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EVPA.cpp
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#include "EVPA.h"
void EVPA::DisplayVoxel(ros::Publisher &pub_voxel,ros::Publisher &pub_plane,ros::Publisher &pub_notplane)
{
}
void EVPA::CutVoxel(PointCloudPtr &pcd,trajectory &traj,int n_scan)
{
float voxel_location[3];
for(int i =0;i<pcd->points.size();i++)
{
PointType p_t;
tool::TransformPoint(pcd->points[i],p_t,traj);
Eigen::Vector3d p_t_e(p_t.x,p_t.y,p_t.z);
Eigen::Vector3d p_o_e(pcd->points[i].x,pcd->points[i].y,pcd->points[i].z);
voxel_location[0] = p_t.x/voxel_size;
voxel_location[1] = p_t.y/voxel_size;
voxel_location[2] = p_t.z/voxel_size;
if(voxel_location[0]<0) voxel_location[0] -=1.0;
if(voxel_location[1]<0) voxel_location[1] -=1.0;
if(voxel_location[2]<0) voxel_location[2] -=1.0;
VoxelLocation loc( (int64_t)voxel_location[0],(int64_t)voxel_location[1],(int64_t)voxel_location[2]);
std::unordered_map<VoxelLocation,Voxel*>::iterator iter = Voxelized_map.find(loc);
if(iter!=Voxelized_map.end())
{
iter->second->PushBack(p_o_e,p_t_e,n_scan);
}
else
{
Voxel* vox =new Voxel(pose_size);
vox->PushBack(p_o_e,p_t_e,n_scan);
vox->voxel_center[0] = (0.5+loc.x)*voxel_size;
vox->voxel_center[1] = (0.5+loc.y)*voxel_size;
vox->voxel_center[2] = (0.5+loc.z)*voxel_size;
Voxelized_map[loc]=vox;
}
}
}
void EVPA::SolveWithFactorGraph(ros::Publisher &pub_voxel,ros::Publisher &pub_plane,ros::Publisher &pub_notplane,std::vector<trajectory> &traj_s)
{
LOG(INFO)<<"begin to construct factor graph...\n";
TicToc t_solver;
t_solver.tic();
//std::unordered_map<int,int> problem_indices;
std::vector<int> problem_indices;
std::unordered_map<int,ceres::Problem*> problems;
//ceres::Problem problem;
last_plane_count = plane_count;
overlap_count = 0;
plane_count = 0;
notplane_count = 0;
//PointCloudPtr plane(new PointCloud);
//PointCloudPtr notplane(new PointCloud);
#pragma omp parallel
{
#pragma omp single
{
for (std::unordered_map<VoxelLocation, Voxel *>::iterator iter = Voxelized_map.begin(); iter != Voxelized_map.end(); iter++)
#pragma omp task
{
// 寻找重叠部分的体素
std::vector<int> pose_index;
// std::unordered_map<int,std::pair<int,int>> relative_pose_graph_this_voxel;
for (int i = 0; i < pose_size; i++)
{
// 30
if (iter->second->pts_trans[i].size() < 15)
continue;
pose_index.push_back(i);
}
// if (pose_index.size() < 2)
// continue;
//
#pragma omp critical
{
if (pose_index.size() >= 3)
overlap_count++;
}
// plane factors
if (pose_index.size() >= 2)
{
bool judge = iter->second->JudgePlane(pose_size);
// 如果有重叠部分的体素，则构建因子图,从后往前（root）配准
// i -> j
for (int i = pose_index.size() - 1; i >= 1; i--)
{
for (int j = i - 1; j >= 0; j--)
{
if(pose_index[i]-pose_index[j]>=reliable_region)
break;
int relative_index = pose_index[i] + pose_index[j] * pose_size;
#pragma omp critical
{
if (relative_pose_graph.find(relative_index) == relative_pose_graph.end())
{
// ceres::Problem* problem = new ceres::Problem;
ceres::Problem *problem = new ceres::Problem;
ceres::Manifold *manifold = new ceres::EigenQuaternionManifold();
//problem_indices.push_back(relative_index);
problems[relative_index] = problem;
// problem_indices[relative_index] = problems.size()-1;
relative_pose_graph[relative_index] = std::make_pair(pose_index[i], pose_index[j]);
Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
// std::cout<<"original "<<relative_index<<"-> \n"<<q_j_i.toRotationMatrix()<<"\n";
// std::cout<<t_j_i<<"\n";
relative_pose[relative_index] = temp;
relative_pose_point[relative_index] = temp;
relative_pose_point2point[relative_index] =temp;
problems[relative_index]->AddParameterBlock(relative_pose[relative_index].para_q, 4, manifold);
problems[relative_index]->AddParameterBlock(relative_pose[relative_index].para_t, 3);
//problems[relative_index]->AddParameterBlock(relative_pose_point[relative_index].para_q, 4, manifold);
//problems[relative_index]->AddParameterBlock(relative_pose_point[relative_index].para_t, 3);
//problems[relative_index]->AddParameterBlock(relative_pose_point[relative_index].para_t, 3);
// problems[relative_index].AddParameterBlock(relative_pose[relative_index].para_q, 4, manifold);
// problems[relative_index].AddParameterBlock(relative_pose[relative_index].para_t, 3);
// problem.AddParameterBlock(relative_pose[pose_index[i] + pose_index[j] * pose_size].para_q, 4, manifold);
// problem.AddParameterBlock(relative_pose[pose_index[i] + pose_index[j] * pose_size].para_t, 3);
}
}
// add factors
if (judge)
{
#pragma omp critical
{
plane_count++;
Voxelized_map_plane_visualize.push_back(iter->second);
pose_index_each_voxel.push_back(pose_index);
}
// 从大序号向小序号配准
// for (int i = pose_index.size() - 1; i >= 1; i--)
// {
// for (int j = i - 1; j >= 0; j--)
// {
// int relative_index = index_i + index_j * pose_size;
// relative_pose_graph_this_voxel[pose_index[i] + pose_index[j] * pose_size] = std::make_pair(pose_index[i], pose_index[j]);
// if(relative_pose.find(relative_index)== relative_pose.end())
// {
// Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
// Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
// Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
// Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
// Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
// Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
// trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
// relative_pose[relative_index] = temp;
// }
PointCloudPtr target(new PointCloud);
for (int k = 0; k < iter->second->pts_orig[pose_index[j]].size(); k++)
{
PointType temp(iter->second->pts_orig[pose_index[j]][k].x(), iter->second->pts_orig[pose_index[j]][k].y(), iter->second->pts_orig[pose_index[j]][k].z());
target->points.push_back(temp);
}
pcl::KdTreeFLANN<PointType> kdtree;
kdtree.setInputCloud(target);
for (int k = 0; k < iter->second->pts_orig[pose_index[i]].size(); k++)
{
std::vector<float> distances;
std::vector<int> indices;
PointType temp(iter->second->pts_orig[pose_index[i]][k].x(), iter->second->pts_orig[pose_index[i]][k].y(), iter->second->pts_orig[pose_index[i]][k].z());
PointType temp_trans;
tool::TransformPoint(temp, temp_trans, relative_pose[relative_index]);
kdtree.nearestKSearch(temp_trans, PLANE_FITTING_NUM, indices, distances);
Eigen::Matrix<double, PLANE_FITTING_NUM, 3> matA0;
Eigen::Matrix<double, PLANE_FITTING_NUM, 1> matB0 = -1 * Eigen::Matrix<double, PLANE_FITTING_NUM, 1>::Ones();
if (distances[4] < 1.0)
{
for (int j = 0; j < PLANE_FITTING_NUM; j++)
{
matA0(j, 0) = target->points[indices[j]].x;
matA0(j, 1) = target->points[indices[j]].y;
matA0(j, 2) = target->points[indices[j]].z;
}
// 计算平面法向量
Eigen::Vector3d norm = matA0.colPivHouseholderQr().solve(matB0);
double negative_OA_dot_norm = 1 / norm.norm();
norm.normalize();
// 如果有点距离平面太远，则该平面拟合的不好
bool plane_valid = true;
for (int j = 0; j < PLANE_FITTING_NUM; j++)
{
if (fabs(norm(0) * target->points[indices[j]].x +
norm(1) * target->points[indices[j]].y +
norm(2) * target->points[indices[j]].z + negative_OA_dot_norm) > 0.2)
{
plane_valid = false;
break;
}
}
Eigen::Vector3d curr_point(iter->second->pts_orig[pose_index[i]][k].x(), iter->second->pts_orig[pose_index[i]][k].y(), iter->second->pts_orig[pose_index[i]][k].z());
if (plane_valid)
{
ceres::LossFunction *loss_function = new ceres::HuberLoss(0.1);
ceres::CostFunction *cost_function = new Point2PlaneOptimize(curr_point, norm, negative_OA_dot_norm);
#pragma omp critical
{
problems[relative_index]->AddResidualBlock(cost_function, loss_function, relative_pose[relative_index].para_q, relative_pose[relative_index].para_t);
// problems[relative_index].AddResidualBlock(cost_function, nullptr, relative_pose[relative_index].para_q, relative_pose[relative_index].para_t);
// problem.AddResidualBlock(cost_function, nullptr, relative_pose[pose_index[i] + pose_index[j] * pose_size].para_q, relative_pose[pose_index[i] + pose_index[j] * pose_size].para_t);
}
}
}
}
// }
// }
}
else
{
#pragma omp critical
{
notplane_count++;
}
// for (int i = pose_index.size() - 1; i >= 1; i--)
// {
// for (int j = i - 1; j >= 0; j--)
// {
// int relative_index = pose_index[i] + pose_index[j] * pose_size;
// relative_pose_graph_this_voxel[pose_index[i] + pose_index[j] * pose_size] = std::make_pair(pose_index[i], pose_index[j]);
// #pragma omp critical
// {
// if (relative_pose_graph.find(relative_index) == relative_pose_graph.end())
// {
// //ceres::Problem* problem =new ceres::Problem;
// ceres::Problem* problem = new ceres::Problem;
// ceres::Manifold *manifold = new ceres::EigenQuaternionManifold();
// problems[relative_index] = problem;
// //problem_indices[relative_index] = problems.size()-1;
// relative_pose_graph[relative_index] = std::make_pair(pose_index[i], pose_index[j]);
// Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
// Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
// Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
// Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
// Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
// Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
// trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
// relative_pose_point[relative_index] = temp;
// relative_pose[relative_index] = temp;
// problems[relative_index]->AddParameterBlock(relative_pose_point[relative_index].para_q, 4, manifold);
// problems[relative_index]->AddParameterBlock(relative_pose_point[relative_index].para_t, 3);
// //problems[relative_index].AddParameterBlock(relative_pose_point[relative_index].para_q, 4, manifold);
// //problems[relative_index].AddParameterBlock(relative_pose_point[relative_index].para_t, 3);
// // problem.AddParameterBlock(relative_pose_point[pose_index[i] + pose_index[j] * pose_size].para_q, 4, manifold);
// // problem.AddParameterBlock(relative_pose_point[pose_index[i] + pose_index[j] * pose_size].para_t, 3);
// }
// }
// if(relative_pose_point.find(relative_index)== relative_pose_point.end())
// {
// Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
// Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
// Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
// Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
// Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
// Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
// trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
// relative_pose_point[relative_index] = temp;
// }
PointCloudPtr source(new PointCloud);
PointCloudPtr target(new PointCloud);
for (int k = 0; k < iter->second->pts_orig[pose_index[j]].size(); k++)
{
PointType temp(iter->second->pts_orig[pose_index[j]][k].x(), iter->second->pts_orig[pose_index[j]][k].y(), iter->second->pts_orig[pose_index[j]][k].z());
target->points.push_back(temp);
}
pcl::KdTreeFLANN<PointType> kdtree_target;
kdtree_target.setInputCloud(target);
for (int k = 0; k < iter->second->pts_orig[pose_index[i]].size(); k++)
{
PointType temp(iter->second->pts_orig[pose_index[i]][k].x(), iter->second->pts_orig[pose_index[i]][k].y(), iter->second->pts_orig[pose_index[i]][k].z());
PointType temp_trans;
// tool::TransformPoint(temp, temp_trans, relative_pose_point[relative_index]);
tool::TransformPoint(temp, temp_trans, relative_pose_point2point[relative_index]);
source->points.push_back(temp);
}
pcl::KdTreeFLANN<PointType> kdtree_source;
kdtree_source.setInputCloud(source);
// pcl::registration::CorrespondenceEstimation<PointType,PointType> corr_es;
// pcl::Correspondences temp;
// corr_es.setInputSource(source);
// corr_es.setInputTarget(target);
// corr_es.determineReciprocalCorrespondences(temp,0.1);
// for(int k=0;k<temp.size();k++)
// {
// Eigen::Vector3d curr(source->points[temp[k].index_query].x,source->points[temp[k].index_query].y,source->points[temp[k].index_query].z);
// Eigen::Vector3d map(target->points[temp[k].index_match].x,target->points[temp[k].index_match].y,target->points[temp[k].index_match].z);
// //ceres::CostFunction *cost_function = new Point2PointOptimize(curr,map);
// //problem.AddResidualBlock(cost_function,nullptr,relative_pose[pose_index[i] + pose_index[j] * pose_size].para_q,relative_pose[pose_index[i] + pose_index[j] * pose_size].para_t);
// }
for (int k = 0; k < iter->second->pts_orig[pose_index[i]].size(); k++)
{
PointType curr(source->points[k].x, source->points[k].y, source->points[k].z);
// if(!std::isfinite(curr.x)||!std::isfinite(curr.y)||!std::isfinite(curr.z))
// {
// std::cout<<"point: "<<curr.x<<curr.y<<curr.z<<"\n";
// continue;
// }
// Eigen::Vector3d map(target->points[temp[k].index_match].x,target->points[temp[k].index_match].y,target->points[temp[k].index_match].z);
std::vector<float> distances_t;
std::vector<int> indices_t;
std::vector<float> distances_s;
std::vector<int> indices_s;
kdtree_target.nearestKSearch(curr, 1, indices_t, distances_t);
kdtree_source.nearestKSearch(target->points[indices_t[0]], 1, indices_s, distances_s);
if (indices_s[0] == k && distances_t[0] < 0.1)
{
Eigen::Vector3d cp(iter->second->pts_orig[pose_index[i]][k].x(), iter->second->pts_orig[pose_index[i]][k].y(), iter->second->pts_orig[pose_index[i]][k].z());
Eigen::Vector3d map(target->points[indices_t[0]].x, target->points[indices_t[0]].y, target->points[indices_t[0]].z);
ceres::CostFunction *cost_function = Point2PointAuto::Create(cp, map);
ceres::LossFunction *loss_function = new ceres::HuberLoss(0.1);
#pragma omp critical
{
//problems[relative_index]->AddResidualBlock(cost_function, loss_function, relative_pose_point[relative_index].para_q, relative_pose_point[relative_index].para_t);
problems[relative_index]->AddResidualBlock(cost_function, loss_function, relative_pose[relative_index].para_q, relative_pose[relative_index].para_t);
// problems[relative_index].AddResidualBlock(cost_function, nullptr, relative_pose_point[relative_index].para_q, relative_pose_point[relative_index].para_t);
// problem.AddResidualBlock(cost_function, nullptr, relative_pose_point[pose_index[i] + pose_index[j] * pose_size].para_q, relative_pose_point[pose_index[i] + pose_index[j] * pose_size].para_t);
}
}
else
continue;
// ceres::CostFunction *cost_function = new Point2PointOptimize(curr,map);
// problem.AddResidualBlock(cost_function,nullptr,relative_pose[pose_index[i] + pose_index[j] * pose_size].para_q,relative_pose[pose_index[i] + pose_index[j] * pose_size].para_t);
}
// }
// }
}
}
}
}
}
}
}
LOG(INFO)<<"finished\n";
LOG(INFO)<<"number of voxels that overlap > 3 : "<<overlap_count<<"\n";
LOG(INFO)<<"plane optimization num: "<<plane_count<<"\n";
LOG(INFO)<<"point optimization num: "<<notplane_count<<"\n";
if(last_plane_count>=plane_count)
{
solve_flag = false;
LOG(INFO)<<"termination criteria is satisfied.\n";
return;
}
LOG(INFO)<<"problem size:"<<problems.size()<<"\n";
LOG(INFO)<<"relative pose size: "<<relative_pose_graph.size()<<"\n";
LOG(INFO) <<"solving problem...\n";
// ceres::Solve(options,&problem,&sum);
#pragma omp parallel
{
#pragma omp single
{
for (auto iter = problems.begin();iter!=problems.end();iter++)
#pragma omp task
{
// if(iter->second->NumResidualBlocks()>200000)
// {
ceres::Solver::Options options;
options.linear_solver_type = ceres::LinearSolverType::DENSE_QR;
options.max_num_iterations = 8;
options.num_threads = 1;
ceres::Solver::Summary sum;
ceres::Solve(options, iter->second, &sum);
// }
// std::vector<const double*> cov_blocks;
// cov_blocks.push_back(relative_pose[iter->first].para_q);
// cov_blocks.push_back(relative_pose[iter->first].para_t);
// //cov_blocks.push_back();
// //std::vector<std::pair<const double*,const double*>> cov_blocks;
// //cov_blocks.push_back(std::make_pair(relative_pose[iter->first].para_q,relative_pose[iter->first].para_q));
// //cov_blocks.push_back(std::make_pair(relative_pose[iter->first].para_t,relative_pose[iter->first].para_t));
// //cov_blocks.push_back(std::make_pair(relative_pose[iter->first].para_q,relative_pose[iter->first].para_t));
// ceres::Covariance::Options cov_options;
// cov_options.algorithm_type = ceres::CovarianceAlgorithmType::DENSE_SVD;
// ceres::Covariance cov(cov_options);
// CHECK(cov.Compute(cov_blocks,iter->second));
//cov.GetCovarianceBlockInTangentSpace(relative_pose[iter->first].para_q,relative_pose[iter->first].para_q,relative_pose[iter->first].covariance_q);
//cov.GetCovarianceBlock(relative_pose[iter->first].para_t,relative_pose[iter->first].para_t,relative_pose[iter->first].covariance_t);
//cov.GetCovarianceMatrixInTangentSpace(cov_blocks,relative_pose[iter->first].covariance_q_t);
delete iter->second;
}
}
}
//problems.clear();
double time =t_solver.toc();
LOG(INFO) <<"relative poses are sovled in "<<time<<" secs\n";
cost_time +=time;
// if(plane->points.size()!=0)
// {
// pcl::io::savePCDFileBinary("/home/sgg-whu/TLS/EVPA/src/data/result/plane.pcd",*plane);
// }
// if(notplane->points.size()!=0)
// {
// pcl::io::savePCDFileBinary("/home/sgg-whu/TLS/EVPA/src/data/result/notplane.pcd",*notplane);
// }
}
void EVPA::PrintRelativePoseGraph()
{
std::vector<int> graph(pose_size*pose_size,0);
for(auto iter:relative_pose_graph)
{
graph[iter.second.second*pose_size+iter.second.first] = 1;
graph[iter.second.first*pose_size+iter.second.second] = 1;
}
for(int i =0;i<pose_size;i++)
{
for(int j=0;j<pose_size;j++)
{
std::cout<<graph[i*pose_size+j]<<" ";
}
std::cout<<"\n";
}
}
void EVPA::PoseGraphOptimization(std::vector<trajectory> &traj_s)
{
if(!solve_flag)
return;
LOG(INFO)<<"start the pose graph optimization...\n";
TicToc pose_grpah_solver;
pose_grpah_solver.tic();
ceres::Problem problem;
ceres::Solver::Options options;
options.linear_solver_type = ceres::DENSE_QR;
options.max_num_iterations = 200;
options.num_threads = 16;
ceres::Manifold *manifold = new ceres::EigenQuaternionManifold();
ceres::Solver::Summary sum;
//point2plane factor
for(auto iter:relative_pose)
{
std::pair<int,int> col_raw = relative_pose_graph[iter.first];
ceres::LossFunction *loss_function = new ceres::HuberLoss(0.1);
// Eigen::Quaterniond q_esti(iter.second.para_q[3],iter.second.para_q[0],iter.second.para_q[1],iter.second.para_q[2]);
// Eigen::Vector3d t_esti(iter.second.para_t[0],iter.second.para_t[1],iter.second.para_t[2]);
// Eigen::Quaterniond q_init(relative_pose_point[iter.first].para_q[3],relative_pose_point[iter.first].para_q[0],relative_pose_point[iter.first].para_q[1],relative_pose_point[iter.first].para_q[2]);
// Eigen::Vector3d t_init(relative_pose_point[iter.first].para_t[0],relative_pose_point[iter.first].para_t[1],relative_pose_point[iter.first].para_t[2]);
// double distance = (t_esti-t_init).norm();
// double angle = Eigen::AngleAxisd(q_esti.conjugate()*q_init).angle();
// if(angle>0.001308 || distance > 0.2)
// continue;
//ceres::CostFunction *cost_function = PoseGraphOptimizeAuto::Create(iter.second.para_q,iter.second.para_t,iter.second.covariance_q_t); covariance
//ceres::CostFunction *cost_function = PoseGraphOptimizeAuto::Create(iter.second.para_q,iter.second.para_t);
ceres::CostFunction *cost_function = new PoseGraphOptimize(iter.second.para_q,iter.second.para_t);
problem.AddResidualBlock(cost_function,loss_function,traj_s[col_raw.second].para_q,traj_s[col_raw.second].para_t,traj_s[col_raw.first].para_q,traj_s[col_raw.first].para_t);
problem.SetManifold(traj_s[col_raw.second].para_q,manifold);
problem.SetManifold(traj_s[col_raw.first].para_q,manifold);
}
// //point2point factor
// for(auto iter:relative_pose_point2point)
// {
// std::pair<int,int> col_raw = relative_pose_graph[iter.first];
// ceres::LossFunction *loss_function = new ceres::HuberLoss(0.1);
// Eigen::Quaterniond q_esti(iter.second.para_q[3],iter.second.para_q[0],iter.second.para_q[1],iter.second.para_q[2]);
// Eigen::Vector3d t_esti(iter.second.para_t[0],iter.second.para_t[1],iter.second.para_t[2]);
// Eigen::Quaterniond q_init(relative_pose_point[iter.first].para_q[3],relative_pose_point[iter.first].para_q[0],relative_pose_point[iter.first].para_q[1],relative_pose_point[iter.first].para_q[2]);
// Eigen::Vector3d t_init(relative_pose_point[iter.first].para_t[0],relative_pose_point[iter.first].para_t[1],relative_pose_point[iter.first].para_t[2]);
// double distance = (t_esti-t_init).norm();
// double angle = Eigen::AngleAxisd(q_esti.conjugate()*q_init).angle();
// if(angle>0.001308 || distance > 0.2)
// continue;
// ceres::CostFunction *cost_function = PoseGraphOptimizeAuto::Create(iter.second.para_q,iter.second.para_t);
// problem.AddResidualBlock(cost_function,loss_function,traj_s[col_raw.second].para_q,traj_s[col_raw.second].para_t,traj_s[col_raw.first].para_q,traj_s[col_raw.first].para_t);
// problem.SetManifold(traj_s[col_raw.second].para_q,manifold);
// problem.SetManifold(traj_s[col_raw.first].para_q,manifold);
// }
problem.SetParameterBlockConstant(traj_s[0].para_q);
problem.SetParameterBlockConstant(traj_s[0].para_t);
ceres::Solve(options,&problem,&sum);
double time = pose_grpah_solver.toc();
LOG(INFO)<<"pose graph optimization is done in "<<pose_grpah_solver.toc()<<" secs.\n\n";
cost_time+=time;
}
void EVPA::init()
{
relative_pose.clear();
relative_pose_graph.clear();
for(auto voxel:Voxelized_map)
{
delete voxel.second;
}
Voxelized_map.clear();
Voxelized_map_plane_visualize.clear();
pose_index_each_voxel.clear();
}
void EVPA::SolveWithICP(std::vector<PointCloudPtr> &pcs,std::vector<trajectory> &traj_s)
{
std::cout<<"begin to solve with icp...\n";
for (std::unordered_map<VoxelLocation, Voxel *>::iterator iter = Voxelized_map.begin(); iter != Voxelized_map.end(); iter++)
{
// 寻找重叠部分的体素
std::vector<int> pose_index;
// std::unordered_map<int,std::pair<int,int>> relative_pose_graph_this_voxel;
for (int i = 0; i < pose_size; i++)
{
if (iter->second->pts_trans[i].size() < 30)
continue;
pose_index.push_back(i);
}
// 如果有重叠部分的体素，则构建因子图,从后往前（root）配准
// if (pose_index.size() < 2)
// continue;
//
// plane factors
if (pose_index.size() >= 2)
{
for (int i = pose_index.size() - 1; i >= 1; i--)
{
for (int j = i - 1; j >= 0; j--)
{
if(pose_index[i]-pose_index[j]>=reliable_region)
break;
int relative_index = pose_index[i] + pose_index[j] * pose_size;
if (relative_pose_graph.find(relative_index) == relative_pose_graph.end())
{
relative_pose_graph[relative_index] = std::make_pair(pose_index[i], pose_index[j]);
Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
relative_pose[relative_index] = temp;
}
}
}
}
}
std::cout<<"relative pose size: "<<relative_pose.size()<<"\n";
TicToc t_solver;
t_solver.tic();
#pragma omp parallel
{
#pragma omp single
{
for (auto iter : relative_pose_graph)
#pragma omp task
{
pcl::IterativeClosestPoint<PointType, PointType> icp;
pcl::PointCloud<PointType> res;
Eigen::Quaterniond q_r(relative_pose[iter.first].para_q[3], relative_pose[iter.first].para_q[0], relative_pose[iter.first].para_q[1], relative_pose[iter.first].para_q[2]);
Eigen::Affine3d aff;
aff.linear() = q_r.toRotationMatrix();
aff.translation() << relative_pose[iter.first].para_t[0], relative_pose[iter.first].para_t[1], relative_pose[iter.first].para_t[2];
icp.setInputSource(pcs[iter.second.first]);
icp.setInputTarget(pcs[iter.second.second]);
icp.setMaxCorrespondenceDistance(0.1);
icp.setUseReciprocalCorrespondences(true);
icp.setMaximumIterations(1);
icp.align(res, aff.matrix().cast<float>());
Eigen::Affine3d aff_res;
aff_res.matrix() = icp.getFinalTransformation().cast<double>();
Eigen::Quaterniond q(aff_res.rotation());
relative_pose[iter.first].para_q[0] = q.x();
relative_pose[iter.first].para_q[1] = q.y();
relative_pose[iter.first].para_q[2] = q.z();
relative_pose[iter.first].para_q[3] = q.w();
relative_pose[iter.first].para_t[0] = aff_res.translation()(0, 0);
relative_pose[iter.first].para_t[1] = aff_res.translation()(1, 0);
relative_pose[iter.first].para_t[2] = aff_res.translation()(2, 0);
}
}
}
double time = t_solver.toc();
std::cout<<"finished\n";
std::cout <<"relative poses are sovled in "<<time<<" secs\n";
cost_time +=time;
}
void EVPA::SolveWithICPNormal(std::vector<PointCloudPtr> &pcs,std::vector<trajectory> &traj_s)
{
std::cout<<"begin to solve with point to plane icp...\n";
for (std::unordered_map<VoxelLocation, Voxel *>::iterator iter = Voxelized_map.begin(); iter != Voxelized_map.end(); iter++)
{
// 寻找重叠部分的体素
std::vector<int> pose_index;
// std::unordered_map<int,std::pair<int,int>> relative_pose_graph_this_voxel;
for (int i = 0; i < pose_size; i++)
{
if (iter->second->pts_trans[i].size() < 30)
continue;
pose_index.push_back(i);
}
// 如果有重叠部分的体素，则构建因子图,从后往前（root）配准
// if (pose_index.size() < 2)
// continue;
//
// plane factors
if (pose_index.size() >= 2)
{
for (int i = pose_index.size() - 1; i >= 1; i--)
{
for (int j = i - 1; j >= 0; j--)
{
if(pose_index[i]-pose_index[j]>=reliable_region)
break;
int relative_index = pose_index[i] + pose_index[j] * pose_size;
if (relative_pose_graph.find(relative_index) == relative_pose_graph.end())
{
relative_pose_graph[relative_index] = std::make_pair(pose_index[i], pose_index[j]);
Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
relative_pose[relative_index] = temp;
}
}
}
}
}
std::vector<pcl::PointCloud<pcl::PointNormal>::Ptr> pcs_nomals(pcs.size());
std::cout<<"relative pose size: "<<relative_pose.size()<<"\n";
TicToc t_solver;
t_solver.tic();
#pragma omp parallel
{
#pragma omp single
{
for (int i=0;i<pcs.size();i++)
#pragma omp task
{
pcl::PointCloud<pcl::Normal>::Ptr pcs_nomal(new pcl::PointCloud<pcl::Normal>());
pcl::NormalEstimation<pcl::PointXYZ,pcl::Normal> ne;
//pcl::search::KdTree<pcl::PointXYZ>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZ>());
ne.setInputCloud(pcs[i]);
ne.setRadiusSearch(0.1);
//ne.setSearchMethod(tree);
ne.compute(*pcs_nomal);
pcl::PointCloud<pcl::PointNormal>::Ptr out(new pcl::PointCloud<pcl::PointNormal>());
pcl::concatenateFields(*pcs[i],*pcs_nomal,*out);
pcs_nomals[i]=out;
}
}
}
#pragma omp parallel
{
#pragma omp single
{
for (auto iter : relative_pose_graph)
#pragma omp task
{
pcl::registration::TransformationEstimationPointToPlaneLLS<pcl::PointNormal,pcl::PointNormal>::Ptr trans(new pcl::registration::TransformationEstimationPointToPlaneLLS<pcl::PointNormal,pcl::PointNormal>());
pcl::IterativeClosestPoint<pcl::PointNormal, pcl::PointNormal> icp;
pcl::PointCloud<pcl::PointNormal> res;
Eigen::Quaterniond q_r(relative_pose[iter.first].para_q[3], relative_pose[iter.first].para_q[0], relative_pose[iter.first].para_q[1], relative_pose[iter.first].para_q[2]);
Eigen::Affine3d aff;
aff.linear() = q_r.toRotationMatrix();
aff.translation() << relative_pose[iter.first].para_t[0], relative_pose[iter.first].para_t[1], relative_pose[iter.first].para_t[2];
icp.setInputSource(pcs_nomals[iter.second.first]);
icp.setInputTarget(pcs_nomals[iter.second.second]);
icp.setMaxCorrespondenceDistance(0.1);
icp.setUseReciprocalCorrespondences(true);
icp.setTransformationEstimation(trans);
icp.setMaximumIterations(1);
icp.align(res, aff.matrix().cast<float>());
Eigen::Affine3d aff_res;
aff_res.matrix() = icp.getFinalTransformation().cast<double>();
Eigen::Quaterniond q(aff_res.rotation());
relative_pose[iter.first].para_q[0] = q.x();
relative_pose[iter.first].para_q[1] = q.y();
relative_pose[iter.first].para_q[2] = q.z();
relative_pose[iter.first].para_q[3] = q.w();
relative_pose[iter.first].para_t[0] = aff_res.translation()(0, 0);
relative_pose[iter.first].para_t[1] = aff_res.translation()(1, 0);
relative_pose[iter.first].para_t[2] = aff_res.translation()(2, 0);
}
}
}
double time = t_solver.toc();
std::cout<<"finished\n";
std::cout <<"relative poses are sovled in "<<time<<" secs\n";
cost_time +=time;
}
void EVPA::SolveWithLum(std::vector<PointCloudPtr> &pcs,std::vector<trajectory> &traj_s)
{
std::cout<<"begin to solve with lum...\n";
for (std::unordered_map<VoxelLocation, Voxel *>::iterator iter = Voxelized_map.begin(); iter != Voxelized_map.end(); iter++)
{
// 寻找重叠部分的体素
std::vector<int> pose_index;
// std::unordered_map<int,std::pair<int,int>> relative_pose_graph_this_voxel;
for (int i = 0; i < pose_size; i++)
{
if (iter->second->pts_trans[i].size() < 30)
continue;
pose_index.push_back(i);
}
// 如果有重叠部分的体素，则构建因子图,从后往前（root）配准
// if (pose_index.size() < 2)
// continue;
//
// plane factors
if (pose_index.size() >= 2)
{
for (int i = pose_index.size() - 1; i >= 1; i--)
{
for (int j = i - 1; j >= 0; j--)
{
int relative_index = pose_index[i] + pose_index[j] * pose_size;
if (relative_pose_graph.find(relative_index) == relative_pose_graph.end())
{
if(pose_index[i]-pose_index[j]>=reliable_region)
break;
relative_pose_graph[relative_index] = std::make_pair(pose_index[i], pose_index[j]);
Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
relative_pose[relative_index] = temp;
}
}
}
}
}
std::vector<pcl::PointCloud<pcl::PointNormal>::Ptr> pcs_nomals;
std::cout<<"relative pose size: "<<relative_pose.size()<<"\n";
TicToc t_solver;
t_solver.tic();
pcl::registration::LUM<PointType> lum;
for(int i =0;i<pcs.size();i++)
{
Eigen::Quaternionf q_(traj_s[i].para_q[3],traj_s[i].para_q[0],traj_s[i].para_q[1],traj_s[i].para_q[2]);
Eigen::Affine3f traj;
traj.linear() = q_.toRotationMatrix();
traj.translation() << traj_s[i].para_t[0],traj_s[i].para_t[1],traj_s[i].para_t[2];
Eigen::Vector6f pose;
pcl::getTranslationAndEulerAngles(traj,pose[0],pose[1],pose[2],pose[3],pose[4],pose[5]);
lum.addPointCloud(pcs[i],pose);
}
lum.setMaxIterations(1);
//lum.setConvergenceThreshold(0.01);
//std::vector<pcl::Correspondences> corrs;
#pragma omp parallel
{
#pragma omp single
{
for (auto iter : relative_pose_graph)
#pragma omp task
{
pcl::registration::CorrespondenceEstimation<PointType, PointType> ce;
pcl::PointCloud<PointType>::Ptr temp(new pcl::PointCloud<PointType>());
Eigen::Quaternionf trans(relative_pose[iter.first].para_q[3],relative_pose[iter.first].para_q[0],relative_pose[iter.first].para_q[1],relative_pose[iter.first].para_q[2]);
Eigen::Affine3f aff;
aff.linear() = trans.toRotationMatrix();
aff.translation() << relative_pose[iter.first].para_t[0],relative_pose[iter.first].para_t[1],relative_pose[iter.first].para_t[2];
pcl::transformPointCloud(*pcs[iter.second.first],*temp,aff.matrix());
pcl::CorrespondencesPtr corr(new pcl::Correspondences);
ce.setInputSource(temp);
ce.setInputTarget(pcs[iter.second.second]);
ce.determineReciprocalCorrespondences(*corr, 0.1);
lum.setCorrespondences(iter.second.first, iter.second.second, corr);
}
}
}
std::cout<<"calculate correspondences done..\n";
lum.compute();
for(int i = 0;i<pcs.size();i++)
{
Eigen::Quaternionf q(lum.getTransformation(i).rotation());
traj_s[i].para_q[0] = q.x();
traj_s[i].para_q[1] = q.y();
traj_s[i].para_q[2] = q.z();
traj_s[i].para_q[3] = q.w();
traj_s[i].para_t[0] = lum.getTransformation(i).translation().x();
traj_s[i].para_t[1] = lum.getTransformation(i).translation().y();
traj_s[i].para_t[2] = lum.getTransformation(i).translation().z();
}
double time = t_solver.toc();
std::cout<<"finished\n";
std::cout <<"relative poses are sovled in "<<time<<" secs\n";
cost_time +=time;
}
void EVPA::SolveWithGICP(std::vector<PointCloudPtr> &pcs,std::vector<trajectory> &traj_s)
{
std::cout<<"begin to solve with gicp...\n";
for (std::unordered_map<VoxelLocation, Voxel *>::iterator iter = Voxelized_map.begin(); iter != Voxelized_map.end(); iter++)
{
// 寻找重叠部分的体素
std::vector<int> pose_index;
// std::unordered_map<int,std::pair<int,int>> relative_pose_graph_this_voxel;
for (int i = 0; i < pose_size; i++)
{
if (iter->second->pts_trans[i].size() < 30)
continue;
pose_index.push_back(i);
}
// 如果有重叠部分的体素，则构建因子图,从后往前（root）配准
// if (pose_index.size() < 2)
// continue;
//
// plane factors
if (pose_index.size() >= 2)
{
for (int i = pose_index.size() - 1; i >= 1; i--)
{
for (int j = i - 1; j >= 0; j--)
{
if(pose_index[i]-pose_index[j]>=reliable_region)
break;
int relative_index = pose_index[i] + pose_index[j] * pose_size;
if (relative_pose_graph.find(relative_index) == relative_pose_graph.end())
{
relative_pose_graph[relative_index] = std::make_pair(pose_index[i], pose_index[j]);
Eigen::Quaterniond q_j(traj_s[pose_index[j]].para_q[3], traj_s[pose_index[j]].para_q[0], traj_s[pose_index[j]].para_q[1], traj_s[pose_index[j]].para_q[2]);
Eigen::Quaterniond q_i(traj_s[pose_index[i]].para_q[3], traj_s[pose_index[i]].para_q[0], traj_s[pose_index[i]].para_q[1], traj_s[pose_index[i]].para_q[2]);
Eigen::Vector3d t_i(traj_s[pose_index[i]].para_t[0], traj_s[pose_index[i]].para_t[1], traj_s[pose_index[i]].para_t[2]);
Eigen::Vector3d t_j(traj_s[pose_index[j]].para_t[0], traj_s[pose_index[j]].para_t[1], traj_s[pose_index[j]].para_t[2]);
Eigen::Quaterniond q_j_i = q_j.conjugate() * q_i;
Eigen::Vector3d t_j_i = q_j.conjugate() * (t_i - t_j);
trajectory temp(q_j_i.x(), q_j_i.y(), q_j_i.z(), q_j_i.w(), t_j_i.x(), t_j_i.y(), t_j_i.z());
relative_pose[relative_index] = temp;
}
}
}
}
}
std::cout<<"relative pose size: "<<relative_pose.size()<<"\n";
TicToc t_solver;
t_solver.tic();
#pragma omp parallel
{
#pragma omp single
{
for (auto iter : relative_pose_graph)
#pragma omp task
{
pcl::GeneralizedIterativeClosestPoint<PointType, PointType> icp;
pcl::PointCloud<PointType> res;
Eigen::Quaterniond q_r(relative_pose[iter.first].para_q[3], relative_pose[iter.first].para_q[0], relative_pose[iter.first].para_q[1], relative_pose[iter.first].para_q[2]);