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- /* ----------------------------------------------------------------------------
- * 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
- * -------------------------------------------------------------------------- */
- /**
- * @file testVisualISAM2.cpp
- * @brief Test convergence of visualSLAM example.
- * @author Duy-Nguyen Ta
- * @author Frank Dellaert
- */
- #include <CppUnitLite/TestHarness.h>
- #include <examples/SFMdata.h>
- #include <gtsam/geometry/Point2.h>
- #include <gtsam/inference/Symbol.h>
- #include <gtsam/nonlinear/ISAM2.h>
- #include <gtsam/nonlinear/NonlinearFactorGraph.h>
- #include <gtsam/nonlinear/Values.h>
- #include <gtsam/slam/ProjectionFactor.h>
- #include <vector>
- using namespace std;
- using namespace gtsam;
- /* ************************************************************************* */
- TEST(testVisualISAM2, all)
- {
- Cal3_S2::shared_ptr K(new Cal3_S2(50.0, 50.0, 0.0, 50.0, 50.0));
- auto measurementNoise = noiseModel::Isotropic::Sigma(2, 1.0);
- // Create ground truth data
- vector<Point3> points = createPoints();
- vector<Pose3> poses = createPoses();
- // Set the parameters
- ISAM2Params parameters;
- parameters.relinearizeThreshold = 0.01;
- parameters.relinearizeSkip = 1;
- ISAM2 isam(parameters);
- // Create a Factor Graph and Values to hold the new data
- NonlinearFactorGraph graph;
- Values initialEstimate;
- // Loop over the poses, adding the observations to iSAM incrementally
- for (size_t i = 0; i < poses.size(); ++i)
- {
- // Add factors for each landmark observation
- for (size_t j = 0; j < points.size(); ++j)
- {
- PinholeCamera<Cal3_S2> camera(poses[i], *K);
- Point2 measurement = camera.project(points[j]);
- graph.emplace_shared<GenericProjectionFactor<Pose3, Point3, Cal3_S2>>(
- measurement, measurementNoise, Symbol('x', i), Symbol('l', j), K);
- }
- // Add an initial guess for the current pose
- // Intentionally initialize the variables off from the ground truth
- static Pose3 kDeltaPose(Rot3::Rodrigues(-0.1, 0.2, 0.25),
- Point3(0.05, -0.10, 0.20));
- initialEstimate.insert(Symbol('x', i), poses[i] * kDeltaPose);
- // Treat first iteration as special case
- if (i == 0)
- {
- // Add a prior on pose x0, 30cm std on x,y,z and 0.1 rad on roll,pitch,yaw
- static auto kPosePrior = noiseModel::Diagonal::Sigmas(
- (Vector(6) << Vector3::Constant(0.1), Vector3::Constant(0.3))
- .finished());
- graph.addPrior(Symbol('x', 0), poses[0], kPosePrior);
- // Add a prior on landmark l0
- static auto kPointPrior = noiseModel::Isotropic::Sigma(3, 0.1);
- graph.addPrior(Symbol('l', 0), points[0], kPointPrior);
- // Add initial guesses to all observed landmarks
- // Intentionally initialize the variables off from the ground truth
- static Point3 kDeltaPoint(-0.25, 0.20, 0.15);
- for (size_t j = 0; j < points.size(); ++j)
- initialEstimate.insert<Point3>(Symbol('l', j), points[j] + kDeltaPoint);
- }
- else
- {
- // Update iSAM with the new factors
- isam.update(graph, initialEstimate);
- // Do an extra update to converge withing these 8 iterations
- isam.update();
- // Optimize
- Values currentEstimate = isam.calculateEstimate();
- // reset for next iteration
- graph.resize(0);
- initialEstimate.clear();
- }
- } // for loop
- auto result = isam.calculateEstimate();
- EXPECT_LONGS_EQUAL(16, result.size());
- for (size_t j = 0; j < points.size(); ++j)
- {
- Symbol key('l', j);
- EXPECT(assert_equal(points[j], result.at<Point3>(key), 0.01));
- }
- }
- /* ************************************************************************* */
- int main()
- {
- TestResult tr;
- return TestRegistry::runAllTests(tr);
- }
- /* ************************************************************************* */
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