109 lines
3.4 KiB
C++
109 lines
3.4 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file testTOAFactor.cpp
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* @brief Unit tests for "Time of Arrival" factor
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* @author Frank Dellaert
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* @author Jay Chakravarty
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* @date December 2014
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*/
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#include <gtsam/base/numericalDerivative.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/expressions.h>
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#include <gtsam_unstable/geometry/Event.h>
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#include <gtsam_unstable/slam/TOAFactor.h>
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#include <CppUnitLite/TestHarness.h>
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#include <boost/bind.hpp>
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#include <boost/format.hpp>
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using namespace std;
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using namespace gtsam;
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// typedefs
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typedef Expression<Point3> Point3_;
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typedef Expression<Event> Event_;
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// units
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static const double ms = 1e-3;
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static const double cm = 1e-2;
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// Create a noise model for the TOA error
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static SharedNoiseModel model(noiseModel::Isotropic::Sigma(1, 0.5 * ms));
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static const double timeOfEvent = 25;
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static const Event exampleEvent(timeOfEvent, 1, 0, 0);
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static const Point3 sensorAt0(0, 0, 0);
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//*****************************************************************************
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TEST(TOAFactor, NewWay) {
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Key key = 12;
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double measurement = 7;
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TOAFactor factor(key, sensorAt0, measurement, model);
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}
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//*****************************************************************************
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TEST(TOAFactor, WholeEnchilada) {
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// Create sensors
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const double height = 0.5;
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vector<Point3> sensors;
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sensors.push_back(Point3(0, 0, height));
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sensors.push_back(Point3(403 * cm, 0, height));
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sensors.push_back(Point3(403 * cm, 403 * cm, height));
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sensors.push_back(Point3(0, 403 * cm, 2 * height));
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EXPECT_LONGS_EQUAL(4, sensors.size());
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// sensors.push_back(Point3(200 * cm, 200 * cm, height));
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// Create a ground truth point
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const double timeOfEvent = 0;
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Event groundTruthEvent(timeOfEvent, 245 * cm, 201.5 * cm, (212 - 45) * cm);
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// Simulate simulatedTOA
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size_t K = sensors.size();
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vector<double> simulatedTOA(K);
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TimeOfArrival toa;
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for (size_t i = 0; i < K; i++) {
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simulatedTOA[i] = toa(groundTruthEvent, sensors[i]);
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}
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// Now, estimate using non-linear optimization
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NonlinearFactorGraph graph;
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Key key = 12;
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for (size_t i = 0; i < K; i++) {
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graph.emplace_shared<TOAFactor>(key, sensors[i], simulatedTOA[i], model);
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}
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// Create initial estimate
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Values initialEstimate;
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// Event estimatedEvent(timeOfEvent -10, 200 * cm, 150 * cm, 350 * cm);
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Vector4 delta;
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delta << 0.1, 0.1, -0.1, 0.1;
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Event estimatedEvent = groundTruthEvent.retract(delta);
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initialEstimate.insert(key, estimatedEvent);
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// Optimize using Levenberg-Marquardt optimization.
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LevenbergMarquardtParams params;
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params.setAbsoluteErrorTol(1e-10);
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LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, params);
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Values result = optimizer.optimize();
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EXPECT(assert_equal(groundTruthEvent, result.at<Event>(key), 1e-6));
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}
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//*****************************************************************************
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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//*****************************************************************************
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