3d激光雷达开发（平面分割）

        平面分割是点云数据经常需要处理的一个功能。在很多场景下面，平面数据都是没有用的。这个时候需要考虑的，就是怎么把平面数据从点云当中分割出去。鉴于此，pcl库给我们提供了一种这样的分割处理方法，​​https://pcl.readthedocs.io/projects/tutorials/en/master/planar_segmentation.html#planar-segmentation​​

1、准备planar_segmentation.cpp文件

#include <iostream>
#include <pcl/ModelCoefficients.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/sample_consensus/method_types.h>
#include <pcl/sample_consensus/model_types.h>
#include <pcl/segmentation/sac_segmentation.h>

int
 main ()
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);

  // Fill in the cloud data
  cloud->width  = 15;
  cloud->height = 1;
  cloud->points.resize (cloud->width * cloud->height);

  // Generate the data
  for (auto& point: *cloud)
  {
    point.x = 1024 * rand () / (RAND_MAX + 1.0f);
    point.y = 1024 * rand () / (RAND_MAX + 1.0f);
    point.z = 1.0;
  }

  // Set a few outliers
  (*cloud)[0].z = 2.0;
  (*cloud)[3].z = -2.0;
  (*cloud)[6].z = 4.0;

  std::cerr << "Point cloud data: " << cloud->size () << " points" << std::endl;
  for (const auto& point: *cloud)
    std::cerr << "    " << point.x << " "
                        << point.y << " "
                        << point.z << std::endl;

  pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
  pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
  // Create the segmentation object
  pcl::SACSegmentation<pcl::PointXYZ> seg;
  // Optional
  seg.setOptimizeCoefficients (true);
  // Mandatory
  seg.setModelType (pcl::SACMODEL_PLANE);
  seg.setMethodType (pcl::SAC_RANSAC);
  seg.setDistanceThreshold (0.01);

  seg.setInputCloud (cloud);
  seg.segment (*inliers, *coefficients);

  if (inliers->indices.size () == 0)
  {
    PCL_ERROR ("Could not estimate a planar model for the given dataset.\n");
    return (-1);
  }

  std::cerr << "Model coefficients: " << coefficients->values[0] << " " 
                                      << coefficients->values[1] << " "
                                      << coefficients->values[2] << " " 
                                      << coefficients->values[3] << std::endl;

  std::cerr << "Model inliers: " << inliers->indices.size () << std::endl;
  for (const auto& idx: inliers->indices)
    std::cerr << idx << "    " << cloud->points[idx].x << " "
                               << cloud->points[idx].y << " "
                               << cloud->points[idx].z << std::endl;

  return (0);
}

2、准备CMakeLists.txt文件

cmake_minimum_required(VERSION 3.5 FATAL_ERROR)

project(planar_segmentation)

find_package(PCL 1.2 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (planar_segmentation planar_segmentation.cpp)
target_link_libraries (planar_segmentation ${PCL_LIBRARIES})

3、生成sln文件，准备编译

4、执行exe文件

        主要是查看非平面数据有没有被算法剔除。