gtsam/gtsam/navigation/tests/testAHRSFactor.cpp

514 lines
18 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 testAHRSFactor.cpp
* @brief Unit test for AHRSFactor
* @author Krunal Chande
* @author Luca Carlone
* @author Frank Dellaert
* @author Varun Agrawal
*/
#include <gtsam/navigation/AHRSFactor.h>
#include <gtsam/inference/Symbol.h>
#include <gtsam/base/TestableAssertions.h>
#include <gtsam/base/numericalDerivative.h>
#include <gtsam/base/debug.h>
#include <CppUnitLite/TestHarness.h>
#include <list>
using namespace std::placeholders;
using namespace std;
using namespace gtsam;
// Convenience for named keys
using symbol_shorthand::X;
using symbol_shorthand::V;
using symbol_shorthand::B;
Vector3 kZeroOmegaCoriolis(0,0,0);
// Define covariance matrices
double accNoiseVar = 0.01;
const Matrix3 kMeasuredAccCovariance = accNoiseVar * I_3x3;
//******************************************************************************
namespace {
Vector callEvaluateError(const AHRSFactor& factor, const Rot3 rot_i,
const Rot3 rot_j, const Vector3& bias) {
return factor.evaluateError(rot_i, rot_j, bias);
}
Rot3 evaluateRotationError(const AHRSFactor& factor, const Rot3 rot_i,
const Rot3 rot_j, const Vector3& bias) {
return Rot3::Expmap(factor.evaluateError(rot_i, rot_j, bias).tail(3));
}
PreintegratedAhrsMeasurements evaluatePreintegratedMeasurements(
const Vector3& bias, const list<Vector3>& measuredOmegas,
const list<double>& deltaTs,
const Vector3& initialRotationRate = Vector3::Zero()) {
PreintegratedAhrsMeasurements result(bias, I_3x3);
list<Vector3>::const_iterator itOmega = measuredOmegas.begin();
list<double>::const_iterator itDeltaT = deltaTs.begin();
for (; itOmega != measuredOmegas.end(); ++itOmega, ++itDeltaT) {
result.integrateMeasurement(*itOmega, *itDeltaT);
}
return result;
}
Rot3 evaluatePreintegratedMeasurementsRotation(
const Vector3& bias, const list<Vector3>& measuredOmegas,
const list<double>& deltaTs,
const Vector3& initialRotationRate = Vector3::Zero()) {
return Rot3(
evaluatePreintegratedMeasurements(bias, measuredOmegas, deltaTs,
initialRotationRate).deltaRij());
}
Rot3 evaluateRotation(const Vector3 measuredOmega, const Vector3 biasOmega,
const double deltaT) {
return Rot3::Expmap((measuredOmega - biasOmega) * deltaT);
}
Vector3 evaluateLogRotation(const Vector3 thetahat, const Vector3 deltatheta) {
return Rot3::Logmap(Rot3::Expmap(thetahat).compose(Rot3::Expmap(deltatheta)));
}
}
//******************************************************************************
TEST( AHRSFactor, PreintegratedAhrsMeasurements ) {
// Linearization point
Vector3 bias(0,0,0); ///< Current estimate of angular rate bias
// Measurements
Vector3 measuredOmega(M_PI / 100.0, 0.0, 0.0);
double deltaT = 0.5;
// Expected preintegrated values
Rot3 expectedDeltaR1 = Rot3::RzRyRx(0.5 * M_PI / 100.0, 0.0, 0.0);
double expectedDeltaT1(0.5);
// Actual preintegrated values
PreintegratedAhrsMeasurements actual1(bias, Z_3x3);
actual1.integrateMeasurement(measuredOmega, deltaT);
EXPECT(assert_equal(expectedDeltaR1, Rot3(actual1.deltaRij()), 1e-6));
DOUBLES_EQUAL(expectedDeltaT1, actual1.deltaTij(), 1e-6);
// Integrate again
Rot3 expectedDeltaR2 = Rot3::RzRyRx(2.0 * 0.5 * M_PI / 100.0, 0.0, 0.0);
double expectedDeltaT2(1);
// Actual preintegrated values
PreintegratedAhrsMeasurements actual2 = actual1;
actual2.integrateMeasurement(measuredOmega, deltaT);
EXPECT(assert_equal(expectedDeltaR2, Rot3(actual2.deltaRij()), 1e-6));
DOUBLES_EQUAL(expectedDeltaT2, actual2.deltaTij(), 1e-6);
}
//******************************************************************************
TEST( AHRSFactor, PreintegratedAhrsMeasurementsConstructor ) {
Matrix3 gyroscopeCovariance = Matrix3::Ones()*0.4;
Vector3 omegaCoriolis(0.1, 0.5, 0.9);
PreintegratedRotationParams params(gyroscopeCovariance, omegaCoriolis);
Vector3 bias(1.0,2.0,3.0); ///< Current estimate of angular rate bias
Rot3 deltaRij(Rot3::RzRyRx(M_PI / 12.0, M_PI / 6.0, M_PI / 4.0));
double deltaTij = 0.02;
Matrix3 delRdelBiasOmega = Matrix3::Ones()*0.5;
Matrix3 preintMeasCov = Matrix3::Ones()*0.2;
PreintegratedAhrsMeasurements actualPim(
boost::make_shared<PreintegratedRotationParams>(params),
bias,
deltaTij,
deltaRij,
delRdelBiasOmega,
preintMeasCov);
EXPECT(assert_equal(gyroscopeCovariance,
actualPim.p().getGyroscopeCovariance(), 1e-6));
EXPECT(assert_equal(omegaCoriolis,
actualPim.p().getOmegaCoriolis().get(), 1e-6));
EXPECT(assert_equal(bias, actualPim.biasHat(), 1e-6));
DOUBLES_EQUAL(deltaTij, actualPim.deltaTij(), 1e-6);
EXPECT(assert_equal(deltaRij, Rot3(actualPim.deltaRij()), 1e-6));
EXPECT(assert_equal(delRdelBiasOmega, actualPim.delRdelBiasOmega(), 1e-6));
EXPECT(assert_equal(preintMeasCov, actualPim.preintMeasCov(), 1e-6));
}
/* ************************************************************************* */
TEST(AHRSFactor, Error) {
// Linearization point
Vector3 bias(0.,0.,0.); // Bias
Rot3 x1(Rot3::RzRyRx(M_PI / 12.0, M_PI / 6.0, M_PI / 4.0));
Rot3 x2(Rot3::RzRyRx(M_PI / 12.0 + M_PI / 100.0, M_PI / 6.0, M_PI / 4.0));
// Measurements
Vector3 measuredOmega;
measuredOmega << M_PI / 100, 0, 0;
double deltaT = 1.0;
PreintegratedAhrsMeasurements pim(bias, Z_3x3);
pim.integrateMeasurement(measuredOmega, deltaT);
// Create factor
AHRSFactor factor(X(1), X(2), B(1), pim, kZeroOmegaCoriolis, boost::none);
Vector3 errorActual = factor.evaluateError(x1, x2, bias);
// Expected error
Vector3 errorExpected(3);
errorExpected << 0, 0, 0;
EXPECT(assert_equal(Vector(errorExpected), Vector(errorActual), 1e-6));
// Expected Jacobians
Matrix H1e = numericalDerivative11<Vector3, Rot3>(
std::bind(&callEvaluateError, factor, std::placeholders::_1, x2, bias), x1);
Matrix H2e = numericalDerivative11<Vector3, Rot3>(
std::bind(&callEvaluateError, factor, x1, std::placeholders::_1, bias), x2);
Matrix H3e = numericalDerivative11<Vector3, Vector3>(
std::bind(&callEvaluateError, factor, x1, x2, std::placeholders::_1), bias);
// Check rotation Jacobians
Matrix RH1e = numericalDerivative11<Rot3, Rot3>(
std::bind(&evaluateRotationError, factor, std::placeholders::_1, x2, bias), x1);
Matrix RH2e = numericalDerivative11<Rot3, Rot3>(
std::bind(&evaluateRotationError, factor, x1, std::placeholders::_1, bias), x2);
// Actual Jacobians
Matrix H1a, H2a, H3a;
(void) factor.evaluateError(x1, x2, bias, H1a, H2a, H3a);
// rotations
EXPECT(assert_equal(RH1e, H1a, 1e-5));
// 1e-5 needs to be added only when using quaternions for rotations
EXPECT(assert_equal(H2e, H2a, 1e-5));
// rotations
EXPECT(assert_equal(RH2e, H2a, 1e-5));
// 1e-5 needs to be added only when using quaternions for rotations
EXPECT(assert_equal(H3e, H3a, 1e-5));
// 1e-5 needs to be added only when using quaternions for rotations
}
/* ************************************************************************* */
TEST(AHRSFactor, ErrorWithBiases) {
// Linearization point
Vector3 bias(0, 0, 0.3);
Rot3 x1(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0)));
Rot3 x2(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0 + M_PI / 10.0)));
// Measurements
Vector3 measuredOmega;
measuredOmega << 0, 0, M_PI / 10.0 + 0.3;
double deltaT = 1.0;
PreintegratedAhrsMeasurements pim(Vector3(0,0,0),
Z_3x3);
pim.integrateMeasurement(measuredOmega, deltaT);
// Create factor
AHRSFactor factor(X(1), X(2), B(1), pim, kZeroOmegaCoriolis);
Vector errorActual = factor.evaluateError(x1, x2, bias);
// Expected error
Vector errorExpected(3);
errorExpected << 0, 0, 0;
EXPECT(assert_equal(errorExpected, errorActual, 1e-6));
// Expected Jacobians
Matrix H1e = numericalDerivative11<Vector, Rot3>(
std::bind(&callEvaluateError, factor, std::placeholders::_1, x2, bias), x1);
Matrix H2e = numericalDerivative11<Vector, Rot3>(
std::bind(&callEvaluateError, factor, x1, std::placeholders::_1, bias), x2);
Matrix H3e = numericalDerivative11<Vector, Vector3>(
std::bind(&callEvaluateError, factor, x1, x2, std::placeholders::_1), bias);
// Check rotation Jacobians
Matrix RH1e = numericalDerivative11<Rot3, Rot3>(
std::bind(&evaluateRotationError, factor, std::placeholders::_1, x2, bias), x1);
Matrix RH2e = numericalDerivative11<Rot3, Rot3>(
std::bind(&evaluateRotationError, factor, x1, std::placeholders::_1, bias), x2);
Matrix RH3e = numericalDerivative11<Rot3, Vector3>(
std::bind(&evaluateRotationError, factor, x1, x2, std::placeholders::_1), bias);
// Actual Jacobians
Matrix H1a, H2a, H3a;
(void) factor.evaluateError(x1, x2, bias, H1a, H2a, H3a);
EXPECT(assert_equal(H1e, H1a));
EXPECT(assert_equal(H2e, H2a));
EXPECT(assert_equal(H3e, H3a));
}
//******************************************************************************
TEST( AHRSFactor, PartialDerivativeExpmap ) {
// Linearization point
Vector3 biasOmega(0,0,0);
// Measurements
Vector3 measuredOmega;
measuredOmega << 0.1, 0, 0;
double deltaT = 0.5;
// Compute numerical derivatives
Matrix expectedDelRdelBiasOmega = numericalDerivative11<Rot3, Vector3>(
std::bind(&evaluateRotation, measuredOmega, std::placeholders::_1, deltaT), biasOmega);
const Matrix3 Jr = Rot3::ExpmapDerivative(
(measuredOmega - biasOmega) * deltaT);
Matrix3 actualdelRdelBiasOmega = -Jr * deltaT; // the delta bias appears with the minus sign
// Compare Jacobians
EXPECT(assert_equal(expectedDelRdelBiasOmega, actualdelRdelBiasOmega, 1e-3));
// 1e-3 needs to be added only when using quaternions for rotations
}
//******************************************************************************
TEST( AHRSFactor, PartialDerivativeLogmap ) {
// Linearization point
Vector3 thetahat;
thetahat << 0.1, 0.1, 0; ///< Current estimate of rotation rate bias
// Measurements
Vector3 deltatheta;
deltatheta << 0, 0, 0;
// Compute numerical derivatives
Matrix expectedDelFdeltheta = numericalDerivative11<Vector3, Vector3>(
std::bind(&evaluateLogRotation, thetahat, std::placeholders::_1), deltatheta);
const Vector3 x = thetahat; // parametrization of so(3)
const Matrix3 X = skewSymmetric(x); // element of Lie algebra so(3): X = x^
double normx = x.norm();
const Matrix3 actualDelFdeltheta = I_3x3 + 0.5 * X
+ (1 / (normx * normx) - (1 + cos(normx)) / (2 * normx * sin(normx))) * X
* X;
// Compare Jacobians
EXPECT(assert_equal(expectedDelFdeltheta, actualDelFdeltheta));
}
//******************************************************************************
TEST( AHRSFactor, fistOrderExponential ) {
// Linearization point
Vector3 biasOmega(0,0,0);
// Measurements
Vector3 measuredOmega;
measuredOmega << 0.1, 0, 0;
double deltaT = 1.0;
// change w.r.t. linearization point
double alpha = 0.0;
Vector3 deltabiasOmega;
deltabiasOmega << alpha, alpha, alpha;
const Matrix3 Jr = Rot3::ExpmapDerivative(
(measuredOmega - biasOmega) * deltaT);
Matrix3 delRdelBiasOmega = -Jr * deltaT; // the delta bias appears with the minus sign
const Matrix expectedRot = Rot3::Expmap(
(measuredOmega - biasOmega - deltabiasOmega) * deltaT).matrix();
const Matrix3 hatRot =
Rot3::Expmap((measuredOmega - biasOmega) * deltaT).matrix();
const Matrix3 actualRot = hatRot
* Rot3::Expmap(delRdelBiasOmega * deltabiasOmega).matrix();
// Compare Jacobians
EXPECT(assert_equal(expectedRot, actualRot));
}
//******************************************************************************
TEST( AHRSFactor, FirstOrderPreIntegratedMeasurements ) {
// Linearization point
Vector3 bias = Vector3::Zero(); ///< Current estimate of rotation rate bias
Pose3 body_P_sensor(Rot3::Expmap(Vector3(0, 0.1, 0.1)), Point3(1, 0, 1));
// Measurements
list<Vector3> measuredOmegas;
list<double> deltaTs;
measuredOmegas.push_back(Vector3(M_PI / 100.0, 0.0, 0.0));
deltaTs.push_back(0.01);
measuredOmegas.push_back(Vector3(M_PI / 100.0, 0.0, 0.0));
deltaTs.push_back(0.01);
for (int i = 1; i < 100; i++) {
measuredOmegas.push_back(
Vector3(M_PI / 100.0, M_PI / 300.0, 2 * M_PI / 100.0));
deltaTs.push_back(0.01);
}
// Actual preintegrated values
PreintegratedAhrsMeasurements preintegrated =
evaluatePreintegratedMeasurements(bias, measuredOmegas, deltaTs,
Vector3(M_PI / 100.0, 0.0, 0.0));
// Compute numerical derivatives
Matrix expectedDelRdelBias =
numericalDerivative11<Rot3, Vector3>(
std::bind(&evaluatePreintegratedMeasurementsRotation, std::placeholders::_1,
measuredOmegas, deltaTs, Vector3(M_PI / 100.0, 0.0, 0.0)), bias);
Matrix expectedDelRdelBiasOmega = expectedDelRdelBias.rightCols(3);
// Compare Jacobians
EXPECT(
assert_equal(expectedDelRdelBiasOmega, preintegrated.delRdelBiasOmega(), 1e-3));
// 1e-3 needs to be added only when using quaternions for rotations
}
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
//******************************************************************************
TEST( AHRSFactor, ErrorWithBiasesAndSensorBodyDisplacement ) {
Vector3 bias(0, 0, 0.3);
Rot3 x1(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0)));
Rot3 x2(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0 + M_PI / 10.0)));
// Measurements
Vector3 omegaCoriolis;
omegaCoriolis << 0, 0.1, 0.1;
Vector3 measuredOmega;
measuredOmega << 0, 0, M_PI / 10.0 + 0.3;
double deltaT = 1.0;
const Pose3 body_P_sensor(Rot3::Expmap(Vector3(0, 0.10, 0.10)),
Point3(1, 0, 0));
PreintegratedAhrsMeasurements pim(Vector3::Zero(), kMeasuredAccCovariance);
pim.integrateMeasurement(measuredOmega, deltaT);
// Check preintegrated covariance
EXPECT(assert_equal(kMeasuredAccCovariance, pim.preintMeasCov()));
// Create factor
AHRSFactor factor(X(1), X(2), B(1), pim, omegaCoriolis);
// Expected Jacobians
Matrix H1e = numericalDerivative11<Vector, Rot3>(
std::bind(&callEvaluateError, factor, std::placeholders::_1, x2, bias), x1);
Matrix H2e = numericalDerivative11<Vector, Rot3>(
std::bind(&callEvaluateError, factor, x1, std::placeholders::_1, bias), x2);
Matrix H3e = numericalDerivative11<Vector, Vector3>(
std::bind(&callEvaluateError, factor, x1, x2, std::placeholders::_1), bias);
// Check rotation Jacobians
Matrix RH1e = numericalDerivative11<Rot3, Rot3>(
std::bind(&evaluateRotationError, factor, std::placeholders::_1, x2, bias), x1);
Matrix RH2e = numericalDerivative11<Rot3, Rot3>(
std::bind(&evaluateRotationError, factor, x1, std::placeholders::_1, bias), x2);
Matrix RH3e = numericalDerivative11<Rot3, Vector3>(
std::bind(&evaluateRotationError, factor, x1, x2, std::placeholders::_1), bias);
// Actual Jacobians
Matrix H1a, H2a, H3a;
(void) factor.evaluateError(x1, x2, bias, H1a, H2a, H3a);
EXPECT(assert_equal(H1e, H1a));
EXPECT(assert_equal(H2e, H2a));
EXPECT(assert_equal(H3e, H3a));
}
//******************************************************************************
TEST (AHRSFactor, predictTest) {
Vector3 bias(0,0,0);
// Measurements
Vector3 measuredOmega;
measuredOmega << 0, 0, M_PI / 10.0;
double deltaT = 0.2;
PreintegratedAhrsMeasurements pim(bias, kMeasuredAccCovariance);
for (int i = 0; i < 1000; ++i) {
pim.integrateMeasurement(measuredOmega, deltaT);
}
// Check preintegrated covariance
Matrix expectedMeasCov(3,3);
expectedMeasCov = 200*kMeasuredAccCovariance;
EXPECT(assert_equal(expectedMeasCov, pim.preintMeasCov()));
AHRSFactor factor(X(1), X(2), B(1), pim, kZeroOmegaCoriolis);
// Predict
Rot3 x;
Rot3 expectedRot = Rot3::Ypr(20*M_PI, 0, 0);
Rot3 actualRot = factor.predict(x, bias, pim, kZeroOmegaCoriolis);
EXPECT(assert_equal(expectedRot, actualRot, 1e-6));
// PreintegratedAhrsMeasurements::predict
Matrix expectedH = numericalDerivative11<Vector3, Vector3>(
std::bind(&PreintegratedAhrsMeasurements::predict,
&pim, std::placeholders::_1, boost::none), bias);
// Actual Jacobians
Matrix H;
(void) pim.predict(bias,H);
EXPECT(assert_equal(expectedH, H, 1e-8));
}
//******************************************************************************
#include <gtsam/linear/GaussianFactorGraph.h>
#include <gtsam/nonlinear/Marginals.h>
TEST (AHRSFactor, graphTest) {
// linearization point
Rot3 x1(Rot3::RzRyRx(0, 0, 0));
Rot3 x2(Rot3::RzRyRx(0, M_PI / 4, 0));
Vector3 bias(0,0,0);
// PreIntegrator
Vector3 biasHat(0, 0, 0);
PreintegratedAhrsMeasurements pim(biasHat, kMeasuredAccCovariance);
// Pre-integrate measurements
Vector3 measuredOmega(0, M_PI / 20, 0);
double deltaT = 1;
// Create Factor
noiseModel::Base::shared_ptr model = //
noiseModel::Gaussian::Covariance(pim.preintMeasCov());
NonlinearFactorGraph graph;
Values values;
for (size_t i = 0; i < 5; ++i) {
pim.integrateMeasurement(measuredOmega, deltaT);
}
// pim.print("Pre integrated measurementes");
AHRSFactor factor(X(1), X(2), B(1), pim, kZeroOmegaCoriolis);
values.insert(X(1), x1);
values.insert(X(2), x2);
values.insert(B(1), bias);
graph.push_back(factor);
LevenbergMarquardtOptimizer optimizer(graph, values);
Values result = optimizer.optimize();
Rot3 expectedRot(Rot3::RzRyRx(0, M_PI / 4, 0));
EXPECT(assert_equal(expectedRot, result.at<Rot3>(X(2))));
}
//******************************************************************************
int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
//******************************************************************************