59 lines
1.8 KiB
C++
59 lines
1.8 KiB
C++
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/*
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* Pose2SLAMExample_easy.cpp
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*
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* Created on: Oct 21, 2010
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* Author: ydjian
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*/
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#include <cmath>
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#include <iostream>
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#include <boost/shared_ptr.hpp>
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// pull in the Pose2 SLAM domain with all typedefs and helper functions defined
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#include <gtsam/slam/pose2SLAM.h>
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#include <gtsam/nonlinear/NonlinearOptimization-inl.h>
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using namespace std;
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using namespace gtsam;
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using namespace gtsam::pose2SLAM;
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int main(int argc, char** argv) {
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// create keys for robot positions
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Key x1(1), x2(2), x3(3);
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/* 1. create graph container and add factors to it */
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Graph graph ;
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/* 2.a add prior */
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// gaussian for prior
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SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1));
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Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin
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graph.addPrior(x1, prior_measurement, prior_model); // add directly to graph
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/* 2.b add odometry */
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// general noisemodel for odometry
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SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1));
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/* Pose2 measurements take (x,y,theta), where theta is taken from the positive x-axis*/
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Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case)
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graph.addConstraint(x1, x2, odom_measurement, odom_model);
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graph.addConstraint(x2, x3, odom_measurement, odom_model);
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graph.print("full graph");
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/* 3. Create the data structure to hold the initial estinmate to the solution
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* initialize to noisy points */
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Values initial;
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initial.insert(x1, Pose2(0.5, 0.0, 0.2));
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initial.insert(x2, Pose2(2.3, 0.1,-0.2));
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initial.insert(x3, Pose2(4.1, 0.1, 0.1));
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initial.print("initial estimate");
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/* 4 Single Step Optimization
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* optimize using Levenberg-Marquardt optimization with an ordering from colamd */
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Values result = optimize<Graph, Values>(graph, initial);
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result.print("final result");
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return 0;
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}
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