PCL 点云配准 IterativeClosestPointNonLinear

最新推荐文章于 2024-08-12 16:03:14 发布

zxcvb036

最新推荐文章于 2024-08-12 16:03:14 发布

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分类专栏： PCL c++

本文链接：https://blog.youkuaiyun.com/zxcvb036/article/details/113849090

本文深入探讨了PCL库中的IterativeClosestPointNonLinear算法，详细阐述了其在点云配准中的应用和优化过程。通过实例解析，展示了如何使用该算法实现精确的三维点云配准，对于理解和提升点云处理技术具有重要意义。

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#include <pcl/memory.h>  // for pcl::make_shared
#include <pcl/point_types.h>
#include <pcl/point_cloud.h>
#include <pcl/point_representation.h>
#include <pcl/io/pcd_io.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/filters/filter.h>
#include <pcl/features/normal_3d.h>
#include <pcl/registration/icp.h>
#include <pcl/registration/icp_nl.h>
#include <pcl/registration/transforms.h>
#include <pcl/visualization/pcl_visualizer.h>

using pcl::visualization::PointCloudColorHandlerGenericField;
using pcl::visualization::PointCloudColorHandlerCustom;

//convenient typedefs
typedef pcl::PointXYZ PointT;
typedef pcl::PointCloud<PointT> PointCloud;
typedef pcl::PointNormal PointNormalT;
typedef pcl::PointCloud<PointNormalT> PointCloudWithNormals;

// This is a tutorial so we can afford having global variables 
    //our visualizer
pcl::visualization::PCLVisualizer* p;
//its left and right viewports
int vp_1, vp_2;

//convenient structure to handle our pointclouds
struct PCD
{
   
    PointCloud::Ptr cloud;
    std::string f_name;

    PCD() : cloud(new PointCloud) {
   };
};

struct PCDComparator
{
   
    bool operator () (const PCD& p1, const PCD& p2)
    {
   
        return (p1.f_name < p2.f_name);
    }
};


// Define a new point representation for < x, y, z, curvature >
class MyPointRepresentation : public pcl::PointRepresentation <PointNormalT>
{
   
    using pcl::PointRepresentation<PointNormalT>::nr_dimensions_;
public:
    MyPointRepresentation()
    {
   
        // Define the number of dimensions
        nr_dimensions_ = 4;
    }

    // Override the copyToFloatArray method to define our feature vector
    virtual void copyToFloatArray(const PointNormalT& p, float* out) const
    {
   
        // < x, y, z, curvature >
        out[0] = p.x;
        out[1] = p.y;
        out[2] = p.z;
        out[3] = p.curvature;
    }
};



/** \brief Display source and target on the first viewport of the visualizer
 *
 */
void showCloudsLeft(const PointCloud::Ptr cloud_target, const PointCloud::Ptr cloud_source)
{
   
    p->removePointCloud("vp1_target");
    p->removePointCloud("vp1_source");

    PointCloudColorHandlerCustom<PointT> tgt_h(cloud_target, 0, 255, 0);
    PointCloudColorHandlerCustom<PointT> src_h(cloud_source, 255, 0, 0);
    p->addPointCloud(cloud_target, tgt_h, "vp1_target", vp_1

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