134 lines
4.2 KiB
C++
134 lines
4.2 KiB
C++
/* ----------------------------------------------------------------------------
|
|
|
|
* 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 testTOAFactor.cpp
|
|
* @brief Unit tests for "Time of Arrival" factor
|
|
* @author Frank Dellaert
|
|
* @author Jay Chakravarty
|
|
* @date December 2014
|
|
*/
|
|
|
|
#include <gtsam_unstable/geometry/Event.h>
|
|
#include <gtsam/nonlinear/ExpressionFactorGraph.h>
|
|
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
|
|
#include <gtsam/base/numericalDerivative.h>
|
|
|
|
#include <CppUnitLite/TestHarness.h>
|
|
#include <boost/format.hpp>
|
|
#include <boost/bind.hpp>
|
|
|
|
using namespace std;
|
|
using namespace gtsam;
|
|
|
|
// typedefs
|
|
typedef Eigen::Matrix<double, 1, 1> Vector1;
|
|
typedef Expression<double> Double_;
|
|
typedef Expression<Point3> Point3_;
|
|
typedef Expression<Event> Event_;
|
|
|
|
// units
|
|
static const double ms = 1e-3;
|
|
static const double cm = 1e-2;
|
|
|
|
// Create a noise model for the TOA error
|
|
static SharedNoiseModel model(noiseModel::Isotropic::Sigma(1, 0.5 * ms));
|
|
|
|
static const double timeOfEvent = 25;
|
|
static const Event exampleEvent(timeOfEvent, 1, 0, 0);
|
|
static const Point3 microphoneAt0(0,0,0);
|
|
|
|
//*****************************************************************************
|
|
TEST( TOAFactor, NewWay ) {
|
|
Key key = 12;
|
|
Event_ eventExpression(key);
|
|
Point3_ microphoneConstant(microphoneAt0); // constant expression
|
|
double measurement = 7;
|
|
Double_ expression(&Event::toa, eventExpression, microphoneConstant);
|
|
ExpressionFactor<double> factor(model, measurement, expression);
|
|
}
|
|
|
|
//*****************************************************************************
|
|
TEST( TOAFactor, WholeEnchilada ) {
|
|
|
|
static const bool verbose = false;
|
|
|
|
// Create microphones
|
|
const double height = 0.5;
|
|
vector<Point3> microphones;
|
|
microphones.push_back(Point3(0, 0, height));
|
|
microphones.push_back(Point3(403 * cm, 0, height));
|
|
microphones.push_back(Point3(403 * cm, 403 * cm, height));
|
|
microphones.push_back(Point3(0, 403 * cm, 2 * height));
|
|
EXPECT_LONGS_EQUAL(4, microphones.size());
|
|
// microphones.push_back(Point3(200 * cm, 200 * cm, height));
|
|
|
|
// Create a ground truth point
|
|
const double timeOfEvent = 0;
|
|
Event groundTruthEvent(timeOfEvent, 245 * cm, 201.5 * cm, (212 - 45) * cm);
|
|
|
|
// Simulate simulatedTOA
|
|
size_t K = microphones.size();
|
|
vector<double> simulatedTOA(K);
|
|
for (size_t i = 0; i < K; i++) {
|
|
simulatedTOA[i] = groundTruthEvent.toa(microphones[i]);
|
|
if (verbose) {
|
|
cout << "mic" << i << " = " << microphones[i] << endl;
|
|
cout << "z" << i << " = " << simulatedTOA[i] / ms << endl;
|
|
}
|
|
}
|
|
|
|
// Now, estimate using non-linear optimization
|
|
ExpressionFactorGraph graph;
|
|
Key key = 12;
|
|
Event_ eventExpression(key);
|
|
for (size_t i = 0; i < K; i++) {
|
|
Point3_ microphone_i(microphones[i]); // constant expression
|
|
Double_ predictTOA(&Event::toa, eventExpression, microphone_i);
|
|
graph.addExpressionFactor(predictTOA, simulatedTOA[i], model);
|
|
}
|
|
|
|
/// Print the graph
|
|
if (verbose)
|
|
GTSAM_PRINT(graph);
|
|
|
|
// Create initial estimate
|
|
Values initialEstimate;
|
|
//Event estimatedEvent(timeOfEvent -10, 200 * cm, 150 * cm, 350 * cm);
|
|
Vector4 delta;
|
|
delta << 0.1, 0.1, -0.1, 0.1;
|
|
Event estimatedEvent = groundTruthEvent.retract(delta);
|
|
initialEstimate.insert(key, estimatedEvent);
|
|
|
|
// Print
|
|
if (verbose)
|
|
initialEstimate.print("Initial Estimate:\n");
|
|
|
|
// Optimize using Levenberg-Marquardt optimization.
|
|
LevenbergMarquardtParams params;
|
|
params.setAbsoluteErrorTol(1e-10);
|
|
if (verbose)
|
|
params.setVerbosity("ERROR");
|
|
LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, params);
|
|
Values result = optimizer.optimize();
|
|
if (verbose)
|
|
result.print("Final Result:\n");
|
|
|
|
EXPECT(assert_equal(groundTruthEvent, result.at<Event>(key), 1e-6));
|
|
}
|
|
//*****************************************************************************
|
|
int main() {
|
|
TestResult tr;
|
|
return TestRegistry::runAllTests(tr);
|
|
}
|
|
//*****************************************************************************
|
|
|