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Updated Pose2SLAMExample_graph to remove SLAM namespaces

release/4.3a0
Stephen Williams 2012-07-30 14:59:18 +00:00
parent 32f9ea526d
commit 08c72e2a8d
1 changed files with 11 additions and 8 deletions
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19
examples/Pose2SLAMExample_graph.cpp
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@ -17,32 +17,35 @@
*/ */
#include <gtsam/slam/dataset.h> #include <gtsam/slam/dataset.h>
#include <gtsam/slam/pose2SLAM.h> #include <gtsam/slam/PriorFactor.h>
#include <gtsam/nonlinear/Marginals.h> #include <gtsam/nonlinear/Marginals.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/Values.h>
#include <gtsam/geometry/Pose2.h>
#include <boost/tuple/tuple.hpp> #include <boost/tuple/tuple.hpp>
#include <cmath> #include <cmath>
using namespace std; using namespace std;
using namespace gtsam; using namespace gtsam;
using namespace gtsam::noiseModel;
int main(int argc, char** argv) { int main(int argc, char** argv) {
// Read File and create graph and initial estimate // Read File and create graph and initial estimate
// we are in build/examples, data is in examples/Data // we are in build/examples, data is in examples/Data
pose2SLAM::Graph::shared_ptr graph ; NonlinearFactorGraph::shared_ptr graph ;
pose2SLAM::Values::shared_ptr initial; Values::shared_ptr initial;
SharedDiagonal model = Diagonal::Sigmas(Vector_(3, 0.05, 0.05, 5.0*M_PI/180.0)); SharedDiagonal model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.05, 0.05, 5.0*M_PI/180.0));
boost::tie(graph,initial) = load2D("../../examples/Data/w100-odom.graph",model); boost::tie(graph,initial) = load2D("../../examples/Data/w100-odom.graph",model);
initial->print("Initial estimate:\n"); initial->print("Initial estimate:\n");
// Add a Gaussian prior on first poses // Add a Gaussian prior on first poses
Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin
SharedDiagonal priorNoise = Diagonal::Sigmas(Vector_(3, 0.01, 0.01, 0.01)); SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.01, 0.01, 0.01));
graph->addPosePrior(0, priorMean, priorNoise); graph->add(PriorFactor<Pose2>(0, priorMean, priorNoise));
// Single Step Optimization using Levenberg-Marquardt // Single Step Optimization using Levenberg-Marquardt
pose2SLAM::Values result = graph->optimize(*initial); Values result = LevenbergMarquardtOptimizer(*graph, *initial).optimize();
result.print("\nFinal result:\n"); result.print("\nFinal result:\n");
// Plot the covariance of the last pose // Plot the covariance of the last pose