gtsam/tests/testImuPreintegration.cpp

156 lines
5.6 KiB
C++

/**
* @file testImuPreintegration.cpp
* @brief Unit tests for IMU Preintegration
* @author Russell Buchanan
**/
#include <tests/ImuMeasurement.h>
#include <fstream>
#include <iostream>
#include <CppUnitLite/TestHarness.h>
#include <gtsam/base/Testable.h>
#include <gtsam/base/numericalDerivative.h>
#include <gtsam/navigation/CombinedImuFactor.h>
namespace drs {
Measurement::Measurement() : dt(0), time(0), type("UNDEFINED") {}
Measurement::Measurement(std::string _type) : dt(0), time(0), type(_type) {}
ImuMeasurement::ImuMeasurement() : I_a_WI{0, 0, 0}, I_w_WI{0, 0, 0} { type = "ImuMeasurement"; }
std::ostream& operator<<(std::ostream& stream, const ImuMeasurement& meas) {
stream << "IMU Measurement at time = " << meas.time << " : \n"
<< "dt : " << meas.dt << "\n"
<< "I_a_WI: " << meas.I_a_WI.transpose() << "\n"
<< "I_w_WI: " << meas.I_w_WI.transpose() << "\n";
return stream;
}
} // namespace drs
using namespace gtsam;
/* ************************************************************************* */
/// \brief Uses the GTSAM library to perform IMU preintegration on an acceleration input.
///
TEST(GtsamLibraryTests, LoadedSimulationData) {
Eigen::Vector3d finalPos;
std::vector<drs::ImuMeasurement> imuMeasurements;
double accNoiseSigma = 0.001249;
double accBiasRwSigma = 0.000106;
double gyrNoiseSigma = 0.000208;
double gyrBiasRwSigma = 0.000004;
double integrationCovariance = 1e-8;
double biasAccOmegaInt = 1e-5;
double gravity = 9.81;
double rate = 400.0; // Hz
/// @todo Update directory to correct location
std::string inFileString = "/home/russell/imu_data.csv";
std::ofstream outputFile;
outputFile.open("/home/russell/gtsam_output.csv", std::ofstream::out);
std::ifstream inputFile(inFileString);
std::string line;
while (std::getline(inputFile, line)) {
std::stringstream ss(line);
std::string str;
std::vector<double> results;
while (getline(ss, str, ',')) {
results.push_back(std::atof(str.c_str()));
}
drs::ImuMeasurement measurement;
measurement.dt = static_cast<uint64_t>(1e9 * (1 / rate));
measurement.time = results[2];
measurement.I_a_WI = {results[29], results[30], results[31]};
measurement.I_w_WI = {results[17], results[18], results[19]};
imuMeasurements.push_back(measurement);
// std::cout << "IMU measurement " << measurement << std::endl;
}
// Assume a Z-up navigation (assuming we are performing optimization in the IMU frame).
boost::shared_ptr<gtsam::PreintegratedCombinedMeasurements::Params> imuPreintegratedParams =
gtsam::PreintegratedCombinedMeasurements::Params::MakeSharedU(gravity);
imuPreintegratedParams->accelerometerCovariance = I_3x3 * pow(accNoiseSigma, 2);
imuPreintegratedParams->biasAccCovariance = I_3x3 * pow(accBiasRwSigma, 2);
imuPreintegratedParams->gyroscopeCovariance = I_3x3 * pow(gyrNoiseSigma, 2);
imuPreintegratedParams->biasOmegaCovariance = I_3x3 * pow(gyrBiasRwSigma, 2);
imuPreintegratedParams->integrationCovariance = I_3x3 * integrationCovariance;
imuPreintegratedParams->biasAccOmegaInt = I_6x6 * biasAccOmegaInt;
// Initial state
gtsam::Pose3 priorPose;
gtsam::Vector3 priorVelocity;
gtsam::imuBias::ConstantBias priorImuBias;
gtsam::PreintegratedCombinedMeasurements imuPreintegrated;
Eigen::Vector3d position;
Eigen::Vector3d velocity;
gtsam::NavState propState;
gtsam::NavState initialNavState(priorPose, priorVelocity);
// Bias estimated by my Algorithm
priorImuBias =
gtsam::imuBias::ConstantBias(Eigen::Vector3d(-0.0314648, 0.0219921, 6.95945e-05),
Eigen::Vector3d(4.88581e-08, -1.04971e-09, -0.000122868));
// zero bias
// priorImuBias = gtsam::imuBias::ConstantBias(Eigen::Vector3d(0,0,0),
// Eigen::Vector3d(0,0,0));
imuPreintegrated = gtsam::PreintegratedCombinedMeasurements(imuPreintegratedParams, priorImuBias);
// Put header row in output csv
outputFile << "X Position,"
<< "Y Position,"
<< "Z Position,"
<< "X Velocity,"
<< "Y Velocity,"
<< "Z Velocity,"
<< "\n";
for (int n = 1; n < imuMeasurements.size(); n++) { //start at 1 to skip header
// integrate
imuPreintegrated.integrateMeasurement(imuMeasurements[n].I_a_WI, imuMeasurements[n].I_w_WI,
1 / rate);
// predict
propState = imuPreintegrated.predict(initialNavState, priorImuBias);
position = propState.pose().translation();
velocity = propState.velocity();
// std::cout << "IMU Position " << position.transpose() << std::endl;
// std::cout << "IMU Velocity " << velocity.transpose() << std::endl;
// Write to csv
outputFile << std::to_string(position.x()) << "," << std::to_string(position.y()) << ","
<< std::to_string(position.z()) << "," << std::to_string(velocity.x()) << ","
<< std::to_string(velocity.y()) << "," << std::to_string(velocity.z()) << ","
<< "\n";
}
outputFile.close();
gtsam::Vector3 rotation = propState.pose().rotation().rpy();
// Dont have ground truth for x and y position yet
// DOUBLES_EQUAL(0.1, position[0], 1e-2);
// DOUBLES_EQUAL(0.1, position[1], 1e-2);
DOUBLES_EQUAL(0.0, position[2], 1e-2);
DOUBLES_EQUAL(0.0, rotation[0], 1e-2);
DOUBLES_EQUAL(0.0, rotation[1], 1e-2);
DOUBLES_EQUAL(0.0, rotation[2], 1e-2);
}
/* ************************************************************************* */
int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */