test_TranslationRecovery.py

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import unittest
 
import gtsam
import numpy as np
 
 
def ExampleValues():
    """ Returns example pose values of 3 points A, B and C in the world frame """
    T = []
    T.append(gtsam.Point3(np.array([3.14, 1.59, 2.65])))
    T.append(gtsam.Point3(np.array([-1.0590e+00, -3.6017e-02, -1.5720e+00])))
    T.append(gtsam.Point3(np.array([8.5034e+00, 6.7499e+00, -3.6383e+00])))
 
    data = gtsam.Values()
    for i, t in enumerate(T):
        data.insert(i, gtsam.Pose3(gtsam.Rot3(), t))
    return data
 
 
def SimulateMeasurements(gt_poses, graph_edges):
    """ Returns binary measurements for the points in the given edges."""
    measurements = []
    for edge in graph_edges:
        Ta = gt_poses.atPose3(edge[0]).translation()
        Tb = gt_poses.atPose3(edge[1]).translation()
        measurements.append(gtsam.BinaryMeasurementUnit3( \
            edge[0], edge[1], gtsam.Unit3(Tb - Ta), \
            gtsam.noiseModel.Isotropic.Sigma(3, 0.01)))
    return measurements
 
 
class TestTranslationRecovery(unittest.TestCase):
    """ Tests for the translation recovery class."""
 
    def test_constructor(self):
        """Construct from binary measurements."""
        algorithm = gtsam.TranslationRecovery()
        self.assertIsInstance(algorithm, gtsam.TranslationRecovery)
        algorithm_params = gtsam.TranslationRecovery(
            gtsam.LevenbergMarquardtParams())
        self.assertIsInstance(algorithm_params, gtsam.TranslationRecovery)
 
    def test_run(self):
        """Test selected Translation Recovery methods."""
        gt_poses = ExampleValues()
        measurements = SimulateMeasurements(gt_poses, [[0, 1], [0, 2], [1, 2]])
 
        # Set verbosity to Silent for tests
        lmParams = gtsam.LevenbergMarquardtParams()
        lmParams.setVerbosityLM("silent")
 
        algorithm = gtsam.TranslationRecovery(lmParams)
        scale = 2.0
        result = algorithm.run(measurements, scale)
 
        w_aTc = gt_poses.atPose3(2).translation() - gt_poses.atPose3(
            0).translation()
        w_aTb = gt_poses.atPose3(1).translation() - gt_poses.atPose3(
            0).translation()
        w_aTc_expected = w_aTc * scale / np.linalg.norm(w_aTb)
        w_aTb_expected = w_aTb * scale / np.linalg.norm(w_aTb)
 
        np.testing.assert_array_almost_equal(result.atPoint3(0),
                                             np.array([0, 0, 0]), 6,
                                             "Origin result is incorrect.")
        np.testing.assert_array_almost_equal(result.atPoint3(1),
                                             w_aTb_expected, 6,
                                             "Point B result is incorrect.")
        np.testing.assert_array_almost_equal(result.atPoint3(2),
                                             w_aTc_expected, 6,
                                             "Point C result is incorrect.")
 
 
if __name__ == "__main__":
    unittest.main()