/* ---------------------------------------------------------------------------- * 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 Pose2SLAMExample.cpp * @brief Simple Pose2SLAM Example using * pre-built pose2SLAM domain * @author Chris Beall */ #include #include #include // pull in the Pose2 SLAM domain with all typedefs and helper functions defined #include #include using namespace std; using namespace gtsam; using namespace boost; using namespace gtsam::pose2SLAM; int main(int argc, char** argv) { // create keys for robot positions Key x1(1), x2(2), x3(3); /* 1. create graph container and add factors to it */ shared_ptr graph(new Graph); /* 2.a add prior */ // gaussian for prior SharedDiagonal prior_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.3, 0.3, 0.1)); Pose2 prior_measurement(0.0, 0.0, 0.0); // prior at origin graph->addPrior(x1, prior_measurement, prior_model); // add directly to graph /* 2.b add odometry */ // general noisemodel for odometry SharedDiagonal odom_model = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1)); /* Pose2 measurements take (x,y,theta), where theta is taken from the positive x-axis*/ Pose2 odom_measurement(2.0, 0.0, 0.0); // create a measurement for both factors (the same in this case) graph->addConstraint(x1, x2, odom_measurement, odom_model); graph->addConstraint(x2, x3, odom_measurement, odom_model); graph->print("full graph"); /* 3. Create the data structure to hold the initial estinmate to the solution * initialize to noisy points */ shared_ptr initial(new Values); initial->insert(x1, Pose2(0.5, 0.0, 0.2)); initial->insert(x2, Pose2(2.3, 0.1,-0.2)); initial->insert(x3, Pose2(4.1, 0.1, 0.1)); initial->print("initial estimate"); /* 4.2.1 Alternatively, you can go through the process step by step * Choose an ordering */ Ordering::shared_ptr ordering = graph->orderingCOLAMD(*initial); /* 4.2.2 set up solver and optimize */ Optimizer optimizer(graph, initial, ordering); Optimizer::Parameters::verbosityLevel verbosity = pose2SLAM::Optimizer::Parameters::SILENT; Optimizer optimizer_result = optimizer.levenbergMarquardt(1e-15, 1e-15, verbosity); Values result = *optimizer_result.config(); result.print("final result"); return 0; }