ROS读取激光雷达点云数据（RS-Lidar为例）
一、准备工作：
1、安装ROS （含有rviz）；
2、安装pcl-ros。
pcl（Point Cloud Library）-ros 是ROS中点云和3D几何处理的接口和工具。
如果安装的是ros-kinetic-desktop版本，默认不包含pcl-ros，在rviz中无法显示点云。
安装方法：
sudo apt-get install libpcap-dev #安装依赖
sudo apt-get install ros-kinetic-pcl-ros显示：
sudo apt-get install ros-kinetic-pcl-ros
Reading package lists... Done
Building dependency tree
Reading state information... Done
The following additional packages will be installed:
libflann-dev libflann1.8 libopenni-dev libopenni-sensor-pointclouds0
libopenni0 libpcl-apps1.7 libpcl-common1.7 libpcl-dev libpcl-features1.7
libpcl-filters1.7 libpcl-io1.7 libpcl-kdtree1.7 libpcl-keypoints1.7
libpcl-octree1.7 libpcl-outofcore1.7 libpcl-people1.7 libpcl-recognition1.7
libpcl-registration1.7 libpcl-sample-consensus1.7 libpcl-search1.7
libpcl-segmentation1.7 libpcl-surface1.7 libpcl-tracking1.7
libpcl-visualization1.7 libpcl1.7 openni-utils ros-kinetic-pcl-conversions
ros-kinetic-pcl-msgs ros-kinetic-tf2-eigen
Suggested packages:
openni-doc libpcl-doc
The following NEW packages will be installed:
libflann-dev libflann1.8 libopenni-dev libopenni-sensor-pointclouds0
libopenni0 libpcl-apps1.7 libpcl-common1.7 libpcl-dev libpcl-features1.7
libpcl-filters1.7 libpcl-io1.7 libpcl-kdtree1.7 libpcl-keypoints1.7
libpcl-octree1.7 libpcl-outofcore1.7 libpcl-people1.7 libpcl-recognition1.7
libpcl-registration1.7 libpcl-sample-consensus1.7 libpcl-search1.7
libpcl-segmentation1.7 libpcl-surface1.7 libpcl-tracking1.7
libpcl-visualization1.7 libpcl1.7 openni-utils ros-kinetic-pcl-conversions
ros-kinetic-pcl-msgs ros-kinetic-pcl-ros ros-kinetic-tf2-eigen
如果对pcl-ros感兴趣，可以参考博客学习更多相关资料 https://www.cnblogs.com/qixianyu/p/6607440.html 。
3、安装RSLidar ROS驱动
ROBOSENSE的激光雷达。
mkdir -p ~/rslidar_ws/src
cd ~/rslidar_ws/src
git clone https://github.com/RoboSense-LiDAR/ros_rslidar
cd ..
catkin_make #编译和安装4、录制好的激光点云数据（rosbag格式）
例如：rslidar_test.bag。
二、方法：
1、启用主节点
roscore # 执行所有ROS程序前必须执行的指令2、发布激光点云
Publisher:
rosbag play rslidar_test.bag倍速播放:
rosbag play -r 100 rslidar_test.bag #100倍速度播放bag time存储到txt文件中:
rosbag play -r 100 rslidar_test.bag >> bagtime.txt
3、运行
source ~/rslidar_ws/devel/setup.bash #启用配置，同一个terminal下运行如下命令：
roslaunch rslidar_pointcloud rs_lidar_16.launch #16表示16线的激光雷达，如果是32线的则运行rs_lidar_32.launch则rviz被启动，相应的Fixed Frame、PointCloud2已经配置好。
三、其他:
1、查看bag信息
rosbag info rslidar_test.bag则弹出如下信息：
path: rslidar_test.bag
version: 2.0
duration: 2hr 23:11s
start: Jun 23 2019 09:25:22.21 (1560903922.21)
end: Jun 23 2019 12:51:11.43 (1560916271.43)
size: 13.4 GB
messages: 121634
compression: none [30448/30448 chunks]
types: rslidar_msgs/rslidarScan [ff6baa58985b528481871cbaf1bb342f]
topics: rslidar_packets 121634 msgs : rslidar_msgs/rslidarScan
2、查看话题：
rostopic list显示出：
/clicked_point
/clock
/diagnostics
/initialpose
/move_base_simple/goal
/rosout #实质为rosgraph_msgs/Log
/rosout_agg
/rslidar_node/parameter_descriptions
/rslidar_node/parameter_updates
/rslidar_packets
/rslidar_packets_difop
/rslidar_points
/tf
/tf_static
3、查看话题发布速率：
rostopic hz /rslidar_points4、打印出通道信息：
rostopic echo /rslidar_points5、查看运行的节点
rosnode list/play_1563514485981639105
/rosout
/rslidar_node
/rviz_1563514559520415329
参考资料：
1. https://www.ncnynl.com/archives/201807/2552.html
2. https://github.com/RoboSense-LiDAR/ros_rslidar/blob/master/doc/readme_cn.md