在導航過程中，傳感器的信息至關重要，這些傳感器可以是激光雷達、攝像機、聲納、紅外線、碰撞開關，但是歸根結底，導航功能包要求機器人必須發布sensor_msgs/LaserScan或sensor_msgs/PointCloud格式的傳感器信息，本篇將詳細介紹如何使用代碼發布所需要的消息。

1、ROS的消息頭信息
無論是 sensor_msgs/LaserScan，還是sensor_msgs/PointCloud ，都和ROS中tf幀信息等時間相關的消息一樣，帶標準格式的頭信息。
#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

以上是標準頭信息的主要部分。seq是消息的順序標識，不需要手動設置，發布節點在發布消息時，會自動累加。stamp 是消息中與數據相關聯的時間戳，例如激光數據中，時間戳對應激光數據的采集時間點。frame_id 是消息中與數據相關聯的參考系id，例如在在激光數據中，frame_id對應激光數據采集的參考系。

2、如何發布激光掃描消息
2.1、激光消息的結構

針對激光雷達，ROS在sensor_msgs 包中定義了專用了數據結構來存儲激光消息的相關信息，成為LaserScan。LaserScan消息的格式化定義，為虛擬的激光雷達數據采集提供了方便，在我們討論如何使用他之前，來看看該消息的結構是什么樣的：
#
# 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]

備注中已經詳細介紹了每個參數的意義。

2.2、通過代碼發布LaserScan消息

使用ROS發布LaserScan格式的激光消息非常簡潔，下邊是一個簡單的例程：
#include
#include

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

ros::NodeHandle n;
ros::Publisher scan_pub = n.advertise("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();
}
}

我們將代碼分解以便于分析：
#include

首先我們需要先包含Laserscan的數據結構。
ros::Publisher scan_pub = n.advertise("scan", 50);

創建一個發布者，以便于后邊發布針對scan主題的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();

這里的例程中我們虛擬一些激光雷達的數據，如果使用真是的激光雷達，這部分數據需要從驅動中獲取。
//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];
}

創建scan_msgs::LaserScan數據類型的變量scan，把我們之前偽造的數據填入格式化的消息結構中。
scan_pub.publish(scan);

數據填充完畢后，通過前邊定義的發布者，將數據發布。

3、如何發布點云數據
3.1、點云消息的結構
為存儲和發布點云消息，ROS定義了sensor_msgs/PointCloud消息結構：

#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，點云消息的結構支持存儲三維環境的點陣列，而且channels參數中，可以設置這些點云相關的數據，例如可以設置一個強度通道，存儲每個點的數據強度，還可以設置一個系數通道，存儲每個點的反射系數，等等。

3.2、通過代碼發布點云數據
ROS發布點云數據同樣簡潔：
#include
#include

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

ros::NodeHandle n;
ros::Publisher cloud_pub = n.advertise("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();
}
}

分解代碼來分析：
#include

首先也是要包含sensor_msgs/PointCloud消息結構。
ros::Publisher cloud_pub = n.advertise("cloud", 50);

定義一個發布點云消息的發布者。
sensor_msgs::PointCloud cloud;
cloud.header.stamp = ros::Time::now();
cloud.header.frame_id = "sensor_frame";

為點云消息填充頭信息，包括時間戳和相關的參考系id。
cloud.points.resize(num_points);

設置存儲點云數據的空間大小。
//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);

設置一個名為“intensity“的強度通道，并且設置存儲每個點強度信息的空間大小。
//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;
}

將我們偽造的數據填充到點云消息結構當中。
cloud_pub.publish(cloud);

最后，發布點云數據。