98 lines
3.3 KiB
C++
98 lines
3.3 KiB
C++
/* ----------------------------------------------------------------------------
|
|
|
|
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
|
|
* Atlanta, Georgia 30332-0415
|
|
* All Rights Reserved
|
|
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
|
|
|
|
* See LICENSE for the license information
|
|
|
|
* -------------------------------------------------------------------------- */
|
|
|
|
/**
|
|
* @file Pose2SLAMExample_g2o.cpp
|
|
* @brief A 2D Pose SLAM example that reads input from g2o, converts it to a factor graph and does the
|
|
* optimization. Output is written on a file, in g2o format
|
|
* Syntax for the script is ./Pose2SLAMExample_g2o input.g2o output.g2o
|
|
* @date May 15, 2014
|
|
* @author Luca Carlone
|
|
*/
|
|
|
|
#include <gtsam/slam/dataset.h>
|
|
#include <gtsam/geometry/Pose2.h>
|
|
#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
|
|
#include <fstream>
|
|
|
|
using namespace std;
|
|
using namespace gtsam;
|
|
|
|
// HOWTO: ./Pose2SLAMExample_g2o inputFile outputFile (maxIterations) (tukey/huber)
|
|
int main(const int argc, const char *argv[]) {
|
|
|
|
string kernelType = "none";
|
|
int maxIterations = 100; // default
|
|
string g2oFile = findExampleDataFile("noisyToyGraph.txt"); // default
|
|
|
|
// Parse user's inputs
|
|
if (argc > 1){
|
|
g2oFile = argv[1]; // input dataset filename
|
|
// outputFile = g2oFile = argv[2]; // done later
|
|
}
|
|
if (argc > 3){
|
|
maxIterations = atoi(argv[3]); // user can specify either tukey or huber
|
|
}
|
|
if (argc > 4){
|
|
kernelType = argv[4]; // user can specify either tukey or huber
|
|
}
|
|
|
|
// reading file and creating factor graph
|
|
NonlinearFactorGraph::shared_ptr graph;
|
|
Values::shared_ptr initial;
|
|
bool is3D = false;
|
|
if(kernelType.compare("none") == 0){
|
|
boost::tie(graph, initial) = readG2o(g2oFile,is3D);
|
|
}
|
|
if(kernelType.compare("huber") == 0){
|
|
std::cout << "Using robust kernel: huber " << std::endl;
|
|
boost::tie(graph, initial) = readG2o(g2oFile,is3D, KernelFunctionTypeHUBER);
|
|
}
|
|
if(kernelType.compare("tukey") == 0){
|
|
std::cout << "Using robust kernel: tukey " << std::endl;
|
|
boost::tie(graph, initial) = readG2o(g2oFile,is3D, KernelFunctionTypeTUKEY);
|
|
}
|
|
|
|
// Add prior on the pose having index (key) = 0
|
|
noiseModel::Diagonal::shared_ptr priorModel = //
|
|
noiseModel::Diagonal::Variances(Vector3(1e-6, 1e-6, 1e-8));
|
|
graph.addPrior(0, Pose2(), priorModel);
|
|
std::cout << "Adding prior on pose 0 " << std::endl;
|
|
|
|
GaussNewtonParams params;
|
|
params.setVerbosity("TERMINATION");
|
|
if (argc > 3) {
|
|
params.maxIterations = maxIterations;
|
|
std::cout << "User required to perform maximum " << params.maxIterations << " iterations "<< std::endl;
|
|
}
|
|
|
|
std::cout << "Optimizing the factor graph" << std::endl;
|
|
GaussNewtonOptimizer optimizer(*graph, *initial, params);
|
|
Values result = optimizer.optimize();
|
|
std::cout << "Optimization complete" << std::endl;
|
|
|
|
std::cout << "initial error=" <<graph->error(*initial)<< std::endl;
|
|
std::cout << "final error=" <<graph->error(result)<< std::endl;
|
|
|
|
if (argc < 3) {
|
|
result.print("result");
|
|
} else {
|
|
const string outputFile = argv[2];
|
|
std::cout << "Writing results to file: " << outputFile << std::endl;
|
|
NonlinearFactorGraph::shared_ptr graphNoKernel;
|
|
Values::shared_ptr initial2;
|
|
boost::tie(graphNoKernel, initial2) = readG2o(g2oFile);
|
|
writeG2o(*graphNoKernel, result, outputFile);
|
|
std::cout << "done! " << std::endl;
|
|
}
|
|
return 0;
|
|
}
|