Merge pull request #252 from borglab/feature/TOA

Time of arrival measurements
release/4.3a0
Frank Dellaert 2020-03-25 16:41:02 -04:00 committed by GitHub
commit 0c2890b815
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9 changed files with 456 additions and 126 deletions

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"""
GTSAM Copyright 2010-2020, 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
Track a moving object "Time of Arrival" measurements at 4 microphones.
Author: Frank Dellaert
"""
# pylint: disable=invalid-name, no-name-in-module
from gtsam import (LevenbergMarquardtOptimizer, LevenbergMarquardtParams,
NonlinearFactorGraph, Point3, Values, noiseModel_Isotropic)
from gtsam_unstable import Event, TimeOfArrival, TOAFactor
# units
MS = 1e-3
CM = 1e-2
# Instantiate functor with speed of sound value
TIME_OF_ARRIVAL = TimeOfArrival(330)
def define_microphones():
"""Create microphones."""
height = 0.5
microphones = []
microphones.append(Point3(0, 0, height))
microphones.append(Point3(403 * CM, 0, height))
microphones.append(Point3(403 * CM, 403 * CM, height))
microphones.append(Point3(0, 403 * CM, 2 * height))
return microphones
def create_trajectory(n):
"""Create ground truth trajectory."""
trajectory = []
timeOfEvent = 10
# simulate emitting a sound every second while moving on straight line
for key in range(n):
trajectory.append(
Event(timeOfEvent, 245 * CM + key * 1.0, 201.5 * CM, (212 - 45) * CM))
timeOfEvent += 1
return trajectory
def simulate_one_toa(microphones, event):
"""Simulate time-of-arrival measurements for a single event."""
return [TIME_OF_ARRIVAL.measure(event, microphones[i])
for i in range(len(microphones))]
def simulate_toa(microphones, trajectory):
"""Simulate time-of-arrival measurements for an entire trajectory."""
return [simulate_one_toa(microphones, event)
for event in trajectory]
def create_graph(microphones, simulatedTOA):
"""Create factor graph."""
graph = NonlinearFactorGraph()
# Create a noise model for the TOA error
model = noiseModel_Isotropic.Sigma(1, 0.5 * MS)
K = len(microphones)
key = 0
for toa in simulatedTOA:
for i in range(K):
factor = TOAFactor(key, microphones[i], toa[i], model)
graph.push_back(factor)
key += 1
return graph
def create_initial_estimate(n):
"""Create initial estimate for n events."""
initial = Values()
zero = Event()
for key in range(n):
TOAFactor.InsertEvent(key, zero, initial)
return initial
def toa_example():
"""Run example with 4 microphones and 5 events in a straight line."""
# Create microphones
microphones = define_microphones()
K = len(microphones)
for i in range(K):
print("mic {} = {}".format(i, microphones[i]))
# Create a ground truth trajectory
n = 5
groundTruth = create_trajectory(n)
for event in groundTruth:
print(event)
# Simulate time-of-arrival measurements
simulatedTOA = simulate_toa(microphones, groundTruth)
for key in range(n):
for i in range(K):
print("z_{}{} = {} ms".format(key, i, simulatedTOA[key][i] / MS))
# create factor graph
graph = create_graph(microphones, simulatedTOA)
print(graph.at(0))
# Create initial estimate
initial_estimate = create_initial_estimate(n)
print(initial_estimate)
# Optimize using Levenberg-Marquardt optimization.
params = LevenbergMarquardtParams()
params.setAbsoluteErrorTol(1e-10)
params.setVerbosityLM("SUMMARY")
optimizer = LevenbergMarquardtOptimizer(graph, initial_estimate, params)
result = optimizer.optimize()
print("Final Result:\n", result)
if __name__ == '__main__':
toa_example()
print("Example complete")

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/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010-2020, 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 TimeOfArrivalExample.cpp
* @brief Track a moving object "Time of Arrival" measurements at 4
* microphones.
* @author Frank Dellaert
* @author Jay Chakravarty
* @date March 2020
*/
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/expressions.h>
#include <gtsam_unstable/geometry/Event.h>
#include <gtsam_unstable/slam/TOAFactor.h>
#include <boost/bind.hpp>
#include <boost/format.hpp>
#include <vector>
using namespace std;
using namespace gtsam;
// units
static const double ms = 1e-3;
static const double cm = 1e-2;
// Instantiate functor with speed of sound value
static const TimeOfArrival kTimeOfArrival(330);
/* ************************************************************************* */
// Create microphones
vector<Point3> defineMicrophones() {
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));
return microphones;
}
/* ************************************************************************* */
// Create ground truth trajectory
vector<Event> createTrajectory(int n) {
vector<Event> trajectory;
double timeOfEvent = 10;
// simulate emitting a sound every second while moving on straight line
for (size_t key = 0; key < n; key++) {
trajectory.push_back(
Event(timeOfEvent, 245 * cm + key * 1.0, 201.5 * cm, (212 - 45) * cm));
timeOfEvent += 1;
}
return trajectory;
}
/* ************************************************************************* */
// Simulate time-of-arrival measurements for a single event
vector<double> simulateTOA(const vector<Point3>& microphones,
const Event& event) {
size_t K = microphones.size();
vector<double> simulatedTOA(K);
for (size_t i = 0; i < K; i++) {
simulatedTOA[i] = kTimeOfArrival(event, microphones[i]);
}
return simulatedTOA;
}
/* ************************************************************************* */
// Simulate time-of-arrival measurements for an entire trajectory
vector<vector<double>> simulateTOA(const vector<Point3>& microphones,
const vector<Event>& trajectory) {
vector<vector<double>> simulatedTOA;
for (auto event : trajectory) {
simulatedTOA.push_back(simulateTOA(microphones, event));
}
return simulatedTOA;
}
/* ************************************************************************* */
// create factor graph
NonlinearFactorGraph createGraph(const vector<Point3>& microphones,
const vector<vector<double>>& simulatedTOA) {
NonlinearFactorGraph graph;
// Create a noise model for the TOA error
auto model = noiseModel::Isotropic::Sigma(1, 0.5 * ms);
size_t K = microphones.size();
size_t key = 0;
for (auto toa : simulatedTOA) {
for (size_t i = 0; i < K; i++) {
graph.emplace_shared<TOAFactor>(key, microphones[i], toa[i], model);
}
key += 1;
}
return graph;
}
/* ************************************************************************* */
// create initial estimate for n events
Values createInitialEstimate(int n) {
Values initial;
Event zero;
for (size_t key = 0; key < n; key++) {
initial.insert(key, zero);
}
return initial;
}
/* ************************************************************************* */
int main(int argc, char* argv[]) {
// Create microphones
auto microphones = defineMicrophones();
size_t K = microphones.size();
for (size_t i = 0; i < K; i++) {
cout << "mic" << i << " = " << microphones[i] << endl;
}
// Create a ground truth trajectory
const size_t n = 5;
auto groundTruth = createTrajectory(n);
// Simulate time-of-arrival measurements
auto simulatedTOA = simulateTOA(microphones, groundTruth);
for (size_t key = 0; key < n; key++) {
for (size_t i = 0; i < K; i++) {
cout << "z_" << key << i << " = " << simulatedTOA[key][i] / ms << " ms"
<< endl;
}
}
// Create factor graph
auto graph = createGraph(microphones, simulatedTOA);
// Create initial estimate
auto initialEstimate = createInitialEstimate(n);
initialEstimate.print("Initial Estimate:\n");
// Optimize using Levenberg-Marquardt optimization.
LevenbergMarquardtParams params;
params.setAbsoluteErrorTol(1e-10);
params.setVerbosityLM("SUMMARY");
LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, params);
Values result = optimizer.optimize();
result.print("Final Result:\n");
}
/* ************************************************************************* */

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@ -24,15 +24,16 @@ namespace gtsam {
/* ************************************************************************* */
void Event::print(const std::string& s) const {
std::cout << s << "time = " << time_ << "location = " << location_.transpose();
std::cout << s << "{'time':" << time_
<< ", 'location': " << location_.transpose() << "}";
}
/* ************************************************************************* */
bool Event::equals(const Event& other, double tol) const {
return std::abs(time_ - other.time_) < tol
&& traits<Point3>::Equals(location_, other.location_, tol);
return std::abs(time_ - other.time_) < tol &&
traits<Point3>::Equals(location_, other.location_, tol);
}
/* ************************************************************************* */
} //\ namespace gtsam
} // namespace gtsam

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@ -20,42 +20,43 @@
#pragma once
#include <gtsam/geometry/Point3.h>
#include <gtsam_unstable/dllexport.h>
#include <cmath>
#include <iosfwd>
#include <gtsam_unstable/dllexport.h>
#include <string>
namespace gtsam {
/// A space-time event
/**
* A space-time event models an event that happens at a certain 3D location, at
* a certain time. One use for it is in sound-based or UWB-ranging tracking or
* SLAM, where we have "time of arrival" measurements at a set of sensors. The
* TOA functor below provides a measurement function for those applications.
*/
class Event {
double time_; ///< Time event was generated
Point3 location_; ///< Location at time event was generated
double time_; ///< Time event was generated
Point3 location_; ///< Location at time event was generated
public:
public:
enum { dimension = 4 };
/// Default Constructor
Event() :
time_(0), location_(0,0,0) {
}
Event() : time_(0), location_(0, 0, 0) {}
/// Constructor from time and location
Event(double t, const Point3& p) :
time_(t), location_(p) {
}
Event(double t, const Point3& p) : time_(t), location_(p) {}
/// Constructor with doubles
Event(double t, double x, double y, double z) :
time_(t), location_(x, y, z) {
}
Event(double t, double x, double y, double z)
: time_(t), location_(x, y, z) {}
double time() const { return time_;}
Point3 location() const { return location_;}
double time() const { return time_; }
Point3 location() const { return location_; }
// TODO we really have to think of a better way to do linear arguments
double height(OptionalJacobian<1,4> H = boost::none) const {
static const Matrix14 JacobianZ = (Matrix14() << 0,0,0,1).finished();
// TODO(frank) we really have to think of a better way to do linear arguments
double height(OptionalJacobian<1, 4> H = boost::none) const {
static const Matrix14 JacobianZ = (Matrix14() << 0, 0, 0, 1).finished();
if (H) *H = JacobianZ;
return location_.z();
}
@ -64,7 +65,8 @@ public:
GTSAM_UNSTABLE_EXPORT void print(const std::string& s = "") const;
/** equals with an tolerance */
GTSAM_UNSTABLE_EXPORT bool equals(const Event& other, double tol = 1e-9) const;
GTSAM_UNSTABLE_EXPORT bool equals(const Event& other,
double tol = 1e-9) const;
/// Updates a with tangent space delta
inline Event retract(const Vector4& v) const {
@ -73,28 +75,44 @@ public:
/// Returns inverse retraction
inline Vector4 localCoordinates(const Event& q) const {
return Vector4::Zero(); // TODO
}
/// Time of arrival to given microphone
double toa(const Point3& microphone, //
OptionalJacobian<1, 4> H1 = boost::none, //
OptionalJacobian<1, 3> H2 = boost::none) const {
static const double Speed = 330;
Matrix13 D1, D2;
double distance = gtsam::distance3(location_, microphone, D1, D2);
if (H1)
// derivative of toa with respect to event
*H1 << 1.0, D1 / Speed;
if (H2)
// derivative of toa with respect to microphone location
*H2 << D2 / Speed;
return time_ + distance / Speed;
return Vector4::Zero(); // TODO(frank) implement!
}
};
// Define GTSAM traits
template<>
template <>
struct traits<Event> : internal::Manifold<Event> {};
} //\ namespace gtsam
/// Time of arrival to given sensor
class TimeOfArrival {
const double speed_; ///< signal speed
public:
typedef double result_type;
/// Constructor with optional speed of signal, in m/sec
explicit TimeOfArrival(double speed = 330) : speed_(speed) {}
/// Calculate time of arrival
double measure(const Event& event, const Point3& sensor) const {
double distance = gtsam::distance3(event.location(), sensor);
return event.time() + distance / speed_;
}
/// Calculate time of arrival, with derivatives
double operator()(const Event& event, const Point3& sensor, //
OptionalJacobian<1, 4> H1 = boost::none, //
OptionalJacobian<1, 3> H2 = boost::none) const {
Matrix13 D1, D2;
double distance = gtsam::distance3(event.location(), sensor, D1, D2);
if (H1)
// derivative of toa with respect to event
*H1 << 1.0, D1 / speed_;
if (H2)
// derivative of toa with respect to sensor location
*H2 << D2 / speed_;
return event.time() + distance / speed_;
}
};
} // namespace gtsam

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@ -17,10 +17,12 @@
* @date December 2014
*/
#include <gtsam_unstable/geometry/Event.h>
#include <gtsam/base/numericalDerivative.h>
#include <gtsam/nonlinear/Expression.h>
#include <gtsam_unstable/geometry/Event.h>
#include <CppUnitLite/TestHarness.h>
#include <boost/bind.hpp>
using namespace std;
@ -30,56 +32,59 @@ using namespace gtsam;
static const double ms = 1e-3;
static const double cm = 1e-2;
typedef Eigen::Matrix<double, 1, 1> Vector1;
static SharedNoiseModel model(noiseModel::Isotropic::Sigma(1,0.5*ms));
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);
static const Point3 microphoneAt0(0, 0, 0);
static const double kSpeedOfSound = 340;
static const TimeOfArrival kToa(kSpeedOfSound);
//*****************************************************************************
TEST( Event, Constructor ) {
TEST(Event, Constructor) {
const double t = 0;
Event actual(t, 201.5 * cm, 201.5 * cm, (212 - 45) * cm);
}
//*****************************************************************************
TEST( Event, Toa1 ) {
TEST(Event, Toa1) {
Event event(0, 1, 0, 0);
double expected = 1. / 330;
EXPECT_DOUBLES_EQUAL(expected, event.toa(microphoneAt0), 1e-9);
double expected = 1. / kSpeedOfSound;
EXPECT_DOUBLES_EQUAL(expected, kToa(event, microphoneAt0), 1e-9);
}
//*****************************************************************************
TEST( Event, Toa2 ) {
double expectedTOA = timeOfEvent + 1. / 330;
EXPECT_DOUBLES_EQUAL(expectedTOA, exampleEvent.toa(microphoneAt0), 1e-9);
TEST(Event, Toa2) {
double expectedTOA = timeOfEvent + 1. / kSpeedOfSound;
EXPECT_DOUBLES_EQUAL(expectedTOA, kToa(exampleEvent, microphoneAt0), 1e-9);
}
//*************************************************************************
TEST (Event, Derivatives) {
TEST(Event, Derivatives) {
Matrix14 actualH1;
Matrix13 actualH2;
exampleEvent.toa(microphoneAt0, actualH1, actualH2);
kToa(exampleEvent, microphoneAt0, actualH1, actualH2);
Matrix expectedH1 = numericalDerivative11<double, Event>(
boost::bind(&Event::toa, _1, microphoneAt0, boost::none, boost::none),
boost::bind(kToa, _1, microphoneAt0, boost::none, boost::none),
exampleEvent);
EXPECT(assert_equal(expectedH1, actualH1, 1e-8));
Matrix expectedH2 = numericalDerivative11<double, Point3>(
boost::bind(&Event::toa, exampleEvent, _1, boost::none, boost::none),
boost::bind(kToa, exampleEvent, _1, boost::none, boost::none),
microphoneAt0);
EXPECT(assert_equal(expectedH2, actualH2, 1e-8));
}
//*****************************************************************************
TEST( Event, Expression ) {
TEST(Event, Expression) {
Key key = 12;
Expression<Event> event_(key);
Expression<Point3> knownMicrophone_(microphoneAt0); // constant expression
Expression<double> expression(&Event::toa, event_, knownMicrophone_);
Expression<Point3> knownMicrophone_(microphoneAt0); // constant expression
Expression<double> expression(kToa, event_, knownMicrophone_);
Values values;
values.insert(key, exampleEvent);
double expectedTOA = timeOfEvent + 1. / 330;
double expectedTOA = timeOfEvent + 1. / kSpeedOfSound;
EXPECT_DOUBLES_EQUAL(expectedTOA, expression.value(values), 1e-9);
}
@ -97,4 +102,3 @@ int main() {
return TestRegistry::runAllTests(tr);
}
//*****************************************************************************

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@ -377,6 +377,30 @@ virtual class RangeFactor : gtsam::NoiseModelFactor {
typedef gtsam::RangeFactor<gtsam::PoseRTV, gtsam::PoseRTV> RangeFactorRTV;
#include <gtsam_unstable/geometry/Event.h>
class Event {
Event();
Event(double t, const gtsam::Point3& p);
Event(double t, double x, double y, double z);
double time() const;
gtsam::Point3 location() const;
double height() const;
void print(string s) const;
};
class TimeOfArrival {
TimeOfArrival();
TimeOfArrival(double speed);
double measure(const gtsam::Event& event, const gtsam::Point3& sensor) const;
};
#include <gtsam_unstable/slam/TOAFactor.h>
virtual class TOAFactor : gtsam::NonlinearFactor {
// For now, because of overload issues, we only expose constructor with known sensor coordinates:
TOAFactor(size_t key1, gtsam::Point3 sensor, double measured,
const gtsam::noiseModel::Base* noiseModel);
static void InsertEvent(size_t key, const gtsam::Event& event, gtsam::Values* values);
};
#include <gtsam/nonlinear/NonlinearEquality.h>
template<T = {gtsam::PoseRTV}>

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@ -17,33 +17,51 @@
* @date December 2014
*/
#pragma once
#include <gtsam/nonlinear/ExpressionFactor.h>
#include <gtsam_unstable/geometry/Event.h>
namespace gtsam {
/// A "Time of Arrival" factor - so little code seems hardly worth it :-)
class TOAFactor: public ExpressionFactor<double> {
class TOAFactor : public ExpressionFactor<double> {
typedef Expression<double> Double_;
public:
public:
/**
* Constructor
* @param some expression yielding an event
* @param microphone_ expression yielding a microphone location
* @param toaMeasurement time of arrival at microphone
* Most general constructor with two expressions
* @param eventExpression expression yielding an event
* @param sensorExpression expression yielding a sensor location
* @param toaMeasurement time of arrival at sensor
* @param model noise model
* @param speed optional speed of signal, in m/sec
*/
TOAFactor(const Expression<Event>& eventExpression,
const Expression<Point3>& microphone_, double toaMeasurement,
const SharedNoiseModel& model) :
ExpressionFactor<double>(model, toaMeasurement,
Double_(&Event::toa, eventExpression, microphone_)) {
}
const Expression<Point3>& sensorExpression, double toaMeasurement,
const SharedNoiseModel& model, double speed = 330)
: ExpressionFactor<double>(
model, toaMeasurement,
Double_(TimeOfArrival(speed), eventExpression, sensorExpression)) {}
/**
* Constructor with fixed sensor
* @param eventExpression expression yielding an event
* @param sensor a known sensor location
* @param toaMeasurement time of arrival at sensor
* @param model noise model
* @param toa optional time of arrival functor
*/
TOAFactor(const Expression<Event>& eventExpression, const Point3& sensor,
double toaMeasurement, const SharedNoiseModel& model,
double speed = 330)
: TOAFactor(eventExpression, Expression<Point3>(sensor), toaMeasurement,
model, speed) {}
static void InsertEvent(Key key, const Event& event,
boost::shared_ptr<Values> values) {
values->insert(key, event);
}
};
} //\ namespace gtsam
} // namespace gtsam

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@ -17,15 +17,16 @@
* @date December 2014
*/
#include <gtsam_unstable/geometry/Event.h>
#include <gtsam/nonlinear/ExpressionFactorGraph.h>
#include <gtsam/nonlinear/expressions.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/base/numericalDerivative.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/expressions.h>
#include <gtsam_unstable/geometry/Event.h>
#include <gtsam_unstable/slam/TOAFactor.h>
#include <CppUnitLite/TestHarness.h>
#include <boost/format.hpp>
#include <boost/bind.hpp>
#include <boost/format.hpp>
using namespace std;
using namespace gtsam;
@ -43,83 +44,59 @@ 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);
static const Point3 sensorAt0(0, 0, 0);
//*****************************************************************************
TEST( TOAFactor, NewWay ) {
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);
TOAFactor factor(key, sensorAt0, measurement, model);
}
//*****************************************************************************
TEST( TOAFactor, WholeEnchilada ) {
static const bool verbose = false;
// Create microphones
TEST(TOAFactor, WholeEnchilada) {
// Create sensors
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));
vector<Point3> sensors;
sensors.push_back(Point3(0, 0, height));
sensors.push_back(Point3(403 * cm, 0, height));
sensors.push_back(Point3(403 * cm, 403 * cm, height));
sensors.push_back(Point3(0, 403 * cm, 2 * height));
EXPECT_LONGS_EQUAL(4, sensors.size());
// sensors.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();
size_t K = sensors.size();
vector<double> simulatedTOA(K);
TimeOfArrival toa;
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;
}
simulatedTOA[i] = toa(groundTruthEvent, sensors[i]);
}
// Now, estimate using non-linear optimization
ExpressionFactorGraph graph;
NonlinearFactorGraph 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);
graph.emplace_shared<TOAFactor>(key, sensors[i], 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);
// 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));
}
@ -129,4 +106,3 @@ int main() {
return TestRegistry::runAllTests(tr);
}
//*****************************************************************************

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wrap/python/pybind11 Submodule

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Subproject commit b3bf248eec9cad8260753c982e1ae6cb72fff470