Cleaned up tests
Frank Dellaert
parent
e81b38114c
commit
c18191d98d
|
|
@ -18,12 +18,17 @@
|
|||
* @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 <gtsam/base/TestableAssertions.h>
|
||||
#include <gtsam/base/debug.h>
|
||||
#include <gtsam/base/numericalDerivative.h>
|
||||
#include <gtsam/inference/Symbol.h>
|
||||
#include <gtsam/linear/GaussianFactorGraph.h>
|
||||
#include <gtsam/navigation/AHRSFactor.h>
|
||||
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
|
||||
#include <gtsam/nonlinear/Marginals.h>
|
||||
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
|
||||
#include <gtsam/nonlinear/factorTesting.h>
|
||||
|
||||
#include <list>
|
||||
|
||||
|
|
@ -32,33 +37,21 @@ using namespace std;
|
|||
using namespace gtsam;
|
||||
|
||||
// Convenience for named keys
|
||||
using symbol_shorthand::X;
|
||||
using symbol_shorthand::V;
|
||||
using symbol_shorthand::B;
|
||||
using symbol_shorthand::X;
|
||||
|
||||
Vector3 kZeroOmegaCoriolis(0,0,0);
|
||||
Vector3 kZeroOmegaCoriolis(0, 0, 0);
|
||||
|
||||
// Define covariance matrices
|
||||
double accNoiseVar = 0.01;
|
||||
const Matrix3 kMeasuredAccCovariance = accNoiseVar * I_3x3;
|
||||
double gyroNoiseVar = 0.01;
|
||||
const Matrix3 kMeasuredOmegaCovariance = gyroNoiseVar * 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);
|
||||
PreintegratedAhrsMeasurements integrateMeasurements(
|
||||
const Vector3& biasHat, const list<Vector3>& measuredOmegas,
|
||||
const list<double>& deltaTs) {
|
||||
PreintegratedAhrsMeasurements result(biasHat, I_3x3);
|
||||
|
||||
list<Vector3>::const_iterator itOmega = measuredOmegas.begin();
|
||||
list<double>::const_iterator itDeltaT = deltaTs.begin();
|
||||
|
|
@ -68,79 +61,59 @@ PreintegratedAhrsMeasurements evaluatePreintegratedMeasurements(
|
|||
|
||||
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)));
|
||||
}
|
||||
}
|
||||
} // namespace
|
||||
|
||||
//******************************************************************************
|
||||
TEST( AHRSFactor, PreintegratedAhrsMeasurements ) {
|
||||
TEST(AHRSFactor, PreintegratedAhrsMeasurements) {
|
||||
// Linearization point
|
||||
Vector3 bias(0,0,0); ///< Current estimate of angular rate bias
|
||||
Vector3 biasHat(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);
|
||||
Rot3 expectedDeltaR1 = Rot3::Roll(0.5 * M_PI / 100.0);
|
||||
|
||||
// Actual preintegrated values
|
||||
PreintegratedAhrsMeasurements actual1(bias, Z_3x3);
|
||||
PreintegratedAhrsMeasurements actual1(biasHat, kMeasuredOmegaCovariance);
|
||||
actual1.integrateMeasurement(measuredOmega, deltaT);
|
||||
|
||||
EXPECT(assert_equal(expectedDeltaR1, Rot3(actual1.deltaRij()), 1e-6));
|
||||
DOUBLES_EQUAL(expectedDeltaT1, actual1.deltaTij(), 1e-6);
|
||||
DOUBLES_EQUAL(deltaT, actual1.deltaTij(), 1e-6);
|
||||
|
||||
// Check the covariance
|
||||
Matrix3 expectedMeasCov = kMeasuredOmegaCovariance * deltaT;
|
||||
EXPECT(assert_equal(expectedMeasCov, actual1.preintMeasCov(), 1e-6));
|
||||
|
||||
// Integrate again
|
||||
Rot3 expectedDeltaR2 = Rot3::RzRyRx(2.0 * 0.5 * M_PI / 100.0, 0.0, 0.0);
|
||||
double expectedDeltaT2(1);
|
||||
Rot3 expectedDeltaR2 = Rot3::Roll(2.0 * 0.5 * M_PI / 100.0);
|
||||
|
||||
// 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);
|
||||
DOUBLES_EQUAL(deltaT * 2, actual2.deltaTij(), 1e-6);
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST( AHRSFactor, PreintegratedAhrsMeasurementsConstructor ) {
|
||||
Matrix3 gyroscopeCovariance = Matrix3::Ones()*0.4;
|
||||
TEST(AHRSFactor, PreintegratedAhrsMeasurementsConstructor) {
|
||||
Matrix3 gyroscopeCovariance = I_3x3 * 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
|
||||
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;
|
||||
Matrix3 delRdelBiasOmega = I_3x3 * 0.5;
|
||||
Matrix3 preintMeasCov = I_3x3 * 0.2;
|
||||
PreintegratedAhrsMeasurements actualPim(
|
||||
std::make_shared<PreintegratedRotationParams>(params),
|
||||
bias,
|
||||
deltaTij,
|
||||
deltaRij,
|
||||
delRdelBiasOmega,
|
||||
preintMeasCov);
|
||||
std::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()), 1e-6));
|
||||
actualPim.p().getGyroscopeCovariance(), 1e-6));
|
||||
EXPECT(
|
||||
assert_equal(omegaCoriolis, *(actualPim.p().getOmegaCoriolis()), 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));
|
||||
|
|
@ -151,198 +124,148 @@ TEST( AHRSFactor, PreintegratedAhrsMeasurementsConstructor ) {
|
|||
/* ************************************************************************* */
|
||||
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));
|
||||
Vector3 bias(0., 0., 0.); // Bias
|
||||
Rot3 Ri(Rot3::RzRyRx(M_PI / 12.0, M_PI / 6.0, M_PI / 4.0));
|
||||
Rot3 Rj(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;
|
||||
Vector3 measuredOmega(M_PI / 100, 0, 0);
|
||||
double deltaT = 1.0;
|
||||
PreintegratedAhrsMeasurements pim(bias, Z_3x3);
|
||||
PreintegratedAhrsMeasurements pim(bias, kMeasuredOmegaCovariance);
|
||||
pim.integrateMeasurement(measuredOmega, deltaT);
|
||||
|
||||
// Create factor
|
||||
AHRSFactor factor(X(1), X(2), B(1), pim, kZeroOmegaCoriolis, {});
|
||||
|
||||
Vector3 errorActual = factor.evaluateError(x1, x2, bias);
|
||||
|
||||
// Expected error
|
||||
Vector3 errorExpected(3);
|
||||
errorExpected << 0, 0, 0;
|
||||
// Check value
|
||||
Vector3 errorActual = factor.evaluateError(Ri, Rj, bias);
|
||||
Vector3 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
|
||||
// Check Derivatives
|
||||
Values values;
|
||||
values.insert(X(1), Ri);
|
||||
values.insert(X(2), Rj);
|
||||
values.insert(B(1), bias);
|
||||
EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-5, 1e-6);
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
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)));
|
||||
Rot3 Ri(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0)));
|
||||
Rot3 Rj(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;
|
||||
Vector3 measuredOmega(0, 0, M_PI / 10.0 + 0.3);
|
||||
double deltaT = 1.0;
|
||||
|
||||
PreintegratedAhrsMeasurements pim(Vector3(0,0,0),
|
||||
Z_3x3);
|
||||
PreintegratedAhrsMeasurements pim(Vector3(0, 0, 0), kMeasuredOmegaCovariance);
|
||||
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;
|
||||
// Check value
|
||||
Vector3 errorExpected(0, 0, 0);
|
||||
Vector3 errorActual = factor.evaluateError(Ri, Rj, bias);
|
||||
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));
|
||||
// Check Derivatives
|
||||
Values values;
|
||||
values.insert(X(1), Ri);
|
||||
values.insert(X(2), Rj);
|
||||
values.insert(B(1), bias);
|
||||
EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-5, 1e-6);
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST( AHRSFactor, PartialDerivativeExpmap ) {
|
||||
TEST(AHRSFactor, PartialDerivativeExpmap) {
|
||||
// Linearization point
|
||||
Vector3 biasOmega(0,0,0);
|
||||
Vector3 biasOmega(0, 0, 0);
|
||||
|
||||
// Measurements
|
||||
Vector3 measuredOmega;
|
||||
measuredOmega << 0.1, 0, 0;
|
||||
Vector3 measuredOmega(0.1, 0, 0);
|
||||
double deltaT = 0.5;
|
||||
|
||||
auto f = [&](const Vector3& biasOmega) {
|
||||
return Rot3::Expmap((measuredOmega - biasOmega) * deltaT);
|
||||
};
|
||||
|
||||
// Compute numerical derivatives
|
||||
Matrix expectedDelRdelBiasOmega = numericalDerivative11<Rot3, Vector3>(
|
||||
std::bind(&evaluateRotation, measuredOmega, std::placeholders::_1, deltaT), biasOmega);
|
||||
Matrix expectedH = numericalDerivative11<Rot3, Vector3>(f, biasOmega);
|
||||
|
||||
const Matrix3 Jr = Rot3::ExpmapDerivative(
|
||||
(measuredOmega - biasOmega) * deltaT);
|
||||
const Matrix3 Jr =
|
||||
Rot3::ExpmapDerivative((measuredOmega - biasOmega) * deltaT);
|
||||
|
||||
Matrix3 actualdelRdelBiasOmega = -Jr * deltaT; // the delta bias appears with the minus sign
|
||||
Matrix3 actualH = -Jr * deltaT; // the delta bias appears with the minus sign
|
||||
|
||||
// Compare Jacobians
|
||||
EXPECT(assert_equal(expectedDelRdelBiasOmega, actualdelRdelBiasOmega, 1e-3));
|
||||
EXPECT(assert_equal(expectedH, actualH, 1e-3));
|
||||
// 1e-3 needs to be added only when using quaternions for rotations
|
||||
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST( AHRSFactor, PartialDerivativeLogmap ) {
|
||||
TEST(AHRSFactor, PartialDerivativeLogmap) {
|
||||
// Linearization point
|
||||
Vector3 thetahat;
|
||||
thetahat << 0.1, 0.1, 0; ///< Current estimate of rotation rate bias
|
||||
Vector3 thetaHat(0.1, 0.1, 0); ///< Current estimate of rotation rate bias
|
||||
|
||||
// Measurements
|
||||
Vector3 deltatheta;
|
||||
deltatheta << 0, 0, 0;
|
||||
auto f = [thetaHat](const Vector3 deltaTheta) {
|
||||
return Rot3::Logmap(
|
||||
Rot3::Expmap(thetaHat).compose(Rot3::Expmap(deltaTheta)));
|
||||
};
|
||||
|
||||
// Compute numerical derivatives
|
||||
Matrix expectedDelFdeltheta = numericalDerivative11<Vector3, Vector3>(
|
||||
std::bind(&evaluateLogRotation, thetahat, std::placeholders::_1), deltatheta);
|
||||
Vector3 deltaTheta(0, 0, 0);
|
||||
Matrix expectedH = numericalDerivative11<Vector3, Vector3>(f, 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;
|
||||
const Vector3 x = thetaHat; // parametrization of so(3)
|
||||
const Matrix3 X = skewSymmetric(x); // element of Lie algebra so(3): X = x^
|
||||
double norm = x.norm();
|
||||
const Matrix3 actualH =
|
||||
I_3x3 + 0.5 * X +
|
||||
(1 / (norm * norm) - (1 + cos(norm)) / (2 * norm * sin(norm))) * X * X;
|
||||
|
||||
// Compare Jacobians
|
||||
EXPECT(assert_equal(expectedDelFdeltheta, actualDelFdeltheta));
|
||||
|
||||
EXPECT(assert_equal(expectedH, actualH));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST( AHRSFactor, fistOrderExponential ) {
|
||||
TEST(AHRSFactor, fistOrderExponential) {
|
||||
// Linearization point
|
||||
Vector3 biasOmega(0,0,0);
|
||||
Vector3 biasOmega(0, 0, 0);
|
||||
|
||||
// Measurements
|
||||
Vector3 measuredOmega;
|
||||
measuredOmega << 0.1, 0, 0;
|
||||
Vector3 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;
|
||||
Vector3 deltaBiasOmega(alpha, alpha, alpha);
|
||||
|
||||
const Matrix3 Jr = Rot3::ExpmapDerivative(
|
||||
(measuredOmega - biasOmega) * deltaT);
|
||||
const Matrix3 Jr =
|
||||
Rot3::ExpmapDerivative((measuredOmega - biasOmega) * deltaT);
|
||||
|
||||
Matrix3 delRdelBiasOmega = -Jr * deltaT; // the delta bias appears with the minus sign
|
||||
Matrix3 delRdelBiasOmega =
|
||||
-Jr * deltaT; // the delta bias appears with the minus sign
|
||||
|
||||
const Matrix expectedRot = Rot3::Expmap(
|
||||
(measuredOmega - biasOmega - deltabiasOmega) * deltaT).matrix();
|
||||
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();
|
||||
const Matrix3 actualRot =
|
||||
hatRot * Rot3::Expmap(delRdelBiasOmega * deltaBiasOmega).matrix();
|
||||
|
||||
// Compare Jacobians
|
||||
EXPECT(assert_equal(expectedRot, actualRot));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST( AHRSFactor, FirstOrderPreIntegratedMeasurements ) {
|
||||
TEST(AHRSFactor, FirstOrderPreIntegratedMeasurements) {
|
||||
// Linearization point
|
||||
Vector3 bias = Vector3::Zero(); ///< Current estimate of rotation rate bias
|
||||
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));
|
||||
|
||||
|
|
@ -361,98 +284,76 @@ TEST( AHRSFactor, FirstOrderPreIntegratedMeasurements ) {
|
|||
|
||||
// Actual preintegrated values
|
||||
PreintegratedAhrsMeasurements preintegrated =
|
||||
evaluatePreintegratedMeasurements(bias, measuredOmegas, deltaTs,
|
||||
Vector3(M_PI / 100.0, 0.0, 0.0));
|
||||
integrateMeasurements(bias, measuredOmegas, deltaTs);
|
||||
|
||||
auto f = [&](const Vector3& bias) {
|
||||
return integrateMeasurements(bias, measuredOmegas, deltaTs).deltaRij();
|
||||
};
|
||||
|
||||
// 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 expectedDelRdelBias = numericalDerivative11<Rot3, Vector3>(f, bias);
|
||||
Matrix expectedDelRdelBiasOmega = expectedDelRdelBias.rightCols(3);
|
||||
|
||||
// Compare Jacobians
|
||||
EXPECT(
|
||||
assert_equal(expectedDelRdelBiasOmega, preintegrated.delRdelBiasOmega(), 1e-3));
|
||||
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 ) {
|
||||
|
||||
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)));
|
||||
Rot3 Ri(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0)));
|
||||
Rot3 Rj(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;
|
||||
Vector3 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));
|
||||
Point3(1, 0, 0));
|
||||
|
||||
PreintegratedAhrsMeasurements pim(Vector3::Zero(), kMeasuredAccCovariance);
|
||||
PreintegratedAhrsMeasurements pim(Vector3::Zero(), kMeasuredOmegaCovariance);
|
||||
|
||||
pim.integrateMeasurement(measuredOmega, deltaT);
|
||||
|
||||
// Check preintegrated covariance
|
||||
EXPECT(assert_equal(kMeasuredAccCovariance, pim.preintMeasCov()));
|
||||
EXPECT(assert_equal(kMeasuredOmegaCovariance, 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));
|
||||
// Check Derivatives
|
||||
Values values;
|
||||
values.insert(X(1), Ri);
|
||||
values.insert(X(2), Rj);
|
||||
values.insert(B(1), bias);
|
||||
EXPECT_CORRECT_FACTOR_JACOBIANS(factor, values, 1e-5, 1e-6);
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
TEST (AHRSFactor, predictTest) {
|
||||
Vector3 bias(0,0,0);
|
||||
TEST(AHRSFactor, predictTest) {
|
||||
Vector3 bias(0, 0, 0);
|
||||
|
||||
// Measurements
|
||||
Vector3 measuredOmega;
|
||||
measuredOmega << 0, 0, M_PI / 10.0;
|
||||
Vector3 measuredOmega(0, 0, M_PI / 10.0);
|
||||
double deltaT = 0.2;
|
||||
PreintegratedAhrsMeasurements pim(bias, kMeasuredAccCovariance);
|
||||
PreintegratedAhrsMeasurements pim(bias, kMeasuredOmegaCovariance);
|
||||
for (int i = 0; i < 1000; ++i) {
|
||||
pim.integrateMeasurement(measuredOmega, deltaT);
|
||||
}
|
||||
// Check preintegrated covariance
|
||||
Matrix expectedMeasCov(3,3);
|
||||
expectedMeasCov = 200*kMeasuredAccCovariance;
|
||||
Matrix expectedMeasCov(3, 3);
|
||||
expectedMeasCov = 200 * kMeasuredOmegaCovariance;
|
||||
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 expectedRot = Rot3::Ypr(20 * M_PI, 0, 0);
|
||||
Rot3 actualRot = factor.predict(x, bias, pim, kZeroOmegaCoriolis);
|
||||
EXPECT(assert_equal(expectedRot, actualRot, 1e-6));
|
||||
|
||||
|
|
@ -462,29 +363,27 @@ TEST (AHRSFactor, predictTest) {
|
|||
|
||||
// Actual Jacobians
|
||||
Matrix H;
|
||||
(void) pim.predict(bias,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) {
|
||||
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);
|
||||
Rot3 Ri(Rot3::RzRyRx(0, 0, 0));
|
||||
Rot3 Rj(Rot3::RzRyRx(0, M_PI / 4, 0));
|
||||
Vector3 bias(0, 0, 0);
|
||||
|
||||
// PreIntegrator
|
||||
Vector3 biasHat(0, 0, 0);
|
||||
PreintegratedAhrsMeasurements pim(biasHat, kMeasuredAccCovariance);
|
||||
PreintegratedAhrsMeasurements pim(biasHat, kMeasuredOmegaCovariance);
|
||||
|
||||
// Pre-integrate measurements
|
||||
Vector3 measuredOmega(0, M_PI / 20, 0);
|
||||
double deltaT = 1;
|
||||
|
||||
// Create Factor
|
||||
noiseModel::Base::shared_ptr model = //
|
||||
noiseModel::Base::shared_ptr model = //
|
||||
noiseModel::Gaussian::Covariance(pim.preintMeasCov());
|
||||
NonlinearFactorGraph graph;
|
||||
Values values;
|
||||
|
|
@ -492,10 +391,10 @@ TEST (AHRSFactor, graphTest) {
|
|||
pim.integrateMeasurement(measuredOmega, deltaT);
|
||||
}
|
||||
|
||||
// pim.print("Pre integrated measurementes");
|
||||
// pim.print("Pre integrated measurements");
|
||||
AHRSFactor factor(X(1), X(2), B(1), pim, kZeroOmegaCoriolis);
|
||||
values.insert(X(1), x1);
|
||||
values.insert(X(2), x2);
|
||||
values.insert(X(1), Ri);
|
||||
values.insert(X(2), Rj);
|
||||
values.insert(B(1), bias);
|
||||
graph.push_back(factor);
|
||||
LevenbergMarquardtOptimizer optimizer(graph, values);
|
||||
|
|
|
|||
Loading…
Reference in New Issue