gtsam/matlab/examples/StereoVOExample.m

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 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
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
graph = visualSLAM.Graph;

%% add a constraint on the starting pose
import gtsam.*
first_pose = Pose3();
graph.addPoseConstraint(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.addStereoMeasurement(StereoPoint2(520, 480, 440), stereo_model, x1, l1, K);
graph.addStereoMeasurement(StereoPoint2(120,  80, 440), stereo_model, x1, l2, K);
graph.addStereoMeasurement(StereoPoint2(320, 280, 140), stereo_model, x1, l3, K);

%pose 2
graph.addStereoMeasurement(StereoPoint2(570, 520, 490), stereo_model, x2, l1, K);
graph.addStereoMeasurement(StereoPoint2( 70,  20, 490), stereo_model, x2, l2, K);
graph.addStereoMeasurement(StereoPoint2(320, 270, 115), stereo_model, x2, l3, K);


%% Create initial estimate for camera poses and landmarks
import gtsam.*
initialEstimate = visualSLAM.Values;
initialEstimate.insertPose(x1, first_pose);
% noisy estimate for pose 2
initialEstimate.insertPose(x2, Pose3(Rot3(), Point3(0.1,-.1,1.1)));
initialEstimate.insertPoint(l1, Point3( 1,  1, 5));
initialEstimate.insertPoint(l2, Point3(-1,  1, 5));
initialEstimate.insertPoint(l3, Point3( 0,-.5, 5));

%% optimize
fprintf(1,'Optimizing\n'); tic
result = graph.optimize(initialEstimate,1);
toc

%% visualize initial trajectory, final trajectory, and final points
cla; hold on;
axis normal
axis([-1 6 -2 2 -1.5 1.5]);
axis equal
view(-38,12)

% initial trajectory in red (rotated so Z is up)
T=initialEstimate.translations;
plot3(T(:,3),-T(:,1),-T(:,2), '-*r','LineWidth',2);

% final trajectory in green (rotated so Z is up)
T=result.translations;
plot3(T(:,3),-T(:,1),-T(:,2), '-*g','LineWidth',2);
xlabel('X (m)'); ylabel('Y (m)'); zlabel('Z (m)');

% optimized 3D points (rotated so Z is up)
P = result.points();
plot3(P(:,3),-P(:,1),-P(:,2),'*');