70 lines
2.3 KiB
C++
70 lines
2.3 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_easy.cpp
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*
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* A 2D Pose SLAM example using the predefined typedefs in gtsam/slam/pose2SLAM.h
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*
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* @date 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/LevenbergMarquardtOptimizer.h>
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using namespace std;
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using namespace gtsam;
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using namespace pose2SLAM;
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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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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(1, 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.addOdometry(1, 2, odom_measurement, odom_model);
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graph.addOdometry(2, 3, 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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pose2SLAM::Values initial;
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initial.insertPose(1, Pose2(0.5, 0.0, 0.2));
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initial.insertPose(2, Pose2(2.3, 0.1,-0.2));
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initial.insertPose(3, 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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pose2SLAM::Values result = *LevenbergMarquardtOptimizer(graph, initial).optimized();
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result.print("final result");
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return 0;
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}
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