gtsam/gtsam/navigation/tests/testCombinedImuFactor.cpp

324 lines
12 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 testCombinedImuFactor.cpp
* @brief Unit test for Lupton-style combined IMU factor
* @author Luca Carlone
* @author Frank Dellaert
* @author Richard Roberts
* @author Stephen Williams
* @author Varun Agrawal
*/
#include <CppUnitLite/TestHarness.h>
#include <gtsam/base/TestableAssertions.h>
#include <gtsam/base/numericalDerivative.h>
#include <gtsam/geometry/Pose3.h>
#include <gtsam/inference/Symbol.h>
#include <gtsam/navigation/CombinedImuFactor.h>
#include <gtsam/navigation/ImuBias.h>
#include <gtsam/navigation/ImuFactor.h>
#include <gtsam/navigation/ScenarioRunner.h>
#include <gtsam/nonlinear/Values.h>
#include <list>
#include "imuFactorTesting.h"
namespace testing {
// Create default parameters with Z-down and above noise parameters
static boost::shared_ptr<PreintegratedCombinedMeasurements::Params> Params() {
auto p = PreintegratedCombinedMeasurements::Params::MakeSharedD(kGravity);
p->gyroscopeCovariance = kGyroSigma * kGyroSigma * I_3x3;
p->accelerometerCovariance = kAccelSigma * kAccelSigma * I_3x3;
p->integrationCovariance = 0.0001 * I_3x3;
p->biasAccCovariance = Z_3x3;
p->biasOmegaCovariance = Z_3x3;
p->biasAccOmegaInit = Z_6x6;
return p;
}
} // namespace testing
/* ************************************************************************* */
TEST(CombinedImuFactor, PreintegratedMeasurements ) {
// Linearization point
Bias bias(Vector3(0, 0, 0), Vector3(0, 0, 0)); ///< Current estimate of acceleration and angular rate biases
// Measurements
Vector3 measuredAcc(0.1, 0.0, 0.0);
Vector3 measuredOmega(M_PI / 100.0, 0.0, 0.0);
double deltaT = 0.5;
double tol = 1e-6;
auto p = testing::Params();
// Actual preintegrated values
PreintegratedImuMeasurements expected1(p, bias);
expected1.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
PreintegratedCombinedMeasurements actual1(p, bias);
actual1.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
EXPECT(assert_equal(Vector(expected1.deltaPij()), actual1.deltaPij(), tol));
EXPECT(assert_equal(Vector(expected1.deltaVij()), actual1.deltaVij(), tol));
EXPECT(assert_equal(expected1.deltaRij(), actual1.deltaRij(), tol));
DOUBLES_EQUAL(expected1.deltaTij(), actual1.deltaTij(), tol);
}
/* ************************************************************************* */
TEST(CombinedImuFactor, ErrorWithBiases ) {
Bias bias(Vector3(0.2, 0, 0), Vector3(0, 0, 0.3)); // Biases (acc, rot)
Bias bias2(Vector3(0.2, 0.2, 0), Vector3(1, 0, 0.3)); // Biases (acc, rot)
Pose3 x1(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0)), Point3(5.0, 1.0, -50.0));
Vector3 v1(0.5, 0.0, 0.0);
Pose3 x2(Rot3::Expmap(Vector3(0, 0, M_PI / 4.0 + M_PI / 10.0)),
Point3(5.5, 1.0, -50.0));
Vector3 v2(0.5, 0.0, 0.0);
auto p = testing::Params();
p->omegaCoriolis = Vector3(0,0.1,0.1);
PreintegratedImuMeasurements pim(
p, Bias(Vector3(0.2, 0.0, 0.0), Vector3(0.0, 0.0, 0.0)));
// Measurements
Vector3 measuredOmega;
measuredOmega << 0, 0, M_PI / 10.0 + 0.3;
Vector3 measuredAcc =
x1.rotation().unrotate(-p->n_gravity) + Vector3(0.2, 0.0, 0.0);
double deltaT = 1.0;
double tol = 1e-6;
pim.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
PreintegratedCombinedMeasurements combined_pim(p,
Bias(Vector3(0.2, 0.0, 0.0), Vector3(0.0, 0.0, 0.0)));
combined_pim.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
// Create factor
ImuFactor imuFactor(X(1), V(1), X(2), V(2), B(1), pim);
noiseModel::Gaussian::shared_ptr Combinedmodel =
noiseModel::Gaussian::Covariance(combined_pim.preintMeasCov());
CombinedImuFactor combinedfactor(X(1), V(1), X(2), V(2), B(1), B(2),
combined_pim);
Vector errorExpected = imuFactor.evaluateError(x1, v1, x2, v2, bias);
Vector errorActual = combinedfactor.evaluateError(x1, v1, x2, v2, bias,
bias2);
EXPECT(assert_equal(errorExpected, errorActual.head(9), tol));
// Expected Jacobians
Matrix H1e, H2e, H3e, H4e, H5e;
(void) imuFactor.evaluateError(x1, v1, x2, v2, bias, H1e, H2e, H3e, H4e, H5e);
// Actual Jacobians
Matrix H1a, H2a, H3a, H4a, H5a, H6a;
(void) combinedfactor.evaluateError(x1, v1, x2, v2, bias, bias2, H1a, H2a,
H3a, H4a, H5a, H6a);
EXPECT(assert_equal(H1e, H1a.topRows(9)));
EXPECT(assert_equal(H2e, H2a.topRows(9)));
EXPECT(assert_equal(H3e, H3a.topRows(9)));
EXPECT(assert_equal(H4e, H4a.topRows(9)));
EXPECT(assert_equal(H5e, H5a.topRows(9)));
}
/* ************************************************************************* */
#ifdef GTSAM_TANGENT_PREINTEGRATION
TEST(CombinedImuFactor, FirstOrderPreIntegratedMeasurements) {
auto p = testing::Params();
testing::SomeMeasurements measurements;
auto preintegrated = [=](const Vector3& a, const Vector3& w) {
PreintegratedImuMeasurements pim(p, Bias(a, w));
testing::integrateMeasurements(measurements, &pim);
return pim.preintegrated();
};
// Actual pre-integrated values
PreintegratedCombinedMeasurements pim(p);
testing::integrateMeasurements(measurements, &pim);
EXPECT(assert_equal(numericalDerivative21<Vector9, Vector3, Vector3>(preintegrated, Z_3x1, Z_3x1),
pim.preintegrated_H_biasAcc()));
EXPECT(assert_equal(numericalDerivative22<Vector9, Vector3, Vector3>(preintegrated, Z_3x1, Z_3x1),
pim.preintegrated_H_biasOmega(), 1e-3));
}
#endif
/* ************************************************************************* */
TEST(CombinedImuFactor, PredictPositionAndVelocity) {
const Bias bias(Vector3(0, 0.1, 0), Vector3(0, 0.1, 0)); // Biases (acc, rot)
auto p = testing::Params();
// Measurements
const Vector3 measuredOmega(0, 0.1, 0); // M_PI/10.0+0.3;
const Vector3 measuredAcc(0, 1.1, -kGravity);
const double deltaT = 0.01;
PreintegratedCombinedMeasurements pim(p, bias);
for (int i = 0; i < 100; ++i)
pim.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
// Create factor
const noiseModel::Gaussian::shared_ptr combinedmodel =
noiseModel::Gaussian::Covariance(pim.preintMeasCov());
const CombinedImuFactor Combinedfactor(X(1), V(1), X(2), V(2), B(1), B(2), pim);
// Predict
const NavState actual = pim.predict(NavState(), bias);
const Pose3 expectedPose(Rot3(), Point3(0, 0.5, 0));
const Vector3 expectedVelocity(0, 1, 0);
EXPECT(assert_equal(expectedPose, actual.pose()));
EXPECT(assert_equal(Vector(expectedVelocity), Vector(actual.velocity())));
}
/* ************************************************************************* */
TEST(CombinedImuFactor, PredictRotation) {
const Bias bias(Vector3(0, 0, 0), Vector3(0, 0, 0)); // Biases (acc, rot)
auto p = testing::Params();
PreintegratedCombinedMeasurements pim(p, bias);
const Vector3 measuredAcc = - kGravityAlongNavZDown;
const Vector3 measuredOmega(0, 0, M_PI / 10.0);
const double deltaT = 0.01;
const double tol = 1e-4;
for (int i = 0; i < 100; ++i)
pim.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
const CombinedImuFactor Combinedfactor(X(1), V(1), X(2), V(2), B(1), B(2), pim);
// Predict
const Pose3 x(Rot3::Ypr(0, 0, 0), Point3(0, 0, 0)), x2;
const Vector3 v(0, 0, 0), v2;
const NavState actual = pim.predict(NavState(x, v), bias);
const Pose3 expectedPose(Rot3::Ypr(M_PI / 10, 0, 0), Point3(0, 0, 0));
EXPECT(assert_equal(expectedPose, actual.pose(), tol));
}
/* ************************************************************************* */
// Testing covariance to check if all the jacobians are accounted for.
TEST(CombinedImuFactor, CheckCovariance) {
auto params = PreintegrationCombinedParams::MakeSharedU(9.81);
params->setAccelerometerCovariance(pow(0.01, 2) * I_3x3);
params->setGyroscopeCovariance(pow(1.75e-4, 2) * I_3x3);
params->setIntegrationCovariance(pow(0.0, 2) * I_3x3);
params->setOmegaCoriolis(Vector3::Zero());
imuBias::ConstantBias currentBias;
PreintegratedCombinedMeasurements actual(params, currentBias);
// Measurements
Vector3 measuredAcc(0.1577, -0.8251, 9.6111);
Vector3 measuredOmega(-0.0210, 0.0311, 0.0145);
double deltaT = 0.01;
actual.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
Eigen::Matrix<double, 15, 15> expected;
expected << 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, //
0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, //
0, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 2.50025e-07, 0, 0, 5.0005e-05, 0, 0, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 0, 2.50025e-07, 0, 0, 5.0005e-05, 0, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 0, 0, 2.50025e-07, 0, 0, 5.0005e-05, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 5.0005e-05, 0, 0, 0.010001, 0, 0, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 0, 5.0005e-05, 0, 0, 0.010001, 0, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 0, 0, 5.0005e-05, 0, 0, 0.010001, 0, 0, 0, 0, 0, 0, //
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, 0, 0, //
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, 0, //
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, //
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, 0, //
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.01, 0, //
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.0;
// regression
EXPECT(assert_equal(expected, actual.preintMeasCov()));
}
// Test that the covariance values for the ImuFactor and the CombinedImuFactor
// (top-left 9x9) are the same
TEST(CombinedImuFactor, SameCovariance) {
// IMU measurements and time delta
Vector3 accMeas(0.1577, -0.8251, 9.6111);
Vector3 omegaMeas(-0.0210, 0.0311, 0.0145);
double deltaT = 0.01;
// Assume zero bias
imuBias::ConstantBias currentBias;
// Define params for ImuFactor
auto params = PreintegrationParams::MakeSharedU();
params->setAccelerometerCovariance(pow(0.01, 2) * I_3x3);
params->setGyroscopeCovariance(pow(1.75e-4, 2) * I_3x3);
params->setIntegrationCovariance(pow(0, 2) * I_3x3);
params->setOmegaCoriolis(Vector3::Zero());
// The IMU preintegration object for ImuFactor
PreintegratedImuMeasurements pim(params, currentBias);
pim.integrateMeasurement(accMeas, omegaMeas, deltaT);
// Define params for CombinedImuFactor
auto combined_params = PreintegrationCombinedParams::MakeSharedU();
combined_params->setAccelerometerCovariance(pow(0.01, 2) * I_3x3);
combined_params->setGyroscopeCovariance(pow(1.75e-4, 2) * I_3x3);
combined_params->setIntegrationCovariance(pow(0, 2) * I_3x3);
combined_params->setOmegaCoriolis(Vector3::Zero());
// Set bias integration covariance explicitly to zero
combined_params->setBiasAccOmegaInt(Z_6x6);
// The IMU preintegration object for CombinedImuFactor
PreintegratedCombinedMeasurements cpim(combined_params, currentBias);
cpim.integrateMeasurement(accMeas, omegaMeas, deltaT);
// Assert if the noise covariance
EXPECT(assert_equal(pim.preintMeasCov(),
cpim.preintMeasCov().block(0, 0, 9, 9)));
}
/* ************************************************************************* */
TEST(CombinedImuFactor, Accelerating) {
const double a = 0.2, v = 50;
// Set up body pointing towards y axis, and start at 10,20,0 with velocity
// going in X The body itself has Z axis pointing down
const Rot3 nRb(Point3(0, 1, 0), Point3(1, 0, 0), Point3(0, 0, -1));
const Point3 initial_position(10, 20, 0);
const Vector3 initial_velocity(v, 0, 0);
const AcceleratingScenario scenario(nRb, initial_position, initial_velocity,
Vector3(a, 0, 0));
const double T = 3.0; // seconds
CombinedScenarioRunner runner(scenario, testing::Params(), T / 10);
PreintegratedCombinedMeasurements pim = runner.integrate(T);
EXPECT(assert_equal(scenario.pose(T), runner.predict(pim).pose(), 1e-9));
auto estimatedCov = runner.estimateCovariance(T, 100);
Eigen::Matrix<double, 15, 15> expected = pim.preintMeasCov();
EXPECT(assert_equal(estimatedCov, expected, 0.1));
}
/* ************************************************************************* */
int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */