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Point Cloud Library

软件 版本号 文件名
os windows10-x64 -
Visual Studio VS2017 -
PCL PCL-1.8.1 PCL-1.8.1-AllInOne-msvc2017-win64.exe; pcl-1.8.1-pdb-msvc2017-win64.zip

Download

从官方 github 仓库 Point Cloud Library - Github Release 下载两个文件:

  1. PCL-1.8.1-AllInOne-msvc2017-win64.exe
  2. pcl-1.8.1-pdb-msvc2017-win64.zip

Install

  1. 双击 PCL-1.8.1-AllInOne-msvc2017-win64.exe 文件进行安装,
    建议勾选 Add PCl to the system PATH for all users.
    安装位置为 D:\PCL\. 安装时会顺带安装一些第三方库到子目录3rdParty 下

  2. 安装过程中会弹出一个第三方库 OpenNI2 的安装: OpenNI 2.2 SDK for Windows 64-bit Setup，建议设置路径到子目录 3rdParty 下.
    最终在 D:\PCL\3rdParty\ 路径下有: Boost,Eigen,FLANN,OpenNI2,Qhull,VTK共 6 个第三方库.
    其中 VTK 库是”万恶之源”, 会导致后续许多 bug. 网上有的帖子建议删除 PCL 自带的 VTK, 转而通过源码自行编译, 待议!

  3. 将 pcl-1.8.1-pdb-msvc2017-win64.zip 解压后的所有 *.pdb 文件复制到 D:\PCL\bin\ 路径下.

Configure

安装完成后需要对系统以及 VS2017 进行适当的配置才能成功使用PCL.

  1. 之前安装过程中如果勾选了 Add PCl to the system PATH for all users, 那么在系统变量中应当会有一个名为: PCL_ROOT, 值为: D:\PCL 的系统变量. 如果没有, 自行添加也可以:系统属性 -> 环境变量 -> 系统变量 -> 新建 -> ....

  2. 新建 VS2017 项目

  3. 在 VS2017 中添加用户宏: 视图 (V) -> 其他窗口 (E) -> 属性管理器 (M) -> Debug | x64 -> Microsoft.Cpp.x64.user -> 用户宏 -> 添加宏 -> 名称:PCL_3rdParty_ROOTDIR, 值:D:\PCL\3rdParty, 勾选 将此宏设置为生成环境中的环境变量.

  4. 添加头文件目录
    C/C++ -> 常规 -> 附加包含目录

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$(PCL_ROOT)\include\pcl-1.8
$(PCL_3rdParty_ROOTDIR)\Boost\include\boost-1_64
$(PCL_3rdParty_ROOTDIR)\Eigen\eigen3
$(PCL_3rdParty_ROOTDIR)\FLANN\include
$(PCL_3rdParty_ROOTDIR)\OpenNI2\Include
$(PCL_3rdParty_ROOTDIR)\Qhull\include
$(PCL_3rdParty_ROOTDIR)\VTK\include\vtk-8.0

  1. 添加 lib 文件目录
    链接器 -> 常规 -> 附加库目录

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    $(PCL_ROOT)\lib
    $(PCL_3rdParty_ROOTDIR)\Boost\lib
    $(PCL_3rdParty_ROOTDIR)\FLANN\lib
    $(PCL_3rdParty_ROOTDIR)\OpenNI2\Lib
    $(PCL_3rdParty_ROOTDIR)\Qhull\lib
    $(PCL_3rdParty_ROOTDIR)\VTK\lib

    Note: 这里 Eigen 没有附加库

  2. 添加 lib 文件名
    链接器 -> 输入 -> 附加依赖项

需要添加的 *.lib 文件名太多了, 这里参考
VS 中 PCL 库附加依赖项配置 - 博客园
通过批处理程序来完成.

在 D:\PCL 下新建一个批处理文件echo.bat, 双击运行该文件, 将所有 lib 文件名分为 debug 和 release 两类, 并写入两个文本文件内. 对于不同版本的软件，也许文件名会不同, 需要仔细核实匹配字符串与对应路径下的文件是否匹配.

  • echo.bat 文件如下 
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    @echo off
    echo "all *.lib files:"> lib_all.txt
    echo "all *.lib files for debug:"> lib_debug.txt
    echo "all *.lib files for release:"> lib_release.txt
    rem lib files of pcl
    for %%I in (lib/*.lib) do echo %%I>>lib_all.txt % 解释：对每一个(*.lib) 通配符匹配到的文件名 I，显示 I 到文件 all.txt，之后的语句类似理解就可 %
    for %%I in (lib/*debug.lib) do echo %%I>>lib_debug.txt
    for %%I in (lib/*release.lib) do echo %%I>>lib_release.txt
    rem lib files of Boost
    for %%I in (3rdParty/Boost/lib/*.lib) do echo %%I>>lib_all.txt
    for %%I in (3rdParty/Boost/lib/*mt-gd-1_64.lib) do echo %%I>>lib_debug.txt
    for %%I in (3rdParty/Boost/lib/*mt-1_64.lib) do echo %%I>>lib_release.txt
    rem lib files of Qhull
    for %%I in (3rdParty/Qhull/lib/*.lib) do echo %%I>>lib_all.txt
    for %%I in (3rdParty/Qhull/lib/*_d.lib) do echo %%I>>lib_debug.txt
    for %%I in (3rdParty/Qhull/lib/*l.lib) do echo %%I>>lib_release.txt
    for %%I in (3rdParty/Qhull/lib/*p.lib) do echo %%I>>lib_release.txt
    for %%I in (3rdParty/Qhull/lib/*r.lib) do echo %%I>>lib_release.txt
    for %%I in (3rdParty/Qhull/lib/*c.lib) do echo %%I>>lib_release.txt
    rem lib files of VTK
    for %%I in (3rdParty/VTK/lib/*.lib) do echo %%I>>lib_all.txt
    for %%I in (3rdParty/VTK/lib/*-gd.lib) do echo %%I>>lib_debug.txt
    for %%I in (3rdParty/VTK/lib/*8.0.lib) do echo %%I>>lib_release.txt
    for %%I in (3rdParty/VTK/lib/*c++.lib) do echo %%I>>lib_release.txt
    rem lib files of FLANN
    for %%I in (3rdParty/FLANN/lib/*.lib) do echo %%I>>lib_all.txt
    for %%I in (3rdParty/FLANN/lib/*-gd.lib) do echo %%I>>lib_debug.txt
    for %%I in (3rdParty/FLANN/lib/*n.lib) do echo %%I>>lib_release.txt
    for %%I in (3rdParty/FLANN/lib/*p.lib) do echo %%I>>lib_release.txt
    for %%I in (3rdParty/FLANN/lib/*s.lib) do echo %%I>>lib_release.txt
    rem lib files of OPENNI2
    for %%I in (3rdParty/OpenNI2/Lib/*.lib) do echo %%I>>lib_all.txt
    for %%I in (3rdParty/OpenNI2/Lib/*.lib) do echo %%I>>lib_debug.txt
    for %%I in (3rdParty/OpenNI2/Lib/*.lib) do echo %%I>>lib_release.txt

    rem pause
  1. 添加 DLL
    将如下路径下的所有 *.dll 文件复制到新建目录 dll\ 路径下:
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    $(PCL_ROOT)\bin
    $(PCL_3rdParty_ROOTDIR)\Qhull\bin
    $(PCL_3rdParty_ROOTDIR)\FLANN\bin
    $(PCL_3rdParty_ROOTDIR)\VTK\bin
    $(PCL_3rdParty_ROOTDIR)\OpenNI2\Tools
    并将该路径添加到 VS2017 的项目环境下.
    在 解决方案资源管理器 右击项目名 ->属性 -> 调试 -> 环境->PATH=.\dll;%PATH%.

或者参考
pcl1.8.0+vs2013 环境配置（详细）- CSDN
将以下路径添加到系统路径中,系统属性 -> 环境变量 -> 系统变量 -> Path -> 编辑 -> 添加

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;%PCL_ROOT%\bin
;%PCL_ROOT%\3rdParty\Qhull\bin
;%PCL_ROOT%\3rdParty\FLANN\bin
;%PCL_ROOT%\3rdParty\VTK\bin
;%PCL_ROOT%\3rdParty\OpenNI2\Tools

属性配置好以后，可以右键属性表，将其保存，以后用的时候直接”添加现有属性表”就可以，不用每次使用 PCL 都重新配置了

Test

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// main.cpp
#include <iostream>
#include <pcl/common/common_headers.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/console/parse.h>


int main(int argc, char **argv) 
{
	std::cout << "Test PCL !!!" << std::endl;

	pcl::PointCloud<pcl::PointXYZRGB>::Ptr point_cloud_ptr(new pcl::PointCloud<pcl::PointXYZRGB>);
	uint8_t r(255), g(15), b(15);
	for (float z(-1.0); z <= 1.0; z += 0.05)
	{
		for (float angle(0.0); angle <= 360.0; angle += 5.0)
		{
			pcl::PointXYZRGB point;
			point.x = 0.5 * cosf(pcl::deg2rad(angle));
			point.y = sinf(pcl::deg2rad(angle));
			point.z = z;
			uint32_t rgb = (static_cast<uint32_t>(r) << 16 |
				static_cast<uint32_t>(g) << 8 | static_cast<uint32_t>(b));
			point.rgb = *reinterpret_cast<float*>(&rgb);
			point_cloud_ptr->points.push_back(point);
		}
		if (z < 0.0)
		{
			r -= 12;
			g += 12;
		}
		else
		{
			g -= 12;
			b += 12;
		}
	}
	point_cloud_ptr->width = (int)point_cloud_ptr->points.size();
	point_cloud_ptr->height = 1;

	pcl::visualization::CloudViewer viewer("test");
	viewer.showCloud(point_cloud_ptr);
	while (!viewer.wasStopped()) {};
	return 0;
}

踩坑

  1. 错误 C4996

    严重性 代码 说明 项目 文件 行 禁止显示状态
    错误 C4996 ‘std::fpos<_Mbstatet>::seekpos’: warning STL4019: The member std::fpos::seekpos() is non-Standard, and is preserved only for compatibility with workarounds for old versions of Visual C++. It will be removed in a future release, and in this release always returns 0. Please use standards-conforming mechanisms to manipulate fpos, such as conversions to and from streamoff, or an integral type, instead. If you are receiving this message while compiling Boost.IOStreams, a fix has been submitted upstream to make Boost use standards-conforming mechanisms, as it does for other compilers. You can define _SILENCE_FPOS_SEEKPOS_DEPRECATION_WARNING to acknowledge that you have received this warning, or define _REMOVE_FPOS_SEEKPOS to remove std::fpos::seekpos entirely. demo_Proj d:\pcl\3rdparty\boost\include\boost-1_64\boost\iostreams\positioning.hpp 96

解决办法: 属性 -> 配置属性 -> C/C++ -> 高级 -> 禁用特定警告 -> 4996;.
也可以关闭 SDL 检查 来解决这一问题: 属性 -> 配置属性 -> C/C++ -> 常规 -> SDL 检查: 否(/sdl-)

  1. no override found for ‘vtkPolyDataMapper’

参考:https://github.com/PointCloudLibrary/pcl/issues/1797

将 $(PCL_3rdParty_ROOTDIR)\OpenNI2\Samples\SimpleViewer\ 添加到 附加包含目录 , 该路径下有头文件GL/glut.h 需要在源文件中包含; 该路径下的 glut32.lib 需要链接到 附加库 ; 对应的glut32.dll 文件复制到相应的位置.
在主程序最开始的地方添加如下代码段:

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#include <GL/glut.h>
#include <vtkAutoInit.h>
VTK_MODULE_INIT(vtkRenderingOpenGL);
VTK_MODULE_INIT(vtkInteractionStyle);
  1. 运行 PCL 代码出现 C2988,C2143,C2913 等错误的解决方法

PCL 点云格式转换

ply 文件可以用 windows 自带的 3d 查看器打开,pcd 文件可以用 CloudViewer 打开

这是目标工件生产时参考的标准 ply 模型文件, 通过 pcl 工具转换为 pcd 文件

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.\pcl_mesh_sampling_release.exe ..\model.ply ..\model.pcd


Convert a CAD model to a point cloud using uniform sampling. 
For more information, use: D:\PCL\bin\pcl_mesh_sampling_release.exe -h

Syntax is: D:\PCL\bin\pcl_mesh_sampling_release.exe input.{ply,obj} output.pcd <options>
  where options are:
                     -n_samples X      = number of samples (default: 100000)
                     -leaf_size X  = the XYZ leaf size for the VoxelGrid -- for data reduction (default: 0.010000 m)
                     -write_normals = flag to write normals to the output pcd
                     -no_vis_result = flag to stop visualizing the generated pcd
(base) PS D:\PCL\bin> .\pcl_mesh_sampling_release.exe ..\model.ply ..\model.pcd -leaf_size 0.001

补充说明 : 我一开始在命令行中运行pcl_mesh_sampling_release.exe 时，命令行直接毫无显示，也没报错。
双击该可执行文件时弹窗说找不到 OpenNI2.dll，于是把该文件拷贝到 pcl_mesh_sampling_release.exe 同一路径下，就可以在命令行中执行转换了。

参考

Reference

代码段示例

统计滤波: 去除离群点

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#include <pcl/filters/statistical_outlier_removal.h>
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>);

pcl::StatisticalOutlierRemoval<pcl::PointXYZ> sor;
sor.setInputCloud(cloud);
sor.setMeanK(50);
sor.setStddevMulThresh(1.0);
sor.filter(*cloud_filtered);

体素滤波: 降采样

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#include <pcl/filters/voxel_grid.h>
pcl::PointCloud<pcl::PointXYZ>::Ptr downsample(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud)
{
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filter(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::VoxelGrid<pcl::PointXYZ> voxel_filter;
    voxel_filter.setInputCloud(cloud);
    float leafsz = 0.3f;
    voxel_filter.setLeafSize(leafsz, leafsz, leafsz);
    voxel_filter.filter(*cloud_filter);
    return cloud_filter;
}

可视化

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visualization::PCLVisualizer viewer("PPF Object Recognition - Results");
viewer.setBackgroundColor(0, 0, 0);
viewer.addPointCloud(cloud_scene);
viewer.spinOnce(10);
visualization::PointCloudColorHandlerRandom<PointXYZ> random_color(cloud_output->makeShared());
viewer.addPointCloud(cloud_output, random_color, mode_name);

平移旋转

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Eigen::Affine3f transform = Eigen::Affine3f::Identity();
// Define a translation of 0 meters on the x axis.
transform.translation() << 0.0, 0.0, 0.0;
// The same rotation matrix as before; theta radians arround Z axis
transform.rotate(Eigen::AngleAxisf(M_PI_2, Eigen::Vector3f::UnitZ()));
// Print the transformation
std::cout << transform.matrix() << std::endl;

// Executing the transformation
pcl::PointCloud<pcl::PointXYZ>::Ptr transformed_cloud(new pcl::PointCloud<pcl::PointXYZ>());
// You can either apply transform_1 or transform_2; they are the same
pcl::transformPointCloud(*cloud, *transformed_cloud, transform);

聚类

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/***********************************************************************************
// 提取出最大的点云聚类
#include <pcl/kdtree/kdtree.h>
#include <pcl/filters/extract_indices.h>
#include <pcl/segmentation/extract_clusters.h>
typedef pcl::PointXYZ PointT;
typedef pcl::PointCloud<PointT> PointCloudT;
*************************************************************************************/
PointCloudT::Ptr largestClusterCloud(const PointCloudT::Ptr& cloud)
{
	// 为提取点云时使用的搜素对象利用输入点云 cloud_filtered 创建 Kd 树对象 tree。
	pcl::search::KdTree<PointT>::Ptr tree(new pcl::search::KdTree<PointT>);
	tree->setInputCloud(cloud);// 创建点云索引向量，用于存储实际的点云信息
	std::vector<pcl::PointIndices> cluster_indices;
	pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec;
	ec.setClusterTolerance(5); // 设置近邻搜索的搜索半径为 5mm
	ec.setMinClusterSize(1000);    // 设置一个聚类需要的最少点数目为 1000
	ec.setMaxClusterSize(50000);  // 设置一个聚类需要的最大点数目为 50000
	ec.setSearchMethod(tree);     // 设置点云的搜索机制
	ec.setInputCloud(cloud); // 设置原始点云 
	ec.extract(cluster_indices);  // 从点云中提取聚类 clusters have been sorted based on their size (largest one first)

	if (cluster_indices.size() == 0)
	{
		return cloud;
	}
	PointCloudT::Ptr cloud_max_cluster(new PointCloudT);
	pcl::copyPointCloud(*cloud, cluster_indices[0], *cloud_max_cluster);
	return cloud_max_cluster;
}

区域生长分割

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#include <pcl/point_types.h>
#include <pcl/point_cloud.h>
#include <pcl/filters/statistical_outlier_removal.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/kdtree/kdtree.h>
#include <pcl/filters/extract_indices.h>
#include <pcl/segmentation/extract_clusters.h>
#include <pcl/segmentation/region_growing.h>
#include <pcl/search/search.h>
#include <pcl/search/kdtree.h>
#include <pcl/features/normal_3d.h>
#include <pcl/visualization/cloud_viewer.h>
// #include <opencv2/opencv.hpp>
// #include <ctime> 

typedef pcl::PointCloud<pcl::PointXYZ> PointCloudT;

std::vector<pcl::PointIndices> region_growing_segmentation(const PointCloudT::Ptr& cloud,bool viewflag)
{
pcl::search::Search<pcl::PointXYZ>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZ>);
pcl::PointCloud <pcl::Normal>::Ptr normals(new pcl::PointCloud <pcl::Normal>);
pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> normal_estimator;
normal_estimator.setSearchMethod(tree);
normal_estimator.setInputCloud(cloud);
normal_estimator.setKSearch(50);
normal_estimator.compute(*normals);
pcl::RegionGrowing<pcl::PointXYZ, pcl::Normal> reg;
reg.setMinClusterSize(5000);
reg.setMaxClusterSize(50000);
reg.setSearchMethod(tree);
reg.setNumberOfNeighbours(30);
reg.setInputCloud(cloud);
//reg.setIndices (indices);
reg.setInputNormals(normals);
reg.setSmoothnessThreshold(6.0 / 180.0 * M_PI);
reg.setCurvatureThreshold(6.0);

std::vector <pcl::PointIndices> clusters;
reg.extract(clusters);
// Sort the clusters based on their size (largest one first)
std::sort(clusters.rbegin(), clusters.rend(), [](pcl::PointIndices a, pcl::PointIndices b){return a.indices.size()>b.indices.size();});// 按照点数由多到少排序
if (viewflag)
{
	pcl::PointCloud <pcl::PointXYZRGB>::Ptr colored_cloud = reg.getColoredCloud();
	pcl::visualization::CloudViewer viewer("Cluster viewer");
	viewer.showCloud(colored_cloud);
	while (!viewer.wasStopped())
	{
	}
}
return clusters;
}

显示多个坐标系 

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#include <pcl/visualization/pcl_visualizer.h>
/************************************
// 调用 addText3D 时需添加该段代码，否则报错 Error:no override found for 'vtkPolyDataMapper'
// https://stackoverflow.com/questions/40086584/errorno-override-found-for-vtkpolydatamapper
#include <vtkAutoInit.h>
VTK_MODULE_INIT(vtkRenderingOpenGL);
VTK_MODULE_INIT(vtkInteractionStyle);
#pragma comment(lib,"OpenGL32.Lib")
// pcl 中 setCameraPosition 的参数说明
// https://blog.csdn.net/nicai41/article/details/98726465
// 为了在指定的视角观察点云，设置一个相机位置，其中 pos_[xyz] 表示相机位置,view_[xyz]表示相机视线方向，up_[xyz]表示相机正上方向向量
double pos_x, double pos_y, double pos_z,
double view_x, double view_y, double view_z,
double up_x, double up_y, double up_z,
****************************************/
// 显示类
pcl::visualization::PCLVisualizer CoordinateViewer("Cloud Viewer");
// 添加坐标系
CoordinateViewer.addCoordinateSystem(10, Eigen::Affine3f::Identity());// 用 Affine3f 表示
CoordinateViewer.addCoordinateSystem(10, 5, 5, 6);// 用 x,y,z 表示
CoordinateViewer.addText3D("coor 1", pcl::PointXYZ(5,5,6), 2, 1, 0, 0, "text1");
CoordinateViewer.addCoordinateSystem(10, 4, 4, 4);
CoordinateViewer.addPointCloud(point_cloud_ptr);
CoordinateViewer.setCameraPosition(10, -10, 3, -10,10,-3,  0.1, -0.1, 1);
while (!CoordinateViewer.wasStopped()) 
{
    CoordinateViewer.spinOnce();
};

生成简单几何体

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typedef pcl::PointXYZ PointT;
typedef pcl::PointCloud<PointT> PointCloudT;

// 构造圆柱体点云
PointCloudT::Ptr ConsCylinderCloud(float radius, float height, float d_degree = 0.5,float d_height = 0.05,float d_radius=0.5)
{
	PointCloudT::Ptr cloud(new PointCloudT);
	for (float x = 0; x <= height; x += d_height)
	{
		for (float angle = 0.0; angle <= 360.0; angle += d_degree)
		{
			PointT point;
			point.x = x;
			point.y = radius * sinf(pcl::deg2rad(angle));
			point.z = radius * cosf(pcl::deg2rad(angle));
			cloud->points.push_back(point);
		}
	}

	for (float r = 0; r <= radius; r += d_radius)
	{
		for (float angle = 0.0; angle <= 360.0; angle += d_degree)
		{
			PointT point;
			point.x = 0;
			point.y = r * sinf(pcl::deg2rad(angle));
			point.z = r * cosf(pcl::deg2rad(angle));
			cloud->points.push_back(point);
		}
	}

	for (float r = 0; r <= radius; r += d_radius)
	{
		for (float angle = 0.0; angle <= 360.0; angle += d_degree)
		{
			PointT point;
			point.x = height;
			point.y = r * sinf(pcl::deg2rad(angle));
			point.z = r * cosf(pcl::deg2rad(angle));
			cloud->points.push_back(point);
		}
	}

	cloud->width = (int)cloud->points.size();
	cloud->height = 1;
	return cloud;
}

PointCloudT::Ptr ConsCubeCloud(float x_length, float y_width, float z_height, float dx = 0.05, float dy = 0.05, float dz = 0.05)
{

	float length_2 = x_length / 2;
	float width_2 = y_width / 2;
	float height_2 = z_height / 2;
	PointCloudT::Ptr cloud(new PointCloudT);

	for (float x = -length_2; x <= length_2; x += dx)
	{
		for (float y = -width_2; y <= width_2; y += dy)
		{
			PointT point_1;
			point_1.x = x;
			point_1.y = y;
			point_1.z = -height_2;
			PointT point_2;
			point_2.x = x;
			point_2.y = y;
			point_2.z = height_2;
			cloud->points.push_back(point_1);
			cloud->points.push_back(point_2);
		}
		for (float z = -height_2; z <= height_2; z += dz)
		{
			PointT point_1;
			point_1.x = x;
			point_1.y = -width_2;
			point_1.z = z;
			PointT point_2;
			point_2.x = x;
			point_2.y = width_2;
			point_2.z = z;
			cloud->points.push_back(point_1);
			cloud->points.push_back(point_2);
		}
	}

	for (float y = -width_2; y <= width_2; y += dy)
	{
		for (float z = -height_2; z <= height_2; z += dz)
		{
			PointT point_1;
			point_1.x = -length_2;
			point_1.y = y;
			point_1.z = z;
			PointT point_2;
			point_2.x = length_2;
			point_2.y = y;
			point_2.z = z;
			cloud->points.push_back(point_1);
			cloud->points.push_back(point_2);
		}
	}


	cloud->width = (int)cloud->points.size();
	cloud->height = 1;
	return cloud;
}

// 构造球体点云
PointCloudT::Ptr ConsSphereCloud(float radius, float d_theta=5.0, float d_phi=5.0)
{
	PointCloudT::Ptr cloud(new PointCloudT);

	for (float theta = 0.0; theta <= 180.0; theta += d_theta)
	{
		for (float phi = 0.0; phi <= 360.0; phi += d_phi)
		{
			PointT point;

			point.x = radius * sinf(pcl::deg2rad(theta)) * cosf(pcl::deg2rad(phi));
			point.y = radius * sinf(pcl::deg2rad(theta)) * sinf(pcl::deg2rad(phi));
			point.z = radius * cosf(pcl::deg2rad(theta));
			cloud->points.push_back(point);
		}
	}

	cloud->width = (int)cloud->points.size();
	cloud->height = 1;
	return cloud;
}

Point Cloud Library

https://luosiyou.cn/blogs/pcl/

作者

Luo Siyou

发布于

2023-01-03

更新于

2023-01-09

许可协议

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