83 lines
2.7 KiB
Matlab
83 lines
2.7 KiB
Matlab
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% GTSAM Copyright 2010, Georgia Tech Research Corporation,
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% Atlanta, Georgia 30332-0415
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% All Rights Reserved
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% Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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%
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% See LICENSE for the license information
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%
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% @brief Read Stereo Visual Odometry from file and optimize
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% @author Chris Beall
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%% Load calibration
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% format: fx fy skew cx cy baseline
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calib = dlmread('../../examples/Data/VO_calibration.txt');
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K = gtsamCal3_S2Stereo(calib(1), calib(2), calib(3), calib(4), calib(5), calib(6));
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stereo_model = gtsamnoiseModelDiagonal_Sigmas([1.0; 1.0; 1.0]);
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%% create empty graph and values
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graph = visualSLAMGraph;
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initial = visualSLAMValues;
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%% load the initial poses from VO
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% row format: camera_id 4x4 pose (row, major)
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fprintf(1,'Reading data\n');
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cameras = dlmread('../../examples/Data/VO_camera_poses_large.txt');
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for i=1:size(cameras,1)
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pose = gtsamPose3(reshape(cameras(i,2:17),4,4)');
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initial.insertPose(symbol('x',cameras(i,1)),pose);
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end
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%% load stereo measurements and initialize landmarks
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% camera_id landmark_id uL uR v X Y Z
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measurements = dlmread('../../examples/Data/VO_stereo_factors_large.txt');
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fprintf(1,'Creating Graph\n'); tic
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for i=1:size(measurements,1)
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sf = measurements(i,:);
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graph.addStereoMeasurement(gtsamStereoPoint2(sf(3),sf(4),sf(5)), stereo_model, ...
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symbol('x', sf(1)), symbol('l', sf(2)), K);
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if ~initial.exists(symbol('l',sf(2)))
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% 3D landmarks are stored in camera coordinates: transform
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% to world coordinates using the respective initial pose
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pose = initial.pose(symbol('x', sf(1)));
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world_point = pose.transform_from(gtsamPoint3(sf(6),sf(7),sf(8)));
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initial.insertPoint(symbol('l',sf(2)), world_point);
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end
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end
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toc
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%% add a constraint on the starting pose
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key = symbol('x',1);
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first_pose = initial.pose(key);
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graph.addPoseConstraint(key, first_pose);
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%% optimize
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fprintf(1,'Optimizing\n'); tic
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result = graph.optimize(initial,1);
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toc
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%% visualize initial trajectory, final trajectory, and final points
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figure(1); clf; hold on;
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% initial trajectory in red (rotated so Z is up)
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plot3(initial.zs(),-initial.xs(),-initial.ys(), '-*r','LineWidth',2);
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% final trajectory in green (rotated so Z is up)
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plot3(result.zs(),-result.xs(),-result.ys(), '-*g','LineWidth',2);
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xlabel('X (m)'); ylabel('Y (m)'); zlabel('Z (m)');
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% switch to XZ view
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view([0 0]);
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% optimized 3D points (rotated so Z is up)
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points = result.points();
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plot3(points(:,3),-points(:,1),-points(:,2),'.');
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axis([0 100 -20 20 -5 20]);
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axis equal
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view(3)
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