2011-08-19 21:11:04 +08:00
										 
									 
								 
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								/* ----------------------------------------------------------------------------
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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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											2011-10-14 11:23:14 +08:00
										 
									 
								 
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								/**
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								 * @file Pose2SLAMExample_easy.cpp
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								 *
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											2011-08-19 21:11:04 +08:00
										 
									 
								 
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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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											2011-10-14 11:23:14 +08:00
										 
									 
								 
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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/NonlinearOptimization.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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									pose2SLAM::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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									pose2SLAM::Values result = optimize<Graph, pose2SLAM::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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