65 lines
2.1 KiB
C++
65 lines
2.1 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file Pose2SLAMExample.cpp
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* @brief A 2D Pose SLAM example using the predefined typedefs in gtsam/slam/pose2SLAM.h
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* @date Oct 21, 2010
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* @author Yong Dian Jian
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*/
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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 <cmath>
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using namespace std;
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using namespace gtsam;
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int main(int argc, char** argv) {
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// 1. Create graph container and add factors to it
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pose2SLAM::Graph graph;
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// 2a. Add Gaussian prior
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Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin
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SharedDiagonal priorNoise(Vector_(3, 0.3, 0.3, 0.1));
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graph.addPrior(1, priorMean, priorNoise);
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// 2b. Add odometry factors
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SharedDiagonal odometryNoise(Vector_(3, 0.2, 0.2, 0.1));
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graph.addOdometry(1, 2, Pose2(2.0, 0.0, 0.0), odometryNoise);
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graph.addOdometry(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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graph.addOdometry(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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graph.addOdometry(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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// 2c. Add pose constraint
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SharedDiagonal model(Vector_(3, 0.2, 0.2, 0.1));
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graph.addConstraint(5, 2, Pose2(2.0, 0.0, M_PI_2), model);
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// print
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graph.print("\nFactor graph:\n");
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// 3. Create the data structure to hold the initialEstimate estimate to the solution
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pose2SLAM::Values initialEstimate;
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initialEstimate.insertPose(1, Pose2(0.5, 0.0, 0.2));
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initialEstimate.insertPose(2, Pose2(2.3, 0.1, -0.2));
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initialEstimate.insertPose(3, Pose2(4.1, 0.1, M_PI_2));
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initialEstimate.insertPose(4, Pose2(4.0, 2.0, M_PI));
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initialEstimate.insertPose(5, Pose2(2.1, 2.1, -M_PI_2));
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initialEstimate.print("\nInitial estimate:\n");
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// 4. Single Step Optimization using Levenberg-Marquardt
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pose2SLAM::Values result = graph.optimize(initialEstimate);
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result.print("\nFinal result:\n");
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return 0;
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}
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