如何使用pcl_ros删除pointcloud2数据中的地板表面



首先,感谢大家的阅读。现在我尝试在点云数据中删除地板,

这是我写的用来移除地板点云的代码。

#include <iostream>
#include <cmath>
#include <vector>
#include <ros/ros.h>
#include <sensor_msgs/PointCloud2.h>
#include <pcl_ros/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl_conversions/pcl_conversions.h>
#include <velodyne_pointcloud/point_types.h>
#include <pcl/common/common.h>
#include <pcl/common/centroid.h>
#include <pcl/common/transforms.h>
#include <pcl/console/parse.h>
#include <set>
#include <pcl/io/pcd_io.h>
#include <boost/format.hpp>
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/filters/passthrough.h>
#include <pcl/sample_consensus/model_types.h>
#include <pcl/sample_consensus/method_types.h>
#include <pcl/segmentation/sac_segmentation.h>
struct VelodynePointXYZIRT
{
PCL_ADD_POINT4D
PCL_ADD_INTENSITY;
uint16_t ring;
float time;
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
} EIGEN_ALIGN16;
POINT_CLOUD_REGISTER_POINT_STRUCT (VelodynePointXYZIRT,
(float, x, x) (float, y, y) (float, z, z) (float, intensity, intensity)
(uint16_t, ring, ring) (float, time, time)
)
ros::Publisher pub1;
using PointXYZIRT = VelodynePointXYZIRT;
void help (const sensor_msgs::PointCloud2ConstPtr& scan)
{
// Convert the sensor_msgs/PointCloud2 data to pcl/PointCloud
pcl::PointCloud<VelodynePointXYZIRT>::Ptr cloud(new pcl::PointCloud<VelodynePointXYZIRT>());
pcl::fromROSMsg (*scan, *cloud);
pcl::ModelCoefficients coefficients;
pcl::PointIndices inliers;
// Create the segmentation object
pcl::SACSegmentation< pcl::PointCloud<PointXYZIRT>> seg;
// Optional
seg.setOptimizeCoefficients (true);
// Mandatory
seg.setModelType (pcl::SACMODEL_PLANE);
seg.setMethodType (pcl::SAC_RANSAC);
seg.setDistanceThreshold (0.01);
seg.setInputCloud (cloud.makeShared ());
seg.segment (inliers, coefficients);
// Publish the model coefficients
pcl_msgs::ModelCoefficients ros_coefficients;
pcl_conversions::fromPCL(coefficients, ros_coefficients);
pub1.publish (ros_coefficients);
}
int main (int argc, char** argv)
{
// Initialize ROS
ros::init (argc, argv, "my_pcl_tutorial");
ros::NodeHandle nh;
// Create a ROS subscriber for the input point cloud
ros::Subscriber sub = nh.subscribe ("input", 1, help);
// Create a ROS publisher for the output point cloud
//#pub1 = nh.advertise<sensor_msgs::PointCloud2> ("output", 1);
pub1 = nh.advertise<pcl_msgs::ModelCoefficients> ("output", 1);
// Spin
ros::spin ();
}

,因为我必须将环数据放入代码中,所以我创建了用于定义velodyne激光雷达的结构体,但是当我在ros中使用catkin_make时,

出现错误,

error: ‘pcl::PointCloud<VelodynePointXYZIRT>::Ptr {aka class boost::shared_ptr<pcl::PointCloud<VelodynePointXYZIRT> >}’ has no member named ‘makeShared’
seg.setInputCloud (cloud.makeShared ());

有一种方法,我可视化的数据?

我的参考代码是这个网站,https://adioshun.gitbooks.io/pcl-tutorial/content/part-1/part01-chapter05/part01-chapter05-practice.html

和我之前的代码来转换激光雷达数据,我使用这些代码来制作我自己的.....

#include <iostream>
#include <cmath>
#include <vector>
#include <ros/ros.h>
#include <sensor_msgs/PointCloud2.h>
#include <pcl_ros/point_cloud.h>
#include <pcl/point_types.h>
#include <pcl_conversions/pcl_conversions.h>
#include <velodyne_pointcloud/point_types.h>
#include <pcl/common/common.h>
#include <pcl/common/centroid.h>
#include <pcl/common/transforms.h>
#include <pcl/console/parse.h>
#include <set>
#include <pcl/io/pcd_io.h>
#include <boost/format.hpp>
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/filters/passthrough.h>
#define PI 3.14159265359
using namespace std;
struct VelodynePointXYZIRT
{
PCL_ADD_POINT4D
PCL_ADD_INTENSITY;
uint16_t ring;
float time;
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
} EIGEN_ALIGN16;
POINT_CLOUD_REGISTER_POINT_STRUCT (VelodynePointXYZIRT,
(float, x, x) (float, y, y) (float, z, z) (float, intensity, intensity)
(uint16_t, ring, ring) (float, time, time)
)
ros::Publisher pub1;
float theta_r =  45* M_PI/ 180; // 라디안 각도로 회전 (180도 회전)
using PointXYZIRT = VelodynePointXYZIRT;
void input(const sensor_msgs::PointCloud2ConstPtr& scan)
{
// Msg to pointcloud
pcl::PointCloud<VelodynePointXYZIRT>::Ptr cloud(new pcl::PointCloud<VelodynePointXYZIRT>());
pcl::fromROSMsg(*scan,*cloud); // ros msg 에서 pcl cloud 데이터로 변환
//회전변환행렬
Eigen::Matrix4f transform_1 = Eigen::Matrix4f::Identity();
// Define a rotation matrix (see https://en.wikipedia.org/wiki/Rotation_matrix)
transform_1 (0,0) = std::cos (theta_r);
transform_1 (0,2) = std::sin(theta_r);
transform_1 (2,0) = -sin (theta_r);
transform_1 (2,2) = std::cos (theta_r);

//    (row, column)
// Executing the transformation
pcl::PointCloud<VelodynePointXYZIRT>::Ptr transformed_cloud (new pcl::PointCloud<PointXYZIRT>());
pcl::transformPointCloud (*cloud, *transformed_cloud, transform_1);
pcl::PCLPointCloud2 cloud_p;
pcl::toPCLPointCloud2(*transformed_cloud, cloud_p); 
sensor_msgs::PointCloud2 output;
pcl_conversions::fromPCL(cloud_p, output);
output.header.frame_id = "velodyne";
pub1.publish(output);
}

int main(int argc, char** argv)
{
ros::init(argc, argv, "input");
ros::NodeHandle nh;
ros::Subscriber sub = nh.subscribe<sensor_msgs::PointCloud2> ("vlp202", 100, input);
pub1 = nh.advertise<sensor_msgs::PointCloud2> ("vlp203", 100);
ros::spin();
}
//if you have to make your own type of custum point type in the pcl, you can see this one to see how to code it !!
// also the ring data that you have to use is from the lio_sam, image projection.cpp 

对于摘要,

  1. 我想删除记录袋中的地板点云数据,
  2. 所以我做了一些代码来删除地板数据

云;对象已经是一个共享指针。删除makeshare调用:

凹陷。setInputCloud(云。

makeShared ());

凹陷。

setInputCloud(云);

对于可视化,您可以在主题上发布结果作为ros消息,并使用rviz将其可视化。

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