%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 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 % % @brief Example of a simple 2D localization example % @author Frank Dellaert %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Create the graph (defined in pose2SLAM.h, derived from NonlinearFactorGraph) graph = pose2SLAMGraph; %% Add a Gaussian prior on pose x_1 priorMean = gtsamPose2(0.0, 0.0, 0.0); % prior mean is at origin priorNoise = gtsamnoiseModelDiagonal_Sigmas([0.3; 0.3; 0.1]); % 30cm std on x,y, 0.1 rad on theta graph.addPosePrior(1, priorMean, priorNoise); % add directly to graph %% Add two odometry factors odometry = gtsamPose2(2.0, 0.0, 0.0); % create a measurement for both factors (the same in this case) odometryNoise = gtsamnoiseModelDiagonal_Sigmas([0.2; 0.2; 0.1]); % 20cm std on x,y, 0.1 rad on theta graph.addRelativePose(1, 2, odometry, odometryNoise); graph.addRelativePose(2, 3, odometry, odometryNoise); %% Initialize to noisy points initialEstimate = pose2SLAMValues; initialEstimate.insertPose(1, gtsamPose2(0.5, 0.0, 0.2)); initialEstimate.insertPose(2, gtsamPose2(2.3, 0.1,-0.2)); initialEstimate.insertPose(3, gtsamPose2(4.1, 0.1, 0.1)); %% Optimize using Levenberg-Marquardt optimization with an ordering from colamd result = graph.optimize(initialEstimate,0); marginals = graph.marginals(result); marginals.marginalCovariance(1); %% Check first pose equality pose_1 = result.pose(1); CHECK('pose_1.equals(gtsamPose2,1e-4)',pose_1.equals(gtsamPose2,1e-4));