76 lines
2.5 KiB
C++
76 lines
2.5 KiB
C++
/* ----------------------------------------------------------------------------
|
|
|
|
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
|
|
* Atlanta, Georgia 30332-0415
|
|
* All Rights Reserved
|
|
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
|
|
|
|
* See LICENSE for the license information
|
|
|
|
* -------------------------------------------------------------------------- */
|
|
|
|
/**
|
|
* @file LocalizationExample.cpp
|
|
* @brief Simple robot localization example
|
|
* @author Frank Dellaert
|
|
*/
|
|
|
|
// pull in the 2D PoseSLAM domain with all typedefs and helper functions defined
|
|
#include <gtsam/slam/pose2SLAM.h>
|
|
|
|
// include this for marginals
|
|
#include <gtsam/nonlinear/Marginals.h>
|
|
|
|
#include <iomanip>
|
|
#include <iostream>
|
|
|
|
using namespace std;
|
|
using namespace gtsam;
|
|
|
|
/**
|
|
* Example of a simple 2D localization example
|
|
* - Robot poses are facing along the X axis (horizontal, to the right in 2D)
|
|
* - The robot moves 2 meters each step
|
|
* - We have full odometry between poses
|
|
*/
|
|
int main(int argc, char** argv) {
|
|
|
|
// create the graph (defined in pose2SLAM.h, derived from NonlinearFactorGraph)
|
|
pose2SLAM::Graph graph;
|
|
|
|
// add a Gaussian prior on pose x_1
|
|
Pose2 priorMean(0.0, 0.0, 0.0); // prior mean is at origin
|
|
SharedDiagonal priorNoise(Vector_(3, 0.3, 0.3, 0.1)); // 30cm std on x,y, 0.1 rad on theta
|
|
graph.addPrior(1, priorMean, priorNoise); // add directly to graph
|
|
|
|
// add two odometry factors
|
|
Pose2 odometry(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case)
|
|
SharedDiagonal odometryNoise(Vector_(3, 0.2, 0.2, 0.1)); // 20cm std on x,y, 0.1 rad on theta
|
|
graph.addOdometry(1, 2, odometry, odometryNoise);
|
|
graph.addOdometry(2, 3, odometry, odometryNoise);
|
|
|
|
// print
|
|
graph.print("\nFactor graph:\n");
|
|
|
|
// create (deliberatly inaccurate) initial estimate
|
|
pose2SLAM::Values initialEstimate;
|
|
initialEstimate.insertPose(1, Pose2(0.5, 0.0, 0.2));
|
|
initialEstimate.insertPose(2, Pose2(2.3, 0.1, -0.2));
|
|
initialEstimate.insertPose(3, Pose2(4.1, 0.1, 0.1));
|
|
initialEstimate.print("\nInitial estimate:\n ");
|
|
|
|
// optimize using Levenberg-Marquardt optimization with an ordering from colamd
|
|
pose2SLAM::Values result = graph.optimize(initialEstimate);
|
|
result.print("\nFinal result:\n ");
|
|
|
|
// Query the marginals
|
|
cout.precision(2);
|
|
Marginals marginals = graph.marginals(result);
|
|
cout << "\nP1:\n" << marginals.marginalCovariance(1) << endl;
|
|
cout << "\nP2:\n" << marginals.marginalCovariance(2) << endl;
|
|
cout << "\nP3:\n" << marginals.marginalCovariance(3) << endl;
|
|
|
|
return 0;
|
|
}
|
|
|