134 lines
		
	
	
		
			4.2 KiB
		
	
	
	
		
			C++
		
	
	
			
		
		
	
	
			134 lines
		
	
	
		
			4.2 KiB
		
	
	
	
		
			C++
		
	
	
| /* ----------------------------------------------------------------------------
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| 
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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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| 
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|  * See LICENSE for the license information
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| 
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|  * -------------------------------------------------------------------------- */
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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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| 
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| #include <gtsam_unstable/geometry/Event.h>
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| #include <gtsam/nonlinear/ExpressionFactorGraph.h>
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| #include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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| #include <gtsam/base/numericalDerivative.h>
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| 
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| #include <CppUnitLite/TestHarness.h>
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| #include <boost/format.hpp>
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| #include <boost/bind.hpp>
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| 
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| using namespace std;
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| using namespace gtsam;
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| 
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| // typedefs
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| typedef Eigen::Matrix<double, 1, 1> Vector1;
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| typedef Expression<double> Double_;
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| typedef Expression<Point3> Point3_;
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| typedef Expression<Event> Event_;
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| 
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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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| 
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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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| 
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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 microphoneAt0;
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| 
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| //*****************************************************************************
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| TEST( TOAFactor, NewWay ) {
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|   Key key = 12;
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|   Event_ eventExpression(key);
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|   Point3_ microphoneConstant(microphoneAt0); // constant expression
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|   double measurement = 7;
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|   Double_ expression(&Event::toa, eventExpression, microphoneConstant);
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|   ExpressionFactor<double> factor(model, measurement, expression);
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| }
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| 
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| //*****************************************************************************
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| TEST( TOAFactor, WholeEnchilada ) {
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| 
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|   static const bool verbose = false;
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| 
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|   // Create microphones
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|   const double height = 0.5;
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|   vector<Point3> microphones;
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|   microphones.push_back(Point3(0, 0, height));
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|   microphones.push_back(Point3(403 * cm, 0, height));
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|   microphones.push_back(Point3(403 * cm, 403 * cm, height));
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|   microphones.push_back(Point3(0, 403 * cm, 2 * height));
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|   EXPECT_LONGS_EQUAL(4, microphones.size());
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| //  microphones.push_back(Point3(200 * cm, 200 * cm, height));
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| 
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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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| 
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|   // Simulate simulatedTOA
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|   size_t K = microphones.size();
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|   vector<double> simulatedTOA(K);
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|   for (size_t i = 0; i < K; i++) {
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|     simulatedTOA[i] = groundTruthEvent.toa(microphones[i]);
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|     if (verbose) {
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|       cout << "mic" << i << " = " << microphones[i] << endl;
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|       cout << "z" << i << " = " << simulatedTOA[i] / ms << endl;
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|     }
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|   }
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| 
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|   // Now, estimate using non-linear optimization
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|   ExpressionFactorGraph graph;
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|   Key key = 12;
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|   Event_ eventExpression(key);
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|   for (size_t i = 0; i < K; i++) {
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|     Point3_ microphone_i(microphones[i]); // constant expression
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|     Double_ predictTOA(&Event::toa, eventExpression, microphone_i);
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|     graph.addExpressionFactor(predictTOA, simulatedTOA[i], model);
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|   }
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| 
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|   /// Print the graph
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|   if (verbose)
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|     GTSAM_PRINT(graph);
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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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| 
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|   // Print
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|   if (verbose)
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|     initialEstimate.print("Initial Estimate:\n");
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| 
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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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|   if (verbose)
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|     params.setVerbosity("ERROR");
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|   LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, params);
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|   Values result = optimizer.optimize();
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|   if (verbose)
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|     result.print("Final Result:\n");
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| 
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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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| 
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