%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 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 Basic VO Example with 3 landmarks and two cameras % @author Chris Beall %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Assumptions % - For simplicity this example is in the camera's coordinate frame % - X: right, Y: down, Z: forward % - Pose x1 is at the origin, Pose 2 is 1 meter forward (along Z-axis) % - x1 is fixed with a constraint, x2 is initialized with noisy values % - No noise on measurements %% Create keys for variables import gtsam.* x1 = symbol('x',1); x2 = symbol('x',2); l1 = symbol('l',1); l2 = symbol('l',2); l3 = symbol('l',3); %% Create graph container and add factors to it import gtsam.* graph = NonlinearFactorGraph; %% add a constraint on the starting pose import gtsam.* first_pose = Pose3(); graph.add(NonlinearEqualityPose3(x1, first_pose)); %% Create realistic calibration and measurement noise model % format: fx fy skew cx cy baseline import gtsam.* K = Cal3_S2Stereo(1000, 1000, 0, 320, 240, 0.2); stereo_model = noiseModel.Diagonal.Sigmas([1.0; 1.0; 1.0]); %% Add measurements import gtsam.* % pose 1 graph.add(GenericStereoFactor3D(StereoPoint2(520, 480, 440), stereo_model, x1, l1, K)); graph.add(GenericStereoFactor3D(StereoPoint2(120, 80, 440), stereo_model, x1, l2, K)); graph.add(GenericStereoFactor3D(StereoPoint2(320, 280, 140), stereo_model, x1, l3, K)); %pose 2 graph.add(GenericStereoFactor3D(StereoPoint2(570, 520, 490), stereo_model, x2, l1, K)); graph.add(GenericStereoFactor3D(StereoPoint2( 70, 20, 490), stereo_model, x2, l2, K)); graph.add(GenericStereoFactor3D(StereoPoint2(320, 270, 115), stereo_model, x2, l3, K)); %% Create initial estimate for camera poses and landmarks import gtsam.* initialEstimate = Values; initialEstimate.insert(x1, first_pose); % noisy estimate for pose 2 initialEstimate.insert(x2, Pose3(Rot3(), Point3(0.1,-.1,1.1))); initialEstimate.insert(l1, Point3( 1, 1, 5)); initialEstimate.insert(l2, Point3(-1, 1, 5)); initialEstimate.insert(l3, Point3( 0,-.5, 5)); %% optimize fprintf(1,'Optimizing\n'); tic import gtsam.* optimizer = LevenbergMarquardtOptimizer(graph, initialEstimate); result = optimizer.optimizeSafely(); toc %% visualize initial trajectory, final trajectory, and final points cla; hold on; axis normal axis([-1.5 1.5 -2 2 -1 6]); axis equal view(-38,12) camup([0;1;0]); gtsam_utils.plot3DTrajectory(initialEstimate, 'r', 1, 0.3); gtsam_utils.plot3DTrajectory(result, 'g', 1, 0.3); gtsam_utils.plot3DPoints(result);