在导航过程中,传感器的信息至关重要,这些传感器可以是激光雷达、摄像机、声纳、红外线、碰撞开关,但是归根结底,导航功能包要求机器人必须发布sensor_msgs/LaserScansensor_msgs/PointCloud格式的传感器信息,本篇将详细介绍如何使用代码发布所需要的消息。

1ROS的消息头信息

    无论是 sensor_msgs/LaserScan还是sensor_msgs/PointCloud ,都和ROStf帧信息等时间相关的消息一样,带标准格式的头信息。

#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 library
time stamp

#Frame this data is associated with
# 0: no frame
# 1: global frame
string 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、如何发布激光扫描消息

2.1、激光消息的结构

      针对激光雷达,ROSsensor_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LaserScanLaserScan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 header
float32 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、如何发布点云数据

3.1、点云消息的结构

      为存储和发布点云消息,ROS定义了sensor_msgs/PointCloud消息结构:

#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 cloud
    cloud.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。

 

参考连接: http://wiki.ros.org/navigation/Tutorials/RobotSetup/Sensors