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#include "utility.h"
#include "lio_sam/cloud_info.h"
#include <gtsam/geometry/Rot3.h>
#include <gtsam/geometry/Pose3.h>
#include <gtsam/slam/PriorFactor.h>
#include <gtsam/slam/BetweenFactor.h>
#include <gtsam/navigation/GPSFactor.h>
#include <gtsam/navigation/ImuFactor.h>
#include <gtsam/navigation/CombinedImuFactor.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/nonlinear/Marginals.h>
#include <gtsam/nonlinear/Values.h>
#include <gtsam/inference/Symbol.h>
#include <gtsam/nonlinear/ISAM2.h>
using namespace gtsam;
using symbol_shorthand::X; // Pose3 (x,y,z,r,p,y)
using symbol_shorthand::V; // Vel (xdot,ydot,zdot)
using symbol_shorthand::B; // Bias (ax,ay,az,gx,gy,gz)
using symbol_shorthand::G; // GPS pose
/*
* A point cloud type that has 6D pose info ([x,y,z,roll,pitch,yaw] intensity is time stamp)
*/
struct PointXYZIRPYT
{
PCL_ADD_POINT4D
PCL_ADD_INTENSITY; // preferred way of adding a XYZ+padding
float roll;
float pitch;
float yaw;
double time;
EIGEN_MAKE_ALIGNED_OPERATOR_NEW // make sure our new allocators are aligned
} EIGEN_ALIGN16; // enforce SSE padding for correct memory alignment
POINT_CLOUD_REGISTER_POINT_STRUCT (PointXYZIRPYT,
(float, x, x) (float, y, y)
(float, z, z) (float, intensity, intensity)
(float, roll, roll) (float, pitch, pitch) (float, yaw, yaw)
(double, time, time))
typedef PointXYZIRPYT PointTypePose;
class mapOptimization : public ParamServer
{
public:
// gtsam
NonlinearFactorGraph gtSAMgraph;
Values initialEstimate;
Values optimizedEstimate;
ISAM2 *isam;
Values isamCurrentEstimate;
Eigen::MatrixXd poseCovariance;
ros::Publisher pubLaserCloudSurround;
ros::Publisher pubOdomAftMappedROS;
ros::Publisher pubKeyPoses;
ros::Publisher pubPath;
ros::Publisher pubHistoryKeyFrames;
ros::Publisher pubIcpKeyFrames;
ros::Publisher pubRecentKeyFrames;
ros::Publisher pubRecentKeyFrame;
ros::Publisher pubCloudRegisteredRaw;
ros::Subscriber subLaserCloudInfo;
ros::Subscriber subGPS;
std::deque<nav_msgs::Odometry> gpsQueue;
lio_sam::cloud_info cloudInfo;
vector<pcl::PointCloud<PointType>::Ptr> cornerCloudKeyFrames;
vector<pcl::PointCloud<PointType>::Ptr> surfCloudKeyFrames;
pcl::PointCloud<PointType>::Ptr cloudKeyPoses3D;
pcl::PointCloud<PointTypePose>::Ptr cloudKeyPoses6D;
pcl::PointCloud<PointType>::Ptr laserCloudCornerLast; // corner feature set from odoOptimization
pcl::PointCloud<PointType>::Ptr laserCloudSurfLast; // surf feature set from odoOptimization
pcl::PointCloud<PointType>::Ptr laserCloudCornerLastDS; // downsampled corner featuer set from odoOptimization
pcl::PointCloud<PointType>::Ptr laserCloudSurfLastDS; // downsampled surf featuer set from odoOptimization
pcl::PointCloud<PointType>::Ptr laserCloudOri;
pcl::PointCloud<PointType>::Ptr coeffSel;
std::vector<PointType> laserCloudOriCornerVec; // corner point holder for parallel computation
std::vector<PointType> coeffSelCornerVec;
std::vector<bool> laserCloudOriCornerFlag;
std::vector<PointType> laserCloudOriSurfVec; // surf point holder for parallel computation
std::vector<PointType> coeffSelSurfVec;
std::vector<bool> laserCloudOriSurfFlag;
pcl::PointCloud<PointType>::Ptr laserCloudCornerFromMap;
pcl::PointCloud<PointType>::Ptr laserCloudSurfFromMap;
pcl::PointCloud<PointType>::Ptr laserCloudCornerFromMapDS;
pcl::PointCloud<PointType>::Ptr laserCloudSurfFromMapDS;
pcl::KdTreeFLANN<PointType>::Ptr kdtreeCornerFromMap;
pcl::KdTreeFLANN<PointType>::Ptr kdtreeSurfFromMap;
pcl::KdTreeFLANN<PointType>::Ptr kdtreeSurroundingKeyPoses;
pcl::KdTreeFLANN<PointType>::Ptr kdtreeHistoryKeyPoses;
pcl::PointCloud<PointType>::Ptr latestKeyFrameCloud;
pcl::PointCloud<PointType>::Ptr nearHistoryKeyFrameCloud;
pcl::VoxelGrid<PointType> downSizeFilterCorner;
pcl::VoxelGrid<PointType> downSizeFilterSurf;
pcl::VoxelGrid<PointType> downSizeFilterICP;
pcl::VoxelGrid<PointType> downSizeFilterSurroundingKeyPoses; // for surrounding key poses of scan-to-map optimization
ros::Time timeLaserInfoStamp;
double timeLaserCloudInfoLast;
float transformTobeMapped[6];
std::mutex mtx;
double timeLastProcessing = -1;
bool isDegenerate = false;
Eigen::Matrix<float, 6, 6> matP;
int laserCloudCornerFromMapDSNum = 0;
int laserCloudSurfFromMapDSNum = 0;
int laserCloudCornerLastDSNum = 0;
int laserCloudSurfLastDSNum = 0;
bool aLoopIsClosed = false;
int imuPreintegrationResetId = 0;
nav_msgs::Path globalPath;
Eigen::Affine3f transPointAssociateToMap;
mapOptimization()
{
ISAM2Params parameters;
parameters.relinearizeThreshold = 0.1;
parameters.relinearizeSkip = 1;
isam = new ISAM2(parameters);
pubKeyPoses = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/trajectory", 1);
pubLaserCloudSurround = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/map_global", 1);
pubOdomAftMappedROS = nh.advertise<nav_msgs::Odometry> ("lio_sam/mapping/odometry", 1);
pubPath = nh.advertise<nav_msgs::Path>("lio_sam/mapping/path", 1);
subLaserCloudInfo = nh.subscribe<lio_sam::cloud_info>("lio_sam/feature/cloud_info", 1, &mapOptimization::laserCloudInfoHandler, this, ros::TransportHints().tcpNoDelay());
subGPS = nh.subscribe<nav_msgs::Odometry> (gpsTopic, 200, &mapOptimization::gpsHandler, this, ros::TransportHints().tcpNoDelay());
pubHistoryKeyFrames = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/icp_loop_closure_history_cloud", 1);
pubIcpKeyFrames = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/icp_loop_closure_corrected_cloud", 1);
pubRecentKeyFrames = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/map_local", 1);
pubRecentKeyFrame = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/cloud_registered", 1);
pubCloudRegisteredRaw = nh.advertise<sensor_msgs::PointCloud2>("lio_sam/mapping/cloud_registered_raw", 1);
downSizeFilterCorner.setLeafSize(mappingCornerLeafSize, mappingCornerLeafSize, mappingCornerLeafSize);
downSizeFilterSurf.setLeafSize(mappingSurfLeafSize, mappingSurfLeafSize, mappingSurfLeafSize);
downSizeFilterICP.setLeafSize(mappingSurfLeafSize, mappingSurfLeafSize, mappingSurfLeafSize);
downSizeFilterSurroundingKeyPoses.setLeafSize(surroundingKeyframeDensity, surroundingKeyframeDensity, surroundingKeyframeDensity); // for surrounding key poses of scan-to-map optimization
allocateMemory();
}
void allocateMemory()
{
cloudKeyPoses3D.reset(new pcl::PointCloud<PointType>());
cloudKeyPoses6D.reset(new pcl::PointCloud<PointTypePose>());
kdtreeSurroundingKeyPoses.reset(new pcl::KdTreeFLANN<PointType>());
kdtreeHistoryKeyPoses.reset(new pcl::KdTreeFLANN<PointType>());
laserCloudCornerLast.reset(new pcl::PointCloud<PointType>()); // corner feature set from odoOptimization
laserCloudSurfLast.reset(new pcl::PointCloud<PointType>()); // surf feature set from odoOptimization
laserCloudCornerLastDS.reset(new pcl::PointCloud<PointType>()); // downsampled corner featuer set from odoOptimization
laserCloudSurfLastDS.reset(new pcl::PointCloud<PointType>()); // downsampled surf featuer set from odoOptimization
laserCloudOri.reset(new pcl::PointCloud<PointType>());
coeffSel.reset(new pcl::PointCloud<PointType>());
laserCloudOriCornerVec.resize(N_SCAN * Horizon_SCAN);
coeffSelCornerVec.resize(N_SCAN * Horizon_SCAN);
laserCloudOriCornerFlag.resize(N_SCAN * Horizon_SCAN);
laserCloudOriSurfVec.resize(N_SCAN * Horizon_SCAN);
coeffSelSurfVec.resize(N_SCAN * Horizon_SCAN);
laserCloudOriSurfFlag.resize(N_SCAN * Horizon_SCAN);
std::fill(laserCloudOriCornerFlag.begin(), laserCloudOriCornerFlag.end(), false);
std::fill(laserCloudOriSurfFlag.begin(), laserCloudOriSurfFlag.end(), false);
laserCloudCornerFromMap.reset(new pcl::PointCloud<PointType>());
laserCloudSurfFromMap.reset(new pcl::PointCloud<PointType>());
laserCloudCornerFromMapDS.reset(new pcl::PointCloud<PointType>());
laserCloudSurfFromMapDS.reset(new pcl::PointCloud<PointType>());
kdtreeCornerFromMap.reset(new pcl::KdTreeFLANN<PointType>());
kdtreeSurfFromMap.reset(new pcl::KdTreeFLANN<PointType>());
latestKeyFrameCloud.reset(new pcl::PointCloud<PointType>());
nearHistoryKeyFrameCloud.reset(new pcl::PointCloud<PointType>());
for (int i = 0; i < 6; ++i){
transformTobeMapped[i] = 0;
}
matP.setZero();
}
void laserCloudInfoHandler(const lio_sam::cloud_infoConstPtr& msgIn)
{
// extract time stamp
timeLaserInfoStamp = msgIn->header.stamp;
timeLaserCloudInfoLast = msgIn->header.stamp.toSec();
// extract info and feature cloud
cloudInfo = *msgIn;
pcl::fromROSMsg(msgIn->cloud_corner, *laserCloudCornerLast);
pcl::fromROSMsg(msgIn->cloud_surface, *laserCloudSurfLast);
std::lock_guard<std::mutex> lock(mtx);
if (timeLaserCloudInfoLast - timeLastProcessing >= mappingProcessInterval) {
timeLastProcessing = timeLaserCloudInfoLast;
updateInitialGuess();
extractSurroundingKeyFrames();
downsampleCurrentScan();
scan2MapOptimization();
saveKeyFramesAndFactor();
correctPoses();
publishOdometry();
publishFrames();
}
}
void gpsHandler(const nav_msgs::Odometry::ConstPtr& gpsMsg)
{
gpsQueue.push_back(*gpsMsg);
}
void pointAssociateToMap(PointType const * const pi, PointType * const po)
{
po->x = transPointAssociateToMap(0,0) * pi->x + transPointAssociateToMap(0,1) * pi->y + transPointAssociateToMap(0,2) * pi->z + transPointAssociateToMap(0,3);
po->y = transPointAssociateToMap(1,0) * pi->x + transPointAssociateToMap(1,1) * pi->y + transPointAssociateToMap(1,2) * pi->z + transPointAssociateToMap(1,3);
po->z = transPointAssociateToMap(2,0) * pi->x + transPointAssociateToMap(2,1) * pi->y + transPointAssociateToMap(2,2) * pi->z + transPointAssociateToMap(2,3);
po->intensity = pi->intensity;
}
pcl::PointCloud<PointType>::Ptr transformPointCloud(pcl::PointCloud<PointType>::Ptr cloudIn, PointTypePose* transformIn)
{
pcl::PointCloud<PointType>::Ptr cloudOut(new pcl::PointCloud<PointType>());
PointType *pointFrom;
int cloudSize = cloudIn->size();
cloudOut->resize(cloudSize);
Eigen::Affine3f transCur = pcl::getTransformation(transformIn->x, transformIn->y, transformIn->z, transformIn->roll, transformIn->pitch, transformIn->yaw);
for (int i = 0; i < cloudSize; ++i){
pointFrom = &cloudIn->points[i];
cloudOut->points[i].x = transCur(0,0) * pointFrom->x + transCur(0,1) * pointFrom->y + transCur(0,2) * pointFrom->z + transCur(0,3);
cloudOut->points[i].y = transCur(1,0) * pointFrom->x + transCur(1,1) * pointFrom->y + transCur(1,2) * pointFrom->z + transCur(1,3);
cloudOut->points[i].z = transCur(2,0) * pointFrom->x + transCur(2,1) * pointFrom->y + transCur(2,2) * pointFrom->z + transCur(2,3);
cloudOut->points[i].intensity = pointFrom->intensity;
}
return cloudOut;
}
gtsam::Pose3 pclPointTogtsamPose3(PointTypePose thisPoint)
{
return gtsam::Pose3(gtsam::Rot3::RzRyRx(double(thisPoint.roll), double(thisPoint.pitch), double(thisPoint.yaw)),
gtsam::Point3(double(thisPoint.x), double(thisPoint.y), double(thisPoint.z)));
}
gtsam::Pose3 trans2gtsamPose(float transformIn[])
{
return gtsam::Pose3(gtsam::Rot3::RzRyRx(transformIn[0], transformIn[1], transformIn[2]),
gtsam::Point3(transformIn[3], transformIn[4], transformIn[5]));
}
Eigen::Affine3f pclPointToAffine3f(PointTypePose thisPoint)
{
return pcl::getTransformation(thisPoint.x, thisPoint.y, thisPoint.z, thisPoint.roll, thisPoint.pitch, thisPoint.yaw);
}
Eigen::Affine3f trans2Affine3f(float transformIn[])
{
return pcl::getTransformation(transformIn[3], transformIn[4], transformIn[5], transformIn[0], transformIn[1], transformIn[2]);
}
PointTypePose trans2PointTypePose(float transformIn[])
{
PointTypePose thisPose6D;
thisPose6D.x = transformIn[3];
thisPose6D.y = transformIn[4];
thisPose6D.z = transformIn[5];
thisPose6D.roll = transformIn[0];
thisPose6D.pitch = transformIn[1];
thisPose6D.yaw = transformIn[2];
return thisPose6D;
}
void visualizeGlobalMapThread()
{
ros::Rate rate(0.2);
while (ros::ok()){
rate.sleep();
publishGlobalMap();
}
if (savePCD == false)
return;
cout << "****************************************************" << endl;
cout << "Saving map to pcd files ..." << endl;
// create directory and remove old files;
savePCDDirectory = std::getenv("HOME") + savePCDDirectory;
int unused = system((std::string("exec rm -r ") + savePCDDirectory).c_str());
unused = system((std::string("mkdir ") + savePCDDirectory).c_str());
// save key frame transformations
pcl::io::savePCDFileASCII(savePCDDirectory + "trajectory.pcd", *cloudKeyPoses3D);
pcl::io::savePCDFileASCII(savePCDDirectory + "transformations.pcd", *cloudKeyPoses6D);
// extract global point cloud map
pcl::PointCloud<PointType>::Ptr globalCornerCloud(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalCornerCloudDS(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalSurfCloud(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalSurfCloudDS(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalMapCloud(new pcl::PointCloud<PointType>());
for (int i = 0; i < (int)cloudKeyPoses3D->size(); i++) {
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*globalCornerCloud += *transformPointCloud(cornerCloudKeyFrames[i], &cloudKeyPoses6D->points[i]);
*globalSurfCloud += *transformPointCloud(surfCloudKeyFrames[i], &cloudKeyPoses6D->points[i]);
cout << "\r" << std::flush << "Processing feature cloud " << i << " of " << cloudKeyPoses6D->size() << " ...";
}
// down-sample and save corner cloud
downSizeFilterCorner.setInputCloud(globalCornerCloud);
downSizeFilterCorner.filter(*globalCornerCloudDS);
pcl::io::savePCDFileASCII(savePCDDirectory + "cloudCorner.pcd", *globalCornerCloudDS);
// down-sample and save surf cloud
downSizeFilterSurf.setInputCloud(globalSurfCloud);
downSizeFilterSurf.filter(*globalSurfCloudDS);
pcl::io::savePCDFileASCII(savePCDDirectory + "cloudSurf.pcd", *globalSurfCloudDS);
// down-sample and save global point cloud map
*globalMapCloud += *globalCornerCloud;
*globalMapCloud += *globalSurfCloud;
pcl::io::savePCDFileASCII(savePCDDirectory + "cloudGlobal.pcd", *globalMapCloud);
cout << "****************************************************" << endl;
cout << "Saving map to pcd files completed" << endl;
}
void publishGlobalMap()
{
if (pubLaserCloudSurround.getNumSubscribers() == 0)
return;
if (cloudKeyPoses3D->points.empty() == true)
return;
pcl::KdTreeFLANN<PointType>::Ptr kdtreeGlobalMap(new pcl::KdTreeFLANN<PointType>());;
pcl::PointCloud<PointType>::Ptr globalMapKeyPoses(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalMapKeyPosesDS(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalMapKeyFrames(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr globalMapKeyFramesDS(new pcl::PointCloud<PointType>());
// kd-tree to find near key frames to visualize
std::vector<int> pointSearchIndGlobalMap;
std::vector<float> pointSearchSqDisGlobalMap;
// search near key frames to visualize
mtx.lock();
kdtreeGlobalMap->setInputCloud(cloudKeyPoses3D);
kdtreeGlobalMap->radiusSearch(cloudKeyPoses3D->back(), globalMapVisualizationSearchRadius, pointSearchIndGlobalMap, pointSearchSqDisGlobalMap, 0);
mtx.unlock();
for (int i = 0; i < (int)pointSearchIndGlobalMap.size(); ++i)
globalMapKeyPoses->push_back(cloudKeyPoses3D->points[pointSearchIndGlobalMap[i]]);
// downsample near selected key frames
pcl::VoxelGrid<PointType> downSizeFilterGlobalMapKeyPoses; // for global map visualization
downSizeFilterGlobalMapKeyPoses.setLeafSize(globalMapVisualizationPoseDensity, globalMapVisualizationPoseDensity, globalMapVisualizationPoseDensity); // for global map visualization
downSizeFilterGlobalMapKeyPoses.setInputCloud(globalMapKeyPoses);
downSizeFilterGlobalMapKeyPoses.filter(*globalMapKeyPosesDS);
// extract visualized and downsampled key frames
for (int i = 0; i < (int)globalMapKeyPosesDS->size(); ++i){
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if (pointDistance(globalMapKeyPosesDS->points[i], cloudKeyPoses3D->back()) > globalMapVisualizationSearchRadius)
continue;
int thisKeyInd = (int)globalMapKeyPosesDS->points[i].intensity;
*globalMapKeyFrames += *transformPointCloud(cornerCloudKeyFrames[thisKeyInd], &cloudKeyPoses6D->points[thisKeyInd]);
*globalMapKeyFrames += *transformPointCloud(surfCloudKeyFrames[thisKeyInd], &cloudKeyPoses6D->points[thisKeyInd]);
}
// downsample visualized points
pcl::VoxelGrid<PointType> downSizeFilterGlobalMapKeyFrames; // for global map visualization
downSizeFilterGlobalMapKeyFrames.setLeafSize(globalMapVisualizationLeafSize, globalMapVisualizationLeafSize, globalMapVisualizationLeafSize); // for global map visualization
downSizeFilterGlobalMapKeyFrames.setInputCloud(globalMapKeyFrames);
downSizeFilterGlobalMapKeyFrames.filter(*globalMapKeyFramesDS);
publishCloud(&pubLaserCloudSurround, globalMapKeyFramesDS, timeLaserInfoStamp, "odom");
}
void loopClosureThread()
{
if (loopClosureEnableFlag == false)
return;
ros::Rate rate(0.2);
while (ros::ok())
{
rate.sleep();
performLoopClosure();
}
}
bool detectLoopClosure(int *latestID, int *closestID)
{
int latestFrameIDLoopCloure;
int closestHistoryFrameID;
latestKeyFrameCloud->clear();
nearHistoryKeyFrameCloud->clear();
std::lock_guard<std::mutex> lock(mtx);
// find the closest history key frame
std::vector<int> pointSearchIndLoop;
std::vector<float> pointSearchSqDisLoop;
kdtreeHistoryKeyPoses->setInputCloud(cloudKeyPoses3D);
kdtreeHistoryKeyPoses->radiusSearch(cloudKeyPoses3D->back(), historyKeyframeSearchRadius, pointSearchIndLoop, pointSearchSqDisLoop, 0);
closestHistoryFrameID = -1;
for (int i = 0; i < (int)pointSearchIndLoop.size(); ++i)
{
int id = pointSearchIndLoop[i];
if (abs(cloudKeyPoses6D->points[id].time - timeLaserCloudInfoLast) > historyKeyframeSearchTimeDiff)
{
closestHistoryFrameID = id;
break;
}
}
if (closestHistoryFrameID == -1)
return false;
if ((int)cloudKeyPoses3D->size() - 1 == closestHistoryFrameID)
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return false;
// save latest key frames
latestFrameIDLoopCloure = cloudKeyPoses3D->size() - 1;
*latestKeyFrameCloud += *transformPointCloud(cornerCloudKeyFrames[latestFrameIDLoopCloure], &cloudKeyPoses6D->points[latestFrameIDLoopCloure]);
*latestKeyFrameCloud += *transformPointCloud(surfCloudKeyFrames[latestFrameIDLoopCloure], &cloudKeyPoses6D->points[latestFrameIDLoopCloure]);
// save history near key frames
bool nearFrameAvailable = false;
for (int j = -historyKeyframeSearchNum; j <= historyKeyframeSearchNum; ++j)
{
if (closestHistoryFrameID + j < 0 || closestHistoryFrameID + j > latestFrameIDLoopCloure)
continue;
*nearHistoryKeyFrameCloud += *transformPointCloud(cornerCloudKeyFrames[closestHistoryFrameID+j], &cloudKeyPoses6D->points[closestHistoryFrameID+j]);
*nearHistoryKeyFrameCloud += *transformPointCloud(surfCloudKeyFrames[closestHistoryFrameID+j], &cloudKeyPoses6D->points[closestHistoryFrameID+j]);
nearFrameAvailable = true;
}
if (nearFrameAvailable == false)
return false;
*latestID = latestFrameIDLoopCloure;
*closestID = closestHistoryFrameID;
return true;
}
void performLoopClosure()
{
if (cloudKeyPoses3D->points.empty() == true)
return;
int latestFrameIDLoopCloure;
int closestHistoryFrameID;
if (detectLoopClosure(&latestFrameIDLoopCloure, &closestHistoryFrameID) == false)
return;
// ICP Settings
pcl::IterativeClosestPoint<PointType, PointType> icp;
icp.setMaxCorrespondenceDistance(100);
icp.setMaximumIterations(100);
icp.setTransformationEpsilon(1e-6);
icp.setEuclideanFitnessEpsilon(1e-6);
icp.setRANSACIterations(0);
// Downsample map cloud
pcl::PointCloud<PointType>::Ptr cloud_temp(new pcl::PointCloud<PointType>());
downSizeFilterICP.setInputCloud(nearHistoryKeyFrameCloud);
downSizeFilterICP.filter(*cloud_temp);
*nearHistoryKeyFrameCloud = *cloud_temp;
// publish history near key frames
publishCloud(&pubHistoryKeyFrames, nearHistoryKeyFrameCloud, timeLaserInfoStamp, "odom");
// Align clouds
icp.setInputSource(latestKeyFrameCloud);
icp.setInputTarget(nearHistoryKeyFrameCloud);
pcl::PointCloud<PointType>::Ptr unused_result(new pcl::PointCloud<PointType>());
icp.align(*unused_result);
// std::cout << "ICP converg flag:" << icp.hasConverged() << ". Fitness score: " << icp.getFitnessScore() << std::endl;
if (icp.hasConverged() == false || icp.getFitnessScore() > historyKeyframeFitnessScore)
return;
// publish corrected cloud
if (pubIcpKeyFrames.getNumSubscribers() != 0){
pcl::PointCloud<PointType>::Ptr closed_cloud(new pcl::PointCloud<PointType>());
pcl::transformPointCloud(*latestKeyFrameCloud, *closed_cloud, icp.getFinalTransformation());
publishCloud(&pubIcpKeyFrames, closed_cloud, timeLaserInfoStamp, "odom");
}
// Get pose transformation
float x, y, z, roll, pitch, yaw;
Eigen::Affine3f correctionLidarFrame;
correctionLidarFrame = icp.getFinalTransformation();
// transform from world origin to wrong pose
Eigen::Affine3f tWrong = pclPointToAffine3f(cloudKeyPoses6D->points[latestFrameIDLoopCloure]);
// transform from world origin to corrected pose
Eigen::Affine3f tCorrect = correctionLidarFrame * tWrong;// pre-multiplying -> successive rotation about a fixed frame
pcl::getTranslationAndEulerAngles (tCorrect, x, y, z, roll, pitch, yaw);
gtsam::Pose3 poseFrom = Pose3(Rot3::RzRyRx(roll, pitch, yaw), Point3(x, y, z));
gtsam::Pose3 poseTo = pclPointTogtsamPose3(cloudKeyPoses6D->points[closestHistoryFrameID]);
gtsam::Vector Vector6(6);
float noiseScore = icp.getFitnessScore();
Vector6 << noiseScore, noiseScore, noiseScore, noiseScore, noiseScore, noiseScore;
noiseModel::Diagonal::shared_ptr constraintNoise = noiseModel::Diagonal::Variances(Vector6);
// Add pose constraint
std::lock_guard<std::mutex> lock(mtx);
gtSAMgraph.add(BetweenFactor<Pose3>(latestFrameIDLoopCloure, closestHistoryFrameID, poseFrom.between(poseTo), constraintNoise));
isam->update(gtSAMgraph);
isam->update();
isam->update();
isam->update();
isam->update();
isam->update();
gtSAMgraph.resize(0);
isamCurrentEstimate = isam->calculateEstimate();
Pose3 latestEstimate = isamCurrentEstimate.at<Pose3>(isamCurrentEstimate.size()-1);
transformTobeMapped[0] = latestEstimate.rotation().roll();
transformTobeMapped[1] = latestEstimate.rotation().pitch();
transformTobeMapped[2] = latestEstimate.rotation().yaw();
transformTobeMapped[3] = latestEstimate.translation().x();
transformTobeMapped[4] = latestEstimate.translation().y();
transformTobeMapped[5] = latestEstimate.translation().z();
correctPoses();
aLoopIsClosed = true;
}
void updateInitialGuess()
{
static Eigen::Affine3f lastImuTransformation;
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// initialization
if (cloudKeyPoses3D->points.empty())
{
transformTobeMapped[0] = cloudInfo.imuRollInit;
transformTobeMapped[1] = cloudInfo.imuPitchInit;
transformTobeMapped[2] = cloudInfo.imuYawInit;
if (!useImuHeadingInitialization)
transformTobeMapped[2] = 0;
lastImuTransformation = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit); // save imu before return;
return;
}
// use imu pre-integration estimation for pose guess
if (cloudInfo.odomAvailable == true && cloudInfo.imuPreintegrationResetId == imuPreintegrationResetId)
{
transformTobeMapped[0] = cloudInfo.initialGuessRoll;
transformTobeMapped[1] = cloudInfo.initialGuessPitch;
transformTobeMapped[2] = cloudInfo.initialGuessYaw;
transformTobeMapped[3] = cloudInfo.initialGuessX;
transformTobeMapped[4] = cloudInfo.initialGuessY;
transformTobeMapped[5] = cloudInfo.initialGuessZ;
lastImuTransformation = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit); // save imu before return;
return;
}
// use imu incremental estimation for pose guess (only rotation)
if (cloudInfo.imuAvailable == true)
{
Eigen::Affine3f transBack = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit);
Eigen::Affine3f transIncre = lastImuTransformation.inverse() * transBack;
Eigen::Affine3f transTobe = trans2Affine3f(transformTobeMapped);
Eigen::Affine3f transFinal = transTobe * transIncre;
pcl::getTranslationAndEulerAngles(transFinal, transformTobeMapped[3], transformTobeMapped[4], transformTobeMapped[5],
transformTobeMapped[0], transformTobeMapped[1], transformTobeMapped[2]);
lastImuTransformation = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit); // save imu before return;
return;
}
}
void extractForLoopClosure()
{
pcl::PointCloud<PointType>::Ptr cloudToExtract(new pcl::PointCloud<PointType>());
int numPoses = cloudKeyPoses3D->size();
for (int i = numPoses-1; i >= 0; --i)
{
if ((int)cloudToExtract->size() <= surroundingKeyframeSize)
cloudToExtract->push_back(cloudKeyPoses3D->points[i]);
else
break;
}
extractCloud(cloudToExtract);
}
void extractNearby()
{
pcl::PointCloud<PointType>::Ptr surroundingKeyPoses(new pcl::PointCloud<PointType>());
pcl::PointCloud<PointType>::Ptr surroundingKeyPosesDS(new pcl::PointCloud<PointType>());
std::vector<int> pointSearchInd;
std::vector<float> pointSearchSqDis;
// extract all the nearby key poses and downsample them
kdtreeSurroundingKeyPoses->setInputCloud(cloudKeyPoses3D); // create kd-tree
kdtreeSurroundingKeyPoses->radiusSearch(cloudKeyPoses3D->back(), (double)surroundingKeyframeSearchRadius, pointSearchInd, pointSearchSqDis);
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{
int id = pointSearchInd[i];
surroundingKeyPoses->push_back(cloudKeyPoses3D->points[id]);
}
downSizeFilterSurroundingKeyPoses.setInputCloud(surroundingKeyPoses);
downSizeFilterSurroundingKeyPoses.filter(*surroundingKeyPosesDS);
// also extract some latest key frames in case the robot rotates in one position
int numPoses = cloudKeyPoses3D->size();
for (int i = numPoses-1; i >= 0; --i)
{
if (timeLaserCloudInfoLast - cloudKeyPoses6D->points[i].time < 10.0)
surroundingKeyPosesDS->push_back(cloudKeyPoses3D->points[i]);
else
break;
}
extractCloud(surroundingKeyPosesDS);
}
void extractCloud(pcl::PointCloud<PointType>::Ptr cloudToExtract)
{
std::vector<pcl::PointCloud<PointType>> laserCloudCornerSurroundingVec;
std::vector<pcl::PointCloud<PointType>> laserCloudSurfSurroundingVec;
laserCloudCornerSurroundingVec.resize(cloudToExtract->size());
laserCloudSurfSurroundingVec.resize(cloudToExtract->size());
// extract surrounding map
#pragma omp parallel for num_threads(numberOfCores)
{
if (pointDistance(cloudToExtract->points[i], cloudKeyPoses3D->back()) > surroundingKeyframeSearchRadius)
continue;
int thisKeyInd = (int)cloudToExtract->points[i].intensity;
laserCloudCornerSurroundingVec[i] = *transformPointCloud(cornerCloudKeyFrames[thisKeyInd], &cloudKeyPoses6D->points[thisKeyInd]);
laserCloudSurfSurroundingVec[i] = *transformPointCloud(surfCloudKeyFrames[thisKeyInd], &cloudKeyPoses6D->points[thisKeyInd]);
}
// fuse the map
laserCloudCornerFromMap->clear();
laserCloudSurfFromMap->clear();
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{
*laserCloudCornerFromMap += laserCloudCornerSurroundingVec[i];
*laserCloudSurfFromMap += laserCloudSurfSurroundingVec[i];
}
// Downsample the surrounding corner key frames (or map)
downSizeFilterCorner.setInputCloud(laserCloudCornerFromMap);
downSizeFilterCorner.filter(*laserCloudCornerFromMapDS);
laserCloudCornerFromMapDSNum = laserCloudCornerFromMapDS->size();
// Downsample the surrounding surf key frames (or map)
downSizeFilterSurf.setInputCloud(laserCloudSurfFromMap);
downSizeFilterSurf.filter(*laserCloudSurfFromMapDS);
laserCloudSurfFromMapDSNum = laserCloudSurfFromMapDS->size();
}
void extractSurroundingKeyFrames()
{
if (cloudKeyPoses3D->points.empty() == true)
return;
if (loopClosureEnableFlag == true)
{
extractForLoopClosure();
} else {
extractNearby();
}
}
void downsampleCurrentScan()
{
// Downsample cloud from current scan
laserCloudCornerLastDS->clear();
downSizeFilterCorner.setInputCloud(laserCloudCornerLast);
downSizeFilterCorner.filter(*laserCloudCornerLastDS);
laserCloudCornerLastDSNum = laserCloudCornerLastDS->size();
laserCloudSurfLastDS->clear();
downSizeFilterSurf.setInputCloud(laserCloudSurfLast);
downSizeFilterSurf.filter(*laserCloudSurfLastDS);
laserCloudSurfLastDSNum = laserCloudSurfLastDS->size();
}
void updatePointAssociateToMap()
{
transPointAssociateToMap = trans2Affine3f(transformTobeMapped);
}
void cornerOptimization()
{
updatePointAssociateToMap();
#pragma omp parallel for num_threads(numberOfCores)
for (int i = 0; i < laserCloudCornerLastDSNum; i++)
{
PointType pointOri, pointSel, coeff;
std::vector<int> pointSearchInd;
std::vector<float> pointSearchSqDis;
pointOri = laserCloudCornerLastDS->points[i];
pointAssociateToMap(&pointOri, &pointSel);
kdtreeCornerFromMap->nearestKSearch(pointSel, 5, pointSearchInd, pointSearchSqDis);
cv::Mat matA1(3, 3, CV_32F, cv::Scalar::all(0));
cv::Mat matD1(1, 3, CV_32F, cv::Scalar::all(0));
cv::Mat matV1(3, 3, CV_32F, cv::Scalar::all(0));
if (pointSearchSqDis[4] < 1.0) {
float cx = 0, cy = 0, cz = 0;
for (int j = 0; j < 5; j++) {
cx += laserCloudCornerFromMapDS->points[pointSearchInd[j]].x;
cy += laserCloudCornerFromMapDS->points[pointSearchInd[j]].y;
cz += laserCloudCornerFromMapDS->points[pointSearchInd[j]].z;
}
cx /= 5; cy /= 5; cz /= 5;
float a11 = 0, a12 = 0, a13 = 0, a22 = 0, a23 = 0, a33 = 0;
for (int j = 0; j < 5; j++) {
float ax = laserCloudCornerFromMapDS->points[pointSearchInd[j]].x - cx;
float ay = laserCloudCornerFromMapDS->points[pointSearchInd[j]].y - cy;
float az = laserCloudCornerFromMapDS->points[pointSearchInd[j]].z - cz;
a11 += ax * ax; a12 += ax * ay; a13 += ax * az;
a22 += ay * ay; a23 += ay * az;
a33 += az * az;
}
a11 /= 5; a12 /= 5; a13 /= 5; a22 /= 5; a23 /= 5; a33 /= 5;
matA1.at<float>(0, 0) = a11; matA1.at<float>(0, 1) = a12; matA1.at<float>(0, 2) = a13;
matA1.at<float>(1, 0) = a12; matA1.at<float>(1, 1) = a22; matA1.at<float>(1, 2) = a23;
matA1.at<float>(2, 0) = a13; matA1.at<float>(2, 1) = a23; matA1.at<float>(2, 2) = a33;
cv::eigen(matA1, matD1, matV1);
if (matD1.at<float>(0, 0) > 3 * matD1.at<float>(0, 1)) {
float x0 = pointSel.x;
float y0 = pointSel.y;
float z0 = pointSel.z;
float x1 = cx + 0.1 * matV1.at<float>(0, 0);
float y1 = cy + 0.1 * matV1.at<float>(0, 1);
float z1 = cz + 0.1 * matV1.at<float>(0, 2);
float x2 = cx - 0.1 * matV1.at<float>(0, 0);
float y2 = cy - 0.1 * matV1.at<float>(0, 1);
float z2 = cz - 0.1 * matV1.at<float>(0, 2);
float a012 = sqrt(((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1)) * ((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1))
+ ((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1)) * ((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1))
+ ((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1)) * ((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1)));
float l12 = sqrt((x1 - x2)*(x1 - x2) + (y1 - y2)*(y1 - y2) + (z1 - z2)*(z1 - z2));
float la = ((y1 - y2)*((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1))
+ (z1 - z2)*((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1))) / a012 / l12;
float lb = -((x1 - x2)*((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1))
- (z1 - z2)*((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1))) / a012 / l12;
float lc = -((x1 - x2)*((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1))
+ (y1 - y2)*((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1))) / a012 / l12;
float ld2 = a012 / l12;
float s = 1 - 0.9 * fabs(ld2);
coeff.x = s * la;
coeff.y = s * lb;
coeff.z = s * lc;
coeff.intensity = s * ld2;
if (s > 0.1) {
laserCloudOriCornerVec[i] = pointOri;
coeffSelCornerVec[i] = coeff;
laserCloudOriCornerFlag[i] = true;
}
}
}
}
}
void surfOptimization()
{
updatePointAssociateToMap();
#pragma omp parallel for num_threads(numberOfCores)
for (int i = 0; i < laserCloudSurfLastDSNum; i++)
{
PointType pointOri, pointSel, coeff;
std::vector<int> pointSearchInd;
std::vector<float> pointSearchSqDis;
pointOri = laserCloudSurfLastDS->points[i];
pointAssociateToMap(&pointOri, &pointSel);
kdtreeSurfFromMap->nearestKSearch(pointSel, 5, pointSearchInd, pointSearchSqDis);
Eigen::Matrix<float, 5, 3> matA0;
Eigen::Matrix<float, 5, 1> matB0;
Eigen::Vector3f matX0;
matA0.setZero();
matB0.fill(-1);
matX0.setZero();
if (pointSearchSqDis[4] < 1.0) {
for (int j = 0; j < 5; j++) {
matA0(j, 0) = laserCloudSurfFromMapDS->points[pointSearchInd[j]].x;
matA0(j, 1) = laserCloudSurfFromMapDS->points[pointSearchInd[j]].y;
matA0(j, 2) = laserCloudSurfFromMapDS->points[pointSearchInd[j]].z;
}
matX0 = matA0.colPivHouseholderQr().solve(matB0);
float pa = matX0(0, 0);
float pb = matX0(1, 0);
float pc = matX0(2, 0);
float pd = 1;
float ps = sqrt(pa * pa + pb * pb + pc * pc);
pa /= ps; pb /= ps; pc /= ps; pd /= ps;
bool planeValid = true;
for (int j = 0; j < 5; j++) {
if (fabs(pa * laserCloudSurfFromMapDS->points[pointSearchInd[j]].x +
pb * laserCloudSurfFromMapDS->points[pointSearchInd[j]].y +
pc * laserCloudSurfFromMapDS->points[pointSearchInd[j]].z + pd) > 0.2) {
planeValid = false;
break;
}
}
if (planeValid) {
float pd2 = pa * pointSel.x + pb * pointSel.y + pc * pointSel.z + pd;
float s = 1 - 0.9 * fabs(pd2) / sqrt(sqrt(pointSel.x * pointSel.x
+ pointSel.y * pointSel.y + pointSel.z * pointSel.z));
coeff.x = s * pa;
coeff.y = s * pb;
coeff.z = s * pc;
coeff.intensity = s * pd2;
if (s > 0.1) {
laserCloudOriSurfVec[i] = pointOri;
coeffSelSurfVec[i] = coeff;
laserCloudOriSurfFlag[i] = true;
}
}
}
}
}
void combineOptimizationCoeffs()
{
// combine corner coeffs
for (int i = 0; i < laserCloudCornerLastDSNum; ++i){
if (laserCloudOriCornerFlag[i] == true){
laserCloudOri->push_back(laserCloudOriCornerVec[i]);
coeffSel->push_back(coeffSelCornerVec[i]);
}
}
// combine surf coeffs
for (int i = 0; i < laserCloudSurfLastDSNum; ++i){
if (laserCloudOriSurfFlag[i] == true){
laserCloudOri->push_back(laserCloudOriSurfVec[i]);
coeffSel->push_back(coeffSelSurfVec[i]);
}
}
// reset flag for next iteration
std::fill(laserCloudOriCornerFlag.begin(), laserCloudOriCornerFlag.end(), false);
std::fill(laserCloudOriSurfFlag.begin(), laserCloudOriSurfFlag.end(), false);
}
bool LMOptimization(int iterCount)
{
// This optimization is from the original loam_velodyne by Ji Zhang, need to cope with coordinate transformation
// lidar <- camera --- camera <- lidar
// x = z --- x = y
// y = x --- y = z
// z = y --- z = x
// roll = yaw --- roll = pitch
// pitch = roll --- pitch = yaw
// yaw = pitch --- yaw = roll
// lidar -> camera
float srx = sin(transformTobeMapped[1]);
float crx = cos(transformTobeMapped[1]);
float sry = sin(transformTobeMapped[2]);
float cry = cos(transformTobeMapped[2]);
float srz = sin(transformTobeMapped[0]);
float crz = cos(transformTobeMapped[0]);
int laserCloudSelNum = laserCloudOri->size();
if (laserCloudSelNum < 50) {
return false;
}
cv::Mat matA(laserCloudSelNum, 6, CV_32F, cv::Scalar::all(0));
cv::Mat matAt(6, laserCloudSelNum, CV_32F, cv::Scalar::all(0));
cv::Mat matAtA(6, 6, CV_32F, cv::Scalar::all(0));
cv::Mat matB(laserCloudSelNum, 1, CV_32F, cv::Scalar::all(0));
cv::Mat matAtB(6, 1, CV_32F, cv::Scalar::all(0));
cv::Mat matX(6, 1, CV_32F, cv::Scalar::all(0));
cv::Mat matP(6, 6, CV_32F, cv::Scalar::all(0));
PointType pointOri, coeff;
for (int i = 0; i < laserCloudSelNum; i++) {
// lidar -> camera
pointOri.x = laserCloudOri->points[i].y;
pointOri.y = laserCloudOri->points[i].z;
pointOri.z = laserCloudOri->points[i].x;
// lidar -> camera
coeff.x = coeffSel->points[i].y;
coeff.y = coeffSel->points[i].z;
coeff.z = coeffSel->points[i].x;
coeff.intensity = coeffSel->points[i].intensity;