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Cplusplus RGBD Mapping
- Introduction
- Details
- Project configuration (example with CMake)
- Code
- Build and run
- Example without threads and events
This tutorial will show an example of usage of the RTAB-Map library in C++ for RGB-D mapping.
Here our project directory:
MyProject
|
-->CMakeLists.txt
-->main.cpp
-->MapBuilder.h
Files:
In your CMakeLists.txt
:
cmake_minimum_required(VERSION 2.8)
PROJECT( MyProject )
FIND_PACKAGE(RTABMap REQUIRED)
SET(moc_srcs MapBuilder.h)
ADD_EXECUTABLE(rgbd_mapping main.cpp ${moc_srcs})
TARGET_LINK_LIBRARIES(rgbd_mapping rtabmap::gui)
SET_TARGET_PROPERTIES(
rgbd_mapping
PROPERTIES
AUTOUIC ON
AUTOMOC ON
AUTORCC ON
)
The main.cpp
#include <rtabmap/core/Odometry.h>
#include "rtabmap/core/Rtabmap.h"
#include "rtabmap/core/RtabmapThread.h"
#include "rtabmap/core/CameraRGBD.h"
#include "rtabmap/core/CameraStereo.h"
#include "rtabmap/core/CameraThread.h"
#include "rtabmap/core/OdometryThread.h"
#include "rtabmap/core/Graph.h"
#include "rtabmap/utilite/UEventsManager.h"
#include <QApplication>
#include <stdio.h>
#include <pcl/io/pcd_io.h>
#include <pcl/io/ply_io.h>
#include <pcl/filters/filter.h>
#ifdef RTABMAP_PYTHON
#include "rtabmap/core/PythonInterface.h"
#endif
#include "MapBuilder.h"
void showUsage()
{
printf("\nUsage:\n"
"rtabmap-rgbd_mapping driver\n"
" driver Driver number to use: 0=OpenNI-PCL, 1=OpenNI2, 2=Freenect, 3=OpenNI-CV, 4=OpenNI-CV-ASUS, 5=Freenect2, 6=ZED SDK, 7=RealSense, 8=RealSense2 9=Kinect for Azure SDK 10=MYNT EYE S\n\n");
exit(1);
}
using namespace rtabmap;
int main(int argc, char * argv[])
{
ULogger::setType(ULogger::kTypeConsole);
ULogger::setLevel(ULogger::kWarning);
#ifdef RTABMAP_PYTHON
PythonInterface python; // Make sure we initialize python in main thread
#endif
int driver = 0;
if(argc < 2)
{
showUsage();
}
else
{
driver = atoi(argv[argc-1]);
if(driver < 0 || driver > 10)
{
UERROR("driver should be between 0 and 10.");
showUsage();
}
}
// Here is the pipeline that we will use:
// CameraOpenni -> "CameraEvent" -> OdometryThread -> "OdometryEvent" -> RtabmapThread -> "RtabmapEvent"
// Create the OpenNI camera, it will send a CameraEvent at the rate specified.
// Set transform to camera so z is up, y is left and x going forward
Camera * camera = 0;
if(driver == 1)
{
if(!CameraOpenNI2::available())
{
UERROR("Not built with OpenNI2 support...");
exit(-1);
}
camera = new CameraOpenNI2();
}
else if(driver == 2)
{
if(!CameraFreenect::available())
{
UERROR("Not built with Freenect support...");
exit(-1);
}
camera = new CameraFreenect();
}
else if(driver == 3)
{
if(!CameraOpenNICV::available())
{
UERROR("Not built with OpenNI from OpenCV support...");
exit(-1);
}
camera = new CameraOpenNICV();
}
else if(driver == 4)
{
if(!CameraOpenNICV::available())
{
UERROR("Not built with OpenNI from OpenCV support...");
exit(-1);
}
camera = new CameraOpenNICV(true);
}
else if (driver == 5)
{
if (!CameraFreenect2::available())
{
UERROR("Not built with Freenect2 support...");
exit(-1);
}
camera = new CameraFreenect2(0, CameraFreenect2::kTypeColor2DepthSD);
}
else if (driver == 6)
{
if (!CameraStereoZed::available())
{
UERROR("Not built with ZED SDK support...");
exit(-1);
}
camera = new CameraStereoZed(0, 2, 1, 1, 100, false);
}
else if (driver == 7)
{
if (!CameraRealSense::available())
{
UERROR("Not built with RealSense support...");
exit(-1);
}
camera = new CameraRealSense();
}
else if (driver == 8)
{
if (!CameraRealSense2::available())
{
UERROR("Not built with RealSense2 support...");
exit(-1);
}
camera = new CameraRealSense2();
}
else if (driver == 9)
{
if (!rtabmap::CameraK4A::available())
{
UERROR("Not built with Kinect for Azure SDK support...");
exit(-1);
}
camera = new rtabmap::CameraK4A(1);
}
else if (driver == 10)
{
if (!rtabmap::CameraMyntEye::available())
{
UERROR("Not built with Mynt Eye S support...");
exit(-1);
}
camera = new rtabmap::CameraMyntEye();
}
else
{
camera = new rtabmap::CameraOpenni();
}
if(!camera->init())
{
UERROR("Camera init failed!");
}
CameraThread cameraThread(camera);
// GUI stuff, there the handler will receive RtabmapEvent and construct the map
// We give it the camera so the GUI can pause/resume the camera
QApplication app(argc, argv);
MapBuilder mapBuilder(&cameraThread);
// Create an odometry thread to process camera events, it will send OdometryEvent.
OdometryThread odomThread(Odometry::create());
ParametersMap params;
//param.insert(ParametersPair(Parameters::kRGBDCreateOccupancyGrid(), "true")); // uncomment to create local occupancy grids
// Create RTAB-Map to process OdometryEvent
Rtabmap * rtabmap = new Rtabmap();
rtabmap->init(params);
RtabmapThread rtabmapThread(rtabmap); // ownership is transfered
// Setup handlers
odomThread.registerToEventsManager();
rtabmapThread.registerToEventsManager();
mapBuilder.registerToEventsManager();
// The RTAB-Map is subscribed by default to CameraEvent, but we want
// RTAB-Map to process OdometryEvent instead, ignoring the CameraEvent.
// We can do that by creating a "pipe" between the camera and odometry, then
// only the odometry will receive CameraEvent from that camera. RTAB-Map is
// also subscribed to OdometryEvent by default, so no need to create a pipe between
// odometry and RTAB-Map.
UEventsManager::createPipe(&cameraThread, &odomThread, "CameraEvent");
// Let's start the threads
rtabmapThread.start();
odomThread.start();
cameraThread.start();
mapBuilder.show();
app.exec(); // main loop
// remove handlers
mapBuilder.unregisterFromEventsManager();
rtabmapThread.unregisterFromEventsManager();
odomThread.unregisterFromEventsManager();
// Kill all threads
cameraThread.kill();
odomThread.join(true);
rtabmapThread.join(true);
// Save 3D map
printf("Saving rtabmap_cloud.pcd...\n");
std::map<int, Signature> nodes;
std::map<int, Transform> optimizedPoses;
std::multimap<int, Link> links;
rtabmap->getGraph(optimizedPoses, links, true, true, &nodes, true, true, true, true);
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
for(std::map<int, Transform>::iterator iter=optimizedPoses.begin(); iter!=optimizedPoses.end(); ++iter)
{
Signature node = nodes.find(iter->first)->second;
// uncompress data
node.sensorData().uncompressData();
pcl::PointCloud<pcl::PointXYZRGB>::Ptr tmp = util3d::cloudRGBFromSensorData(
node.sensorData(),
4, // image decimation before creating the clouds
4.0f, // maximum depth of the cloud
0.0f);
pcl::PointCloud<pcl::PointXYZRGB>::Ptr tmpNoNaN(new pcl::PointCloud<pcl::PointXYZRGB>);
std::vector<int> index;
pcl::removeNaNFromPointCloud(*tmp, *tmpNoNaN, index);
if(!tmpNoNaN->empty())
{
*cloud += *util3d::transformPointCloud(tmpNoNaN, iter->second); // transform the point cloud to its pose
}
}
if(cloud->size())
{
printf("Voxel grid filtering of the assembled cloud (voxel=%f, %d points)\n", 0.01f, (int)cloud->size());
cloud = util3d::voxelize(cloud, 0.01f);
printf("Saving rtabmap_cloud.pcd... done! (%d points)\n", (int)cloud->size());
pcl::io::savePCDFile("rtabmap_cloud.pcd", *cloud);
//pcl::io::savePLYFile("rtabmap_cloud.ply", *cloud); // to save in PLY format
}
else
{
printf("Saving rtabmap_cloud.pcd... failed! The cloud is empty.\n");
}
// Save trajectory
printf("Saving rtabmap_trajectory.txt ...\n");
if(optimizedPoses.size() && graph::exportPoses("rtabmap_trajectory.txt", 0, optimizedPoses, links))
{
printf("Saving rtabmap_trajectory.txt... done!\n");
}
else
{
printf("Saving rtabmap_trajectory.txt... failed!\n");
}
rtabmap->close(false);
return 0;
}
The MapBuilder
class (for visualization):
#ifndef MAPBUILDER_H_
#define MAPBUILDER_H_
#include <QVBoxLayout>
#include <QtCore/QMetaType>
#include <QAction>
#ifndef Q_MOC_RUN // Mac OS X issue
#include "rtabmap/gui/CloudViewer.h"
#include "rtabmap/core/util3d.h"
#include "rtabmap/core/util3d_filtering.h"
#include "rtabmap/core/util3d_transforms.h"
#include "rtabmap/core/util3d_mapping.h"
#include "rtabmap/core/RtabmapEvent.h"
#include "rtabmap/core/global_map/OccupancyGrid.h"
#endif
#include "rtabmap/utilite/UStl.h"
#include "rtabmap/utilite/UConversion.h"
#include "rtabmap/utilite/UEventsHandler.h"
#include "rtabmap/utilite/ULogger.h"
#include "rtabmap/core/OdometryEvent.h"
#include "rtabmap/core/CameraThread.h"
using namespace rtabmap;
// This class receives RtabmapEvent and construct/update a 3D Map
class MapBuilder : public QWidget, public UEventsHandler
{
Q_OBJECT
public:
//Camera ownership is not transferred!
MapBuilder(CameraThread * camera = 0) :
camera_(camera),
odometryCorrection_(Transform::getIdentity()),
processingStatistics_(false),
lastOdometryProcessed_(true),
grid_(&localGrids_)
{
this->setWindowFlags(Qt::Dialog);
this->setWindowTitle(tr("3D Map"));
this->setMinimumWidth(800);
this->setMinimumHeight(600);
cloudViewer_ = new CloudViewer(this);
QVBoxLayout *layout = new QVBoxLayout();
layout->addWidget(cloudViewer_);
this->setLayout(layout);
qRegisterMetaType<rtabmap::OdometryEvent>("rtabmap::OdometryEvent");
qRegisterMetaType<rtabmap::Statistics>("rtabmap::Statistics");
QAction * pause = new QAction(this);
this->addAction(pause);
pause->setShortcut(Qt::Key_Space);
connect(pause, SIGNAL(triggered()), this, SLOT(pauseDetection()));
}
virtual ~MapBuilder()
{
this->unregisterFromEventsManager();
}
protected Q_SLOTS:
virtual void pauseDetection()
{
UWARN("");
if(camera_)
{
if(camera_->isCapturing())
{
camera_->join(true);
}
else
{
camera_->start();
}
}
}
virtual void processOdometry(const rtabmap::OdometryEvent & odom)
{
if(!this->isVisible())
{
return;
}
Transform pose = odom.pose();
if(pose.isNull())
{
//Odometry lost
cloudViewer_->setBackgroundColor(Qt::darkRed);
pose = lastOdomPose_;
}
else
{
cloudViewer_->setBackgroundColor(cloudViewer_->getDefaultBackgroundColor());
}
if(!pose.isNull())
{
lastOdomPose_ = pose;
// 3d cloud
if(odom.data().depthOrRightRaw().cols == odom.data().imageRaw().cols &&
odom.data().depthOrRightRaw().rows == odom.data().imageRaw().rows &&
!odom.data().depthOrRightRaw().empty() &&
(odom.data().stereoCameraModels().size() || odom.data().cameraModels().size()))
{
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud = util3d::cloudRGBFromSensorData(
odom.data(),
2, // decimation
4.0f); // max depth
if(cloud->size())
{
if(!cloudViewer_->addCloud("cloudOdom", cloud, odometryCorrection_*pose))
{
UERROR("Adding cloudOdom to viewer failed!");
}
}
else
{
cloudViewer_->setCloudVisibility("cloudOdom", false);
UWARN("Empty cloudOdom!");
}
}
if(!odom.pose().isNull())
{
// update camera position
cloudViewer_->updateCameraTargetPosition(odometryCorrection_*odom.pose());
}
}
cloudViewer_->update();
lastOdometryProcessed_ = true;
}
virtual void processStatistics(const rtabmap::Statistics & stats)
{
processingStatistics_ = true;
//============================
// Add RGB-D clouds
//============================
const std::map<int, Transform> & poses = stats.poses();
QMap<std::string, Transform> clouds = cloudViewer_->getAddedClouds();
for(std::map<int, Transform>::const_iterator iter = poses.lower_bound(1); iter!=poses.end(); ++iter)
{
if(!iter->second.isNull())
{
std::string cloudName = uFormat("cloud%d", iter->first);
// 3d point cloud
if(clouds.contains(cloudName))
{
// Update only if the pose has changed
Transform tCloud;
cloudViewer_->getPose(cloudName, tCloud);
if(tCloud.isNull() || iter->second != tCloud)
{
if(!cloudViewer_->updateCloudPose(cloudName, iter->second))
{
UERROR("Updating pose cloud %d failed!", iter->first);
}
}
cloudViewer_->setCloudVisibility(cloudName, true);
}
else if(iter->first == stats.getLastSignatureData().id())
{
Signature s = stats.getLastSignatureData();
s.sensorData().uncompressData(); // make sure data is uncompressed
// Add the new cloud
pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud = util3d::cloudRGBFromSensorData(
s.sensorData(),
4, // decimation
4.0f); // max depth
if(cloud->size())
{
if(!cloudViewer_->addCloud(cloudName, cloud, iter->second))
{
UERROR("Adding cloud %d to viewer failed!", iter->first);
}
}
else
{
UWARN("Empty cloud %d!", iter->first);
}
}
}
else
{
UWARN("Null pose for %d ?!?", iter->first);
}
}
//============================
// Add 3D graph (show all poses)
//============================
cloudViewer_->removeAllGraphs();
cloudViewer_->removeCloud("graph_nodes");
if(poses.size())
{
// Set graph
pcl::PointCloud<pcl::PointXYZ>::Ptr graph(new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr graphNodes(new pcl::PointCloud<pcl::PointXYZ>);
for(std::map<int, Transform>::const_iterator iter=poses.lower_bound(1); iter!=poses.end(); ++iter)
{
graph->push_back(pcl::PointXYZ(iter->second.x(), iter->second.y(), iter->second.z()));
}
*graphNodes = *graph;
// add graph
cloudViewer_->addOrUpdateGraph("graph", graph, Qt::gray);
cloudViewer_->addCloud("graph_nodes", graphNodes, Transform::getIdentity(), Qt::green);
cloudViewer_->setCloudPointSize("graph_nodes", 5);
}
//============================
// Update/add occupancy grid (when RGBD/CreateOccupancyGrid is true)
//============================
if(grid_.addedNodes().find(stats.getLastSignatureData().id()) == grid_.addedNodes().end())
{
if(stats.getLastSignatureData().sensorData().gridCellSize() > 0.0f)
{
cv::Mat groundCells, obstacleCells, emptyCells;
stats.getLastSignatureData().sensorData().uncompressDataConst(0, 0, 0, 0, &groundCells, &obstacleCells, &emptyCells);
localGrids_.add(stats.getLastSignatureData().id(), groundCells, obstacleCells, emptyCells, stats.getLastSignatureData().sensorData().gridCellSize(), stats.getLastSignatureData().sensorData().gridViewPoint());
}
}
if(grid_.addedNodes().size() || localGrids_.size())
{
grid_.update(stats.poses());
}
if(grid_.addedNodes().size())
{
float xMin, yMin;
cv::Mat map8S = grid_.getMap(xMin, yMin);
if(!map8S.empty())
{
//convert to gray scaled map
cv::Mat map8U = util3d::convertMap2Image8U(map8S);
cloudViewer_->addOccupancyGridMap(map8U, grid_.getCellSize(), xMin, yMin, 0.75);
}
}
odometryCorrection_ = stats.mapCorrection();
cloudViewer_->update();
processingStatistics_ = false;
}
virtual bool handleEvent(UEvent * event)
{
if(event->getClassName().compare("RtabmapEvent") == 0)
{
RtabmapEvent * rtabmapEvent = (RtabmapEvent *)event;
const Statistics & stats = rtabmapEvent->getStats();
// Statistics must be processed in the Qt thread
if(this->isVisible())
{
QMetaObject::invokeMethod(this, "processStatistics", Q_ARG(rtabmap::Statistics, stats));
}
}
else if(event->getClassName().compare("OdometryEvent") == 0)
{
OdometryEvent * odomEvent = (OdometryEvent *)event;
// Odometry must be processed in the Qt thread
if(this->isVisible() &&
lastOdometryProcessed_ &&
!processingStatistics_)
{
lastOdometryProcessed_ = false; // if we receive too many odometry events!
QMetaObject::invokeMethod(this, "processOdometry", Q_ARG(rtabmap::OdometryEvent, *odomEvent));
}
}
return false;
}
protected:
CloudViewer * cloudViewer_;
CameraThread * camera_;
Transform lastOdomPose_;
Transform odometryCorrection_;
bool processingStatistics_;
bool lastOdometryProcessed_;
LocalGridCache localGrids_;
OccupancyGrid grid_;
};
#endif /* MAPBUILDER_H_ */
In your directory:
$ cmake .
$ make
$ ./rgbd_mapping
You should see a window with the 3D map constructing. If the background turns red, that means that odometry cannot be computed: visit the Lost Odometry section on this page for more information.
The previous approach based on threads and events is preferred. However, if you want to see step-by-step how images are processed in the different modules, it would be easier to remove threading stuff. So I provide an example in which I don't use any threads and events. The code is here and the dataset used can be downloaded here in the stereo tutorial. It is also built when RTAB-Map is built from source, the name is rtabmap-noEventsExample
.
Example (with unzipped stereo_20Hz.zip images):
./rtabmap-noEventsExample 20 2 10 stereo_20Hz stereo_20Hz stereo_20Hz/left stereo_20Hz/right