int main(int argc, char **argv) {
/************************************************************************
* Input handling *
************************************************************************/
float rows, cols, gain, square_size;
float resolution, max_range, usable_range, angle, threshold;
string g2oFilename, mapFilename;
g2o::CommandArgs arg;
arg.param("resolution", resolution, 0.05f, "resolution of the map (how much is in meters a pixel)");
arg.param("threshold", threshold, -1.0f, "threshold to apply to the frequency map (values under the threshold are discarded)");
arg.param("rows", rows, 0, "impose the resulting map to have this number of rows");
arg.param("cols", cols, 0, "impose the resulting map to have this number of columns");
arg.param("max_range", max_range, -1.0f, "max laser range to consider for map building");
arg.param("usable_range", usable_range, -1.0f, "usable laser range for map building");
arg.param("gain", gain, 1, "gain to impose to the pixels of the map");
arg.param("square_size", square_size, 1, "square size of the region where increment the hits");
arg.param("angle", angle, 0, "rotate the map of x degrees");
arg.paramLeftOver("input_graph.g2o", g2oFilename, "", "input g2o graph to use to build the map", false);
arg.paramLeftOver("output_map", mapFilename, "", "output filename where to save the map (without extension)", false);
arg.parseArgs(argc, argv);
angle = angle*M_PI/180.0;
/************************************************************************
* Loading Graph *
************************************************************************/
// Load graph
typedef BlockSolver< BlockSolverTraits<-1, -1> > SlamBlockSolver;
typedef LinearSolverCSparse<SlamBlockSolver::PoseMatrixType> SlamLinearSolver;
SlamLinearSolver *linearSolver = new SlamLinearSolver();
linearSolver->setBlockOrdering(false);
SlamBlockSolver *blockSolver = new SlamBlockSolver(linearSolver);
OptimizationAlgorithmGaussNewton *solverGauss = new OptimizationAlgorithmGaussNewton(blockSolver);
SparseOptimizer *graph = new SparseOptimizer();
graph->setAlgorithm(solverGauss);
graph->load(g2oFilename.c_str());
// Sort verteces
vector<int> vertexIds(graph->vertices().size());
int k = 0;
for(OptimizableGraph::VertexIDMap::iterator it = graph->vertices().begin(); it != graph->vertices().end(); ++it) {
vertexIds[k++] = (it->first);
}
sort(vertexIds.begin(), vertexIds.end());
/************************************************************************
* Compute map size *
************************************************************************/
// Check the entire graph to find map bounding box
Eigen::Matrix2d boundingBox = Eigen::Matrix2d::Zero();
std::vector<RobotLaser*> robotLasers;
std::vector<SE2> robotPoses;
double xmin=std::numeric_limits<double>::max();
double xmax=std::numeric_limits<double>::min();
double ymin=std::numeric_limits<double>::max();
double ymax=std::numeric_limits<double>::min();
SE2 baseTransform(0,0,angle);
for(size_t i = 0; i < vertexIds.size(); ++i) {
OptimizableGraph::Vertex *_v = graph->vertex(vertexIds[i]);
VertexSE2 *v = dynamic_cast<VertexSE2*>(_v);
if(!v) { continue; }
v->setEstimate(baseTransform*v->estimate());
OptimizableGraph::Data *d = v->userData();
while(d) {
RobotLaser *robotLaser = dynamic_cast<RobotLaser*>(d);
if(!robotLaser) {
d = d->next();
continue;
}
robotLasers.push_back(robotLaser);
robotPoses.push_back(v->estimate());
double x = v->estimate().translation().x();
double y = v->estimate().translation().y();
xmax = xmax > x+usable_range ? xmax : x+usable_range;
ymax = ymax > y+usable_range ? ymax : y+usable_range;
xmin = xmin < x-usable_range ? xmin : x-usable_range;
ymin = ymin < y-usable_range ? ymin : y-usable_range;
d = d->next();
}
}
boundingBox(0,0)=xmin;
boundingBox(0,1)=xmax;
boundingBox(1,0)=ymin;
boundingBox(1,1)=ymax;
std::cout << "Found " << robotLasers.size() << " laser scans"<< std::endl;
std::cout << "Bounding box: " << std::endl << boundingBox << std::endl;
if(robotLasers.size() == 0) {
std::cout << "No laser scans found ... quitting!" << std::endl;
return 0;
}
/************************************************************************
* Compute the map *
************************************************************************/
// Create the map
Eigen::Vector2i size;
if(rows != 0 && cols != 0) { size = Eigen::Vector2i(rows, cols); }
else {
size = Eigen::Vector2i((boundingBox(0, 1) - boundingBox(0, 0))/ resolution,
(boundingBox(1, 1) - boundingBox(1, 0))/ resolution);
}
std::cout << "Map size: " << size.transpose() << std::endl;
if(size.x() == 0 || size.y() == 0) {
std::cout << "Zero map size ... quitting!" << std::endl;
return 0;
}
//Eigen::Vector2f offset(-size.x() * resolution / 2.0f, -size.y() * resolution / 2.0f);
Eigen::Vector2f offset(boundingBox(0, 0),boundingBox(1, 0));
FrequencyMapCell unknownCell;
FrequencyMap map = FrequencyMap(resolution, offset, size, unknownCell);
for(size_t i = 0; i < vertexIds.size(); ++i) {
OptimizableGraph::Vertex *_v = graph->vertex(vertexIds[i]);
VertexSE2 *v = dynamic_cast<VertexSE2*>(_v);
if(!v) { continue; }
OptimizableGraph::Data *d = v->userData();
SE2 robotPose = v->estimate();
while(d) {
RobotLaser *robotLaser = dynamic_cast<RobotLaser*>(d);
if(!robotLaser) {
d = d->next();
continue;
}
map.integrateScan(robotLaser, robotPose, max_range, usable_range, gain, square_size);
d = d->next();
}
}
/************************************************************************
* Save map image *
************************************************************************/
cv::Mat mapImage(map.rows(), map.cols(), CV_8UC1);
mapImage.setTo(cv::Scalar(0));
for(int c = 0; c < map.cols(); c++) {
for(int r = 0; r < map.rows(); r++) {
if(map(r, c).misses() == 0 && map(r, c).hits() == 0) {
mapImage.at<unsigned char>(r, c) = 127;
} else {
float fraction = (float)map(r, c).hits()/(float)(map(r, c).hits()+map(r, c).misses());
if (threshold > 0 && fraction > threshold)
mapImage.at<unsigned char>(r, c) = 0;
else if (threshold > 0 && fraction <= threshold)
mapImage.at<unsigned char>(r, c) = 255;
else {
float val = 255*(1-fraction);
mapImage.at<unsigned char>(r, c) = (unsigned char)val;
}
}
// else if(map(r, c).hits() > threshold) {
// mapImage.at<unsigned char>(r, c) = 255;
// }
// else {
// mapImage.at<unsigned char>(r, c) = 0;
// }
}
}
cv::imwrite(mapFilename + ".png", mapImage);
/************************************************************************
* Write yaml file *
************************************************************************/
std::ofstream ofs(string(mapFilename + ".yaml").c_str());
Eigen::Vector3f origin(0.0f, 0.0f, 0.0f);
ofs << "image: " << mapFilename << ".png" << std::endl
<< "resolution: " << resolution << std::endl
<< "origin: [" << origin.x() << ", " << origin.y() << ", " << origin.z() << "]" << std::endl
<< "negate: 0" << std::endl
<< "occupied_thresh: " << 0.65f << std::endl
<< "free_thresh: " << 0.2f << std::endl;
return 0;
}
