Ros 消息结构1

1、ROS的消息头信息

    

#Standard metadata for higher-level flow data types#sequence ID: consecutively increasing ID uint32 seq #Two-integer timestamp that is expressed as:# * stamp.secs: seconds (stamp_secs) since epoch# * stamp.nsecs: nanoseconds since stamp_secs# time-handling sugar is provided by the client librarytime stamp #Frame this data is associated with# 0: no frame# 1: global framestring frame_id

       以上是标准头信息的主要部分。seq是消息的顺序标识，不需要手动设置，发布节点在发布消息时，会自动累加。stamp 是消息中与数据相关联的时间戳，例如激光数据中，时间戳对应激光数据的采集时间点。frame_id 是消息中与数据相关联的参考系id，例如在在激光数据中，frame_id对应激光数据采集的参考系。

2.1、激光消息的结构

      针对激光雷达，ROS在sensor_msgs 包中定义了专用了数据结构来存储激光消息的相关信息，成为LaserScan。LaserScan消息的格式化定义，为虚拟的激光雷达数据采集提供了方便，在我们讨论如何使用他之前，来看看该消息的结构是什么样的：

## Laser scans angles are measured counter clockwise, with 0 facing forward# (along the x-axis) of the device frame# Header headerfloat32 angle_min        # start angle of the scan [rad]float32 angle_max        # end angle of the scan [rad]float32 angle_increment  # angular distance between measurements [rad]float32 time_increment   # time between measurements [seconds]float32 scan_time        # time between scans [seconds]float32 range_min        # minimum range value [m]float32 range_max        # maximum range value [m]float32[] ranges         # range data [m] (Note: values < range_min or > range_max should be discarded)float32[] intensities    # intensity data [device-specific units]

      备注中已经详细介绍了每个参数的意义。

2.2、通过代码发布LaserScan消息

    使用ROS发布LaserScan格式的激光消息非常简洁，下边是一个简单的例程：

#include <ros/ros.h>#include <sensor_msgs/LaserScan.h> int main(int argc, char** argv){  ros::init(argc, argv, "laser_scan_publisher");   ros::NodeHandle n;  ros::Publisher scan_pub = n.advertise<sensor_msgs::LaserScan>("scan", 50);   unsigned int num_readings = 100;  double laser_frequency = 40;  double ranges[num_readings];  double intensities[num_readings];   int count = 0;  ros::Rate r(1.0);  while(n.ok()){    //generate some fake data for our laser scan    for(unsigned int i = 0; i < num_readings; ++i){      ranges[i] = count;      intensities[i] = 100 + count;    }    ros::Time scan_time = ros::Time::now();     //populate the LaserScan message    sensor_msgs::LaserScan scan;    scan.header.stamp = scan_time;    scan.header.frame_id = "laser_frame";    scan.angle_min = -1.57;    scan.angle_max = 1.57;    scan.angle_increment = 3.14 / num_readings;    scan.time_increment = (1 / laser_frequency) / (num_readings);    scan.range_min = 0.0;    scan.range_max = 100.0;     scan.ranges.resize(num_readings);    scan.intensities.resize(num_readings);    for(unsigned int i = 0; i < num_readings; ++i){      scan.ranges[i] = ranges[i];      scan.intensities[i] = intensities[i];    }     scan_pub.publish(scan);    ++count;    r.sleep();  }}

    我们将代码分解以便于分析：

#include <sensor_msgs/LaserScan.h>

    首先我们需要先包含Laserscan的数据结构。

ros::Publisher scan_pub = n.advertise<sensor_msgs::LaserScan>("scan", 50);

    创建一个发布者，以便于后边发布针对scan主题的Laserscan消息。

  unsigned int num_readings = 100;  double laser_frequency = 40;  double ranges[num_readings];  double intensities[num_readings];   int count = 0;  ros::Rate r(1.0);  while(n.ok()){    //generate some fake data for our laser scan    for(unsigned int i = 0; i < num_readings; ++i){      ranges[i] = count;      intensities[i] = 100 + count;    }    ros::Time scan_time = ros::Time::now();

    这里的例程中我们虚拟一些激光雷达的数据，如果使用真是的激光雷达，这部分数据需要从驱动中获取。

    //populate the LaserScan message    sensor_msgs::LaserScan scan;    scan.header.stamp = scan_time;    scan.header.frame_id = "laser_frame";    scan.angle_min = -1.57;    scan.angle_max = 1.57;    scan.angle_increment = 3.14 / num_readings;    scan.time_increment = (1 / laser_frequency) / (num_readings);    scan.range_min = 0.0;    scan.range_max = 100.0;     scan.ranges.resize(num_readings);    scan.intensities.resize(num_readings);    for(unsigned int i = 0; i < num_readings; ++i){      scan.ranges[i] = ranges[i];      scan.intensities[i] = intensities[i];    }

    创建scan_msgs::LaserScan数据类型的变量scan，把我们之前伪造的数据填入格式化的消息结构中。

scan_pub.publish(scan);

    数据填充完毕后，通过前边定义的发布者，将数据发布。

3.1、点云消息的结构

      

#This message holds a collection of 3d points, plus optional additional information about each point. #Each Point32 should be interpreted as a 3d point in the frame given in the header   Header header geometry_msgs/Point32[] points  #Array of 3d points ChannelFloat32[] channels       #Each channel should have the same number of elements as points array, and the data in each channel should correspond 1:1 with each point

      如上所示，点云消息的结构支持存储三维环境的点阵列，而且channels参数中，可以设置这些点云相关的数据，例如可以设置一个强度通道，存储每个点的数据强度，还可以设置一个系数通道，存储每个点的反射系数，等等。

3.2、通过代码发布点云数据

     ROS发布点云数据同样简洁：

#include <ros/ros.h>#include <sensor_msgs/PointCloud.h> int main(int argc, char** argv){  ros::init(argc, argv, "point_cloud_publisher");   ros::NodeHandle n;  ros::Publisher cloud_pub = n.advertise<sensor_msgs::PointCloud>("cloud", 50);   unsigned int num_points = 100;   int count = 0;  ros::Rate r(1.0);  while(n.ok()){    sensor_msgs::PointCloud cloud;    cloud.header.stamp = ros::Time::now();    cloud.header.frame_id = "sensor_frame";     cloud.points.resize(num_points);     //we'll also add an intensity channel to the cloud    cloud.channels.resize(1);    cloud.channels[0].name = "intensities";    cloud.channels[0].values.resize(num_points);     //generate some fake data for our point cloud    for(unsigned int i = 0; i < num_points; ++i){      cloud.points[i].x = 1 + count;      cloud.points[i].y = 2 + count;      cloud.points[i].z = 3 + count;      cloud.channels[0].values[i] = 100 + count;    }     cloud_pub.publish(cloud);    ++count;    r.sleep();  }}

     分解代码来分析：

#include <sensor_msgs/PointCloud.h>

     首先也是要包含sensor_msgs/PointCloud消息结构。

ros::Publisher cloud_pub = n.advertise<sensor_msgs::PointCloud>("cloud", 50);

     定义一个发布点云消息的发布者。

sensor_msgs::PointCloud cloud;cloud.header.stamp = ros::Time::now();cloud.header.frame_id = "sensor_frame";

     为点云消息填充头信息，包括时间戳和相关的参考系id。

cloud.points.resize(num_points);

     设置存储点云数据的空间大小。

 //we'll also add an intensity channel to the cloudcloud.channels.resize(1);cloud.channels[0].name = "intensities";cloud.channels[0].values.resize(num_points);

     设置一个名为“intensity“的强度通道，并且设置存储每个点强度信息的空间大小。

 //generate some fake data for our point cloud    for(unsigned int i = 0; i < num_points; ++i){      cloud.points[i].x = 1 + count;      cloud.points[i].y = 2 + count;      cloud.points[i].z = 3 + count;      cloud.channels[0].values[i] = 100 + count;    }

     将我们伪造的数据填充到点云消息结构当中。

cloud_pub.publish(cloud);

      最后，发布点云数据。