/* ---------------------------------------------------------------------------- * 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 testImuPreintegration.cpp * @brief Unit tests for IMU Preintegration * @author Russell Buchanan **/ #include #include #include #include #include #include #include #include using namespace std; using namespace gtsam; /* ************************************************************************* */ /** * \brief Uses the GTSAM library to perform IMU preintegration on an * acceleration input. */ TEST(TestImuPreintegration, LoadedSimulationData) { Vector3 finalPos(0, 0, 0); vector 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 string inFileString = findExampleDataFile("quadraped_imu_data.csv"); ifstream inputFile(inFileString); string line; while (getline(inputFile, line)) { stringstream ss(line); string str; vector results; while (getline(ss, str, ',')) { results.push_back(atof(str.c_str())); } ImuMeasurement measurement; measurement.dt = static_cast(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); } // Assume a Z-up navigation (assuming we are performing optimization in the // IMU frame). auto imuPreintegratedParams = 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 Pose3 priorPose; Vector3 priorVelocity(0, 0, 0); imuBias::ConstantBias priorImuBias; PreintegratedCombinedMeasurements imuPreintegrated; Vector3 position(0, 0, 0); Vector3 velocity(0, 0, 0); NavState propState; NavState initialNavState(priorPose, priorVelocity); // Assume zero bias for simulated data priorImuBias = imuBias::ConstantBias(Eigen::Vector3d(0, 0, 0), Eigen::Vector3d(0, 0, 0)); imuPreintegrated = PreintegratedCombinedMeasurements(imuPreintegratedParams, priorImuBias); // start at 1 to skip header for (size_t n = 1; n < imuMeasurements.size(); n++) { // 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(); } 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); } /* ************************************************************************* */