registration.hpp File Reference

点云配准算法统一导出文件 / Unified export file for point cloud registration algorithms More...

#include <cpp-toolbox/pcl/registration/registration_result.hpp>
#include <cpp-toolbox/pcl/registration/base_coarse_registration.hpp>
#include <cpp-toolbox/pcl/registration/base_fine_registration.hpp>
#include <cpp-toolbox/pcl/registration/ransac_registration.hpp>
#include <cpp-toolbox/pcl/registration/prosac_registration.hpp>
#include <cpp-toolbox/pcl/registration/four_pcs_registration.hpp>
#include <cpp-toolbox/pcl/registration/super_four_pcs_registration.hpp>
#include <cpp-toolbox/pcl/registration/point_to_point_icp.hpp>
#include <cpp-toolbox/pcl/registration/point_to_plane_icp.hpp>
#include <cpp-toolbox/pcl/registration/generalized_icp.hpp>
#include <cpp-toolbox/pcl/registration/aa_icp.hpp>
#include <cpp-toolbox/pcl/registration/ndt.hpp>
#include <cpp-toolbox/types/point.hpp>
#include <cpp-toolbox/logger/thread_logger.hpp>

Include dependency graph for registration.hpp:

Go to the source code of this file.

Namespaces
namespace	toolbox
namespace	toolbox::pcl

Macros
#define	LOG_ERROR_S   toolbox::logger::thread_logger_t::instance().error_s()
#define	LOG_WARN_S   toolbox::logger::thread_logger_t::instance().warn_s()
#define	LOG_INFO_S   toolbox::logger::thread_logger_t::instance().info_s()

Typedefs
using	toolbox::pcl::ransac_registration = ransac_registration_t< float >
using	toolbox::pcl::prosac_registration = prosac_registration_t< float >
using	toolbox::pcl::four_pcs_registration = four_pcs_registration_t< float >
using	toolbox::pcl::super_four_pcs_registration = super_four_pcs_registration_t< float >
using	toolbox::pcl::coarse_registration_result = registration_result_t< float >
using	toolbox::pcl::ransac_registration_d = ransac_registration_t< double >
using	toolbox::pcl::prosac_registration_d = prosac_registration_t< double >
using	toolbox::pcl::four_pcs_registration_d = four_pcs_registration_t< double >
using	toolbox::pcl::super_four_pcs_registration_d = super_four_pcs_registration_t< double >
using	toolbox::pcl::coarse_registration_result_d = registration_result_t< double >
using	toolbox::pcl::point_to_point_icp = point_to_point_icp_t< float >
using	toolbox::pcl::point_to_plane_icp = point_to_plane_icp_t< float >
using	toolbox::pcl::generalized_icp = generalized_icp_t< float >
using	toolbox::pcl::aa_icp = aa_icp_t< float >
using	toolbox::pcl::ndt = ndt_t< float >
using	toolbox::pcl::fine_registration_result = fine_registration_result_t< float >
using	toolbox::pcl::point_to_point_icp_d = point_to_point_icp_t< double >
using	toolbox::pcl::point_to_plane_icp_d = point_to_plane_icp_t< double >
using	toolbox::pcl::generalized_icp_d = generalized_icp_t< double >
using	toolbox::pcl::aa_icp_d = aa_icp_t< double >
using	toolbox::pcl::ndt_d = ndt_t< double >
using	toolbox::pcl::fine_registration_result_d = fine_registration_result_t< double >

Functions
template<typename DataType >
Eigen::Matrix< DataType, 4, 4 >	toolbox::pcl::complete_registration (const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &source, const std::shared_ptr< toolbox::types::point_cloud_t< DataType > > &target, bool use_coarse=true, const std::string &fine_algorithm="p2p")
	配准算法选择指南 / Registration algorithm selection guide

Detailed Description

点云配准算法统一导出文件 / Unified export file for point cloud registration algorithms

该文件提供了点云配准的统一接口，包括粗配准和细配准算法。 This file provides a unified interface for point cloud registration, including both coarse and fine registration algorithms.

粗配准算法 / Coarse Registration Algorithms:

• RANSAC: 基于对应关系的随机采样一致性算法 / Correspondence-based random sample consensus
• PROSAC: 渐进式采样一致性，利用对应关系质量排序 / Progressive sample consensus with quality ordering
• 4PCS: 4点共面集算法，不需要初始对应关系 / 4-Point Congruent Sets, no initial correspondences needed
• Super4PCS: 优化的4PCS，适合大规模点云 / Optimized 4PCS for large-scale point clouds

细配准算法 / Fine Registration Algorithms:

• Point-to-Point ICP: 基础ICP算法 / Basic ICP algorithm
• Point-to-Plane ICP: 点到平面ICP，需要法线 / Point-to-plane ICP, requires normals
• Generalized ICP: 平面到平面ICP / Plane-to-plane ICP
• AA-ICP: Anderson加速的ICP / Anderson Accelerated ICP
• NDT: 正态分布变换 / Normal Distributions Transform

#include <cpp-toolbox/pcl/registration/registration.hpp>
 
using namespace toolbox::pcl;
 
// 粗配准示例 / Coarse registration example
super_four_pcs_registration_t<float> coarse_reg;
coarse_reg.set_source(source_cloud);
coarse_reg.set_target(target_cloud);
coarse_reg.set_delta(0.01f);     // 1cm精度 / 1cm accuracy
coarse_reg.set_overlap(0.5f);    // 50%重叠 / 50% overlap
 
coarse_registration_result_t<float> coarse_result;
if (coarse_reg.align(coarse_result)) {
    // 使用粗配准结果作为细配准的初始值
    // Use coarse result as initial guess for fine registration
}
 
// 细配准示例 / Fine registration example
point_to_point_icp_t<float> fine_reg;
fine_reg.set_source(source_cloud);
fine_reg.set_target(target_cloud);
fine_reg.set_max_iterations(50);
 
fine_registration_result_t<float> fine_result;
fine_reg.align(coarse_result.transformation, fine_result);

Macro Definition Documentation

LOG_ERROR_S

#define LOG_ERROR_S   toolbox::logger::thread_logger_t::instance().error_s()

LOG_INFO_S

#define LOG_INFO_S   toolbox::logger::thread_logger_t::instance().info_s()

LOG_WARN_S

#define LOG_WARN_S   toolbox::logger::thread_logger_t::instance().warn_s()