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Now using awesome ExpressionFactorGraph

release/4.3a0
dellaert 2014-12-28 19:26:00 +01:00
parent e119846280
commit c8bfeb6692
1 changed files with 8 additions and 8 deletions
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16
examples/Pose2SLAMExampleExpressions.cpp
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@ -19,7 +19,7 @@
// The two new headers that allow using our Automatic Differentiation Expression framework // The two new headers that allow using our Automatic Differentiation Expression framework
#include <gtsam/slam/expressions.h> #include <gtsam/slam/expressions.h>
#include <gtsam/nonlinear/ExpressionFactor.h> #include <gtsam/nonlinear/ExpressionFactorGraph.h>
// Header order is close to far // Header order is close to far
#include <gtsam/nonlinear/NonlinearFactorGraph.h> #include <gtsam/nonlinear/NonlinearFactorGraph.h>
@ -35,26 +35,26 @@ using namespace gtsam;
int main(int argc, char** argv) { int main(int argc, char** argv) {
// 1. Create a factor graph container and add factors to it // 1. Create a factor graph container and add factors to it
NonlinearFactorGraph graph; ExpressionFactorGraph graph;
// Create Expressions for unknowns // Create Expressions for unknowns
Pose2_ x1(1), x2(2), x3(3), x4(4), x5(5); Pose2_ x1(1), x2(2), x3(3), x4(4), x5(5);
// 2a. Add a prior on the first pose, setting it to the origin // 2a. Add a prior on the first pose, setting it to the origin
noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector3(0.3, 0.3, 0.1)); noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Sigmas(Vector3(0.3, 0.3, 0.1));
graph.push_back(ExpressionFactor<Pose2>(priorNoise, Pose2(0, 0, 0), x1)); graph.addExpressionFactor(x1, Pose2(0, 0, 0), priorNoise);
// For simplicity, we will use the same noise model for odometry and loop closures // For simplicity, we will use the same noise model for odometry and loop closures
noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1)); noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1));
// 2b. Add odometry factors // 2b. Add odometry factors
graph.push_back(ExpressionFactor<Pose2>(model, Pose2(2, 0, 0 ), between(x1,x2))); graph.addExpressionFactor(between(x1,x2), Pose2(2, 0, 0 ), model);
graph.push_back(ExpressionFactor<Pose2>(model, Pose2(2, 0, M_PI_2), between(x2,x3))); graph.addExpressionFactor(between(x2,x3), Pose2(2, 0, M_PI_2), model);
graph.push_back(ExpressionFactor<Pose2>(model, Pose2(2, 0, M_PI_2), between(x3,x4))); graph.addExpressionFactor(between(x3,x4), Pose2(2, 0, M_PI_2), model);
graph.push_back(ExpressionFactor<Pose2>(model, Pose2(2, 0, M_PI_2), between(x4,x5))); graph.addExpressionFactor(between(x4,x5), Pose2(2, 0, M_PI_2), model);
// 2c. Add the loop closure constraint // 2c. Add the loop closure constraint
graph.push_back(ExpressionFactor<Pose2>(model, Pose2(2, 0, M_PI_2), between(x5,x2))); graph.addExpressionFactor(between(x5,x2), Pose2(2, 0, M_PI_2), model);
graph.print("\nFactor Graph:\n"); // print graph.print("\nFactor Graph:\n"); // print
// 3. Create the data structure to hold the initialEstimate estimate to the solution // 3. Create the data structure to hold the initialEstimate estimate to the solution