119 lines
3.8 KiB
C++
119 lines
3.8 KiB
C++
/*
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* COPYRIGHT AND PERMISSION NOTICE
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* Penn Software MSCKF_VIO
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* Copyright (C) 2017 The Trustees of the University of Pennsylvania
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* All rights reserved.
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*/
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#include <iostream>
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#include <vector>
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#include <map>
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#include <Eigen/Dense>
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#include <Eigen/Geometry>
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#include <Eigen/StdVector>
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#include <gtest/gtest.h>
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#include <random_numbers/random_numbers.h>
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#include <msckf_vio/cam_state.h>
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#include <msckf_vio/feature.hpp>
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using namespace std;
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using namespace Eigen;
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using namespace msckf_vio;
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TEST(FeatureInitializeTest, sphereDistribution) {
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// Set the real feature at the origin of the world frame.
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Vector3d feature(0.5, 0.0, 0.0);
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// Add 6 camera poses, all of which are able to see the
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// feature at the origin. For simplicity, the six camera
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// view are located at the six intersections between a
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// unit sphere and the coordinate system. And the z axes
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// of the camera frames are facing the origin.
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vector<Isometry3d> cam_poses(6);
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// Positive x axis.
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cam_poses[0].linear() << 0.0, 0.0, -1.0,
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1.0, 0.0, 0.0, 0.0, -1.0, 0.0;
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cam_poses[0].translation() << 1.0, 0.0, 0.0;
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// Positive y axis.
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cam_poses[1].linear() << -1.0, 0.0, 0.0,
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0.0, 0.0, -1.0, 0.0, -1.0, 0.0;
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cam_poses[1].translation() << 0.0, 1.0, 0.0;
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// Negative x axis.
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cam_poses[2].linear() << 0.0, 0.0, 1.0,
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-1.0, 0.0, 0.0, 0.0, -1.0, 0.0;
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cam_poses[2].translation() << -1.0, 0.0, 0.0;
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// Negative y axis.
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cam_poses[3].linear() << 1.0, 0.0, 0.0,
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0.0, 0.0, 1.0, 0.0, -1.0, 0.0;
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cam_poses[3].translation() << 0.0, -1.0, 0.0;
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// Positive z axis.
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cam_poses[4].linear() << 0.0, -1.0, 0.0,
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-1.0, 0.0, 0.0, 0.0, 0.0, -1.0;
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cam_poses[4].translation() << 0.0, 0.0, 1.0;
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// Negative z axis.
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cam_poses[5].linear() << 1.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 1.0;
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cam_poses[5].translation() << 0.0, 0.0, -1.0;
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// Set the camera states
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CamStateServer cam_states;
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for (int i = 0; i < 6; ++i) {
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CAMState new_cam_state;
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new_cam_state.id = i;
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new_cam_state.time = static_cast<double>(i);
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new_cam_state.orientation = rotationToQuaternion(
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Matrix3d(cam_poses[i].linear().transpose()));
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new_cam_state.position = cam_poses[i].translation();
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cam_states[new_cam_state.id] = new_cam_state;
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}
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// Compute measurements.
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random_numbers::RandomNumberGenerator noise_generator;
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vector<Vector2d, aligned_allocator<Vector2d> > measurements(6);
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for (int i = 0; i < 6; ++i) {
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Isometry3d cam_pose_inv = cam_poses[i].inverse();
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Vector3d p = cam_pose_inv.linear()*feature + cam_pose_inv.translation();
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double u = p(0) / p(2) + noise_generator.gaussian(0.0, 0.01);
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double v = p(1) / p(2) + noise_generator.gaussian(0.0, 0.01);
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//double u = p(0) / p(2);
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//double v = p(1) / p(2);
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measurements[i] = Vector2d(u, v);
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}
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for (int i = 0; i < 6; ++i) {
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cout << "pose " << i << ":" << endl;
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cout << "orientation: " << endl;
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cout << cam_poses[i].linear() << endl;
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cout << "translation: " << endl;
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cout << cam_poses[i].translation().transpose() << endl;
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cout << "measurement: " << endl;
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cout << measurements[i].transpose() << endl;
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cout << endl;
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}
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// Initialize a feature object.
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Feature feature_object;
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for (int i = 0; i < 6; ++i)
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feature_object.observations[i] = measurements[i];
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// Compute the 3d position of the feature.
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feature_object.initializePosition(cam_states);
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// Check the difference between the computed 3d
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// feature position and the groud truth.
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cout << "ground truth position: " << feature.transpose() << endl;
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cout << "estimated position: " << feature_object.position.transpose() << endl;
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Eigen::Vector3d error = feature_object.position - feature;
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EXPECT_NEAR(error.norm(), 0, 0.05);
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}
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int main(int argc, char** argv) {
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testing::InitGoogleTest(&argc, argv);
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return RUN_ALL_TESTS();
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}
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