解析nsor_msgs：：PointCloud2ROS点云数据⼀、消息结构
nsor_msgs::PointCloud2是⼀类点云数据结构，消息定义如下
田鸡的做法$ rosmsg info nsor_msgs/PointCloud2
std_msgs/Header header
uint32 q
time stamp六级考试题型
string frame_id
uint32 height
uint32 width
nsor_msgs/PointField[] fields
uint8 INT8=1
uint8 UINT8=2
uint8 INT16=3
uint8 UINT16=4
uint8 INT32=5
uint8 UINT32=6
uint8 FLOAT32=7
uint8 FLOAT64=8
string name
uint32 offt小学乘法口诀表
uint8 datatype
uint32 count
bool is_bigendian
uint32 point_step奇石收藏
uint32 row_step
uint8[] data
bool is_den
⼀个仿真的点云消息长这样
$ rostopic echo /airsim_node/Drone0/lidar/LidarSensor1
叫header:
q: 2116
stamp:
cs: 1586919439
ncs: 448866652
公关策划书frame_id: "LidarSensor1"
height: 1
width: 3
fields:
-
name: "x"
offt: 0
datatype: 7
count: 1
-
name: "y"
offt: 4
datatype: 7
count: 1
-
name: "z"
offt: 8
datatype: 7
count: 1
is_bigendian: Fal
point_step: 12描写泰山的句子
row_step: 36
data: [143, 194, 117, 53, 10, 215, 163, 53, 222, 238, 165, 64, 143, 194, 117, 53, 10, 215, 163, 53, 222, 238, 165, 64, 143, 194, 117, 53, 10, 215, 163, 53, 222, 23 is_den: True
PointCloud2的data是序列化后的数据，直接看不到物理意义。写了两种解析nsor_msgs::PointCloud2 数据的程序。
⼆、Python
#!/usr/bin/env python2
# coding:utf-8
import rospy
from nsor_msgs.msg import PointCloud2
from nsor_msgs import point_cloud2
def callback_pointcloud(data):
asrt isinstance(data, PointCloud2)
gen = ad_points(data)
print type(gen)
for p in gen:
print p
def listener():
rospy.init_node('pylistener', anonymous=True)
#Subscriber函数第⼀个参数是topic的名称，第⼆个参数是接受的数据类型第三个参数是回调函数的名称
rospy.Subscriber('/airsim_node/Drone0/lidar/LidarSensor1', PointCloud2, callback_pointcloud)
rospy.spin()
if __name__ == '__main__':
listener()
解析上⾯数据输出如下
<type 'generator'>
地震预兆(1.5258788153005298e-06, 1.220703097715159e-06, 5.185408592224121)
(9.155273232863692e-07, 1.220703097715159e-06, 5.185408592224121)
(9.155273232863692e-07, 1.220703097715159e-06, 5.185408592224121)
三、C++
#include <nsor_msgs/PointCloud.h>
#include <nsor_msgs/PointCloud2.h>
#include <nsor_msgs/point_cloud_conversion.h>
double pointCloud2ToZ(const nsor_msgs::PointCloud2 &msg)
{
nsor_msgs::PointCloud out_pointcloud;
nsor_msgs::convertPointCloud2ToPointCloud(msg, out_pointcloud);
for (int i=0; i<out_pointcloud.points.size(); i++) {
cout << out_pointcloud.points[i].x << ", " << out_pointcloud.points[i].y << ", " << out_pointcloud.points[i].z << endl; }
cout << "------" << endl;
return out_pointcloud.points[0].z;
}
