testPose2Graph tests linearize
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@ -4,6 +4,8 @@
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#include <CppUnitLite/TestHarness.h>
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#include <CppUnitLite/TestHarness.h>
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#include "Pose2Graph.h"
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#include "Pose2Graph.h"
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#include "NonlinearFactorGraph-inl.h"
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#include "GaussianFactorGraph.h"
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using namespace std;
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using namespace std;
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using namespace gtsam;
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using namespace gtsam;
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@ -18,15 +20,59 @@ TEST( Pose2Graph, constructor )
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0.0, 0.25, 0.0,
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0.0, 0.25, 0.0,
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0.0, 0.0, 0.01
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0.0, 0.0, 0.01
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);
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);
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Pose2Factor constraint("p1","p2",measured, measurement_covariance);
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Pose2Factor constraint("x1","x2",measured, measurement_covariance);
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Pose2Graph graph;
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Pose2Graph graph;
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graph.push_back(Pose2Factor::shared_ptr(new Pose2Factor("p1","p2",measured, measurement_covariance)));
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graph.push_back(Pose2Factor::shared_ptr(new Pose2Factor("x1","x2",measured, measurement_covariance)));
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// get the size of the graph
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// get the size of the graph
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size_t actual = graph.size();
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size_t actual = graph.size();
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// verify
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// verify
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size_t expected = 1;
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size_t expected = 1;
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CHECK(actual == expected);
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CHECK(actual == expected);
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}
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TEST( Pose2Graph, linerization )
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{
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// create a factor between unknown poses p1 and p2
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Pose2 measured(2,2,M_PI_2);
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Matrix measurement_covariance = Matrix_(3,3,
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0.25, 0.0, 0.0,
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0.0, 0.25, 0.0,
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0.0, 0.0, 0.01
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);
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Pose2Factor constraint("x1","x2",measured, measurement_covariance);
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Pose2Graph graph;
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graph.push_back(Pose2Factor::shared_ptr(new Pose2Factor("x1","x2",measured, measurement_covariance)));
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// Choose a linearization point
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Pose2 p1(1.1,2,M_PI_2); // robot at (1.1,2) looking towards y (ground truth is at 1,2, see testPose2)
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Pose2 p2(-1,4.1,M_PI); // robot at (-1,4) looking at negative (ground truth is at 4.1,2)
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Pose2Config config;
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config.insert("x1",p1);
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config.insert("x2",p2);
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// Linearize
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GaussianFactorGraph lfg_linearized = graph.linearize(config);
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lfg_linearized.print("lfg_actual");
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// the expected linear factor
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GaussianFactorGraph lfg_expected;
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Matrix A1 = Matrix_(3,3,
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0.0, 2.0, -4.2,
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-2.0, 0.0, 4.2,
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0.0, 0.0, 10.0);
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Matrix A2 = Matrix_(3,3,
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0.0, -2.0, 0.0,
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2.0, 0.0, 0.0,
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0.0, 0.0, -10.0);
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double sigma = 1;
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Vector b = Vector_(3,-0.1,-0.1,0.0);
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lfg_expected.add("x1", A1, "x2", A2, b, sigma);
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CHECK(lfg_expected.equals(lfg_linearized));
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}
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}
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/* ************************************************************************* */
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/* ************************************************************************* */
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int main() {
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int main() {
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