cleanup
parent
ec5ef222c9
commit
5b37647e11
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@ -119,7 +119,6 @@ void SmootherUpdate(HybridSmoother& smoother, HybridNonlinearFactorGraph& graph,
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const Values& initial, size_t maxNrHypotheses,
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Values* result) {
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HybridGaussianFactorGraph linearized = *graph.linearize(initial);
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// std::cout << "index: " << index << std::endl;
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smoother.update(linearized, maxNrHypotheses);
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graph.resize(0);
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// HybridValues delta = smoother.hybridBayesNet().optimize();
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@ -2,8 +2,10 @@ clear;
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gt = dlmread('Data/ISAM2_GT_city10000.txt');
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% Generate by running `make ISAM2_City10000.run`
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eh_poses = dlmread('../build/examples/ISAM2_city10000.txt');
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% Generate by running `make Hybrid_City10000.run`
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h_poses = dlmread('../build/examples/HybridISAM_city10000.txt');
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% Plot the same number of GT poses as estimated ones
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@ -16,13 +18,18 @@ figure(1)
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hold on;
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axis equal;
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axis([-65 65 -75 60])
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title('City10000 result with Hybrid Factor Graphs');
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plot(gt(:,1), gt(:,2), '--', 'LineWidth', 4, 'color', [0.1 0.7 0.1 0.5]);
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% hold off;
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% figure(2)
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% hold on;
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% axis equal;
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% axis([-65 65 -75 60])
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plot(eh_poses(:,1), eh_poses(:,2), '-', 'LineWidth', 2, 'color', [0.9 0.1 0. 0.4]);
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plot(h_poses(:,1), h_poses(:,2), '-', 'LineWidth', 2, 'color', [0.1 0.1 0.9 0.4]);
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legend('Ground truth', 'Hybrid Factor Graphs');
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hold off;
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figure(2)
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hold on;
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axis equal;
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axis([-65 65 -75 60])
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title('City10000 result with ISAM2');
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plot(gt(:,1), gt(:,2), '--', 'LineWidth', 4, 'color', [0.1 0.7 0.1 0.5]);
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plot(eh_poses(:,1), eh_poses(:,2), '-', 'LineWidth', 2, 'color', [0.9 0.1 0. 0.4]);
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legend('Ground truth', 'ISAM2');
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hold off;
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