，其余是内部库

2. 在工作空间中（如果没有，请按照ros tutorial新建）test_ws/src并source后，新建package，将所有内部库添加到依赖中（若此时遗漏，仍可通过修改package.xml来添加。实际效果是一样的）

$ cd ~/test/ws/src
$ catkin_create_pkg extract_images roscpp cv_bridge sensor_msgs message_filters

$ catkin_make
$ . ~/test_ws/devel/setup.bash

可查看依赖项

$ rospack depend1 extrac_images

此时只有OpenCV2的库文件没有链接

修改CMakeLists.txt

加入搜索库文件

find_package( OpenCV REQUIRED )
include_directoties( ${OpenCV_INCLUDE_DIRS} )

添加可执行文件，链接cpp文件和库，以及最重要的一点是，将可执行文件与ROS库链接，不然会出现一大堆ROS的报错

add_executable( extract_images src/extrac_iamges.cpp )

target_link_libraries( extract_images ${OpenCV_DIRS} ${catkin_LIBRARIES} )

最后再回到工作空间test_ws，catkin_make即可。

课后作业——根据这个方法，推广为将node文件加入已有的项目中，应该怎么写呢？请读者自行解决！

参考文献：

How to extract depth data fromrosbags(contains depth and RGB data) as picture frames

Installing and Configuring Your ROS Environment

Creating a ROS Package