CPose3DPDFGaussian.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2020, Individual contributors, see AUTHORS file     |
   | See: https://www.mrpt.org/Authors - All rights reserved.               |
   | Released under BSD License. See: https://www.mrpt.org/License          |
   +------------------------------------------------------------------------+ */

#include "poses-precomp.h"  // Precompiled headers

#include <mrpt/math/matrix_serialization.h>
#include <mrpt/math/transform_gaussian.h>
#include <mrpt/math/wrap2pi.h>
#include <mrpt/poses/CPose3DPDFGaussian.h>
#include <mrpt/poses/CPose3DQuatPDFGaussian.h>
#include <mrpt/poses/CPosePDFGaussian.h>
#include <mrpt/random.h>
#include <mrpt/serialization/CArchive.h>
#include <mrpt/system/os.h>
#include <Eigen/Dense>

#include <sstream>

using namespace mrpt;
using namespace mrpt::poses;
using namespace mrpt::math;
using namespace mrpt::random;
using namespace mrpt::system;
using namespace std;

bool USE_SUT_QUAT2EULER_CONVERSION_value = false;

void mrpt::global_settings::USE_SUT_QUAT2EULER_CONVERSION(bool value)
{
    USE_SUT_QUAT2EULER_CONVERSION_value = value;
}
bool mrpt::global_settings::USE_SUT_QUAT2EULER_CONVERSION()
{
    return USE_SUT_QUAT2EULER_CONVERSION_value;
}

IMPLEMENTS_SERIALIZABLE(CPose3DPDFGaussian, CPose3DPDF, mrpt::poses)

/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussian::CPose3DPDFGaussian() : mean(0, 0, 0), cov() {}
/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussian::CPose3DPDFGaussian([
    [maybe_unused]] TConstructorFlags_Poses constructor_dummy_param)
    : mean(UNINITIALIZED_POSE), cov(UNINITIALIZED_MATRIX)
{
}

/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussian::CPose3DPDFGaussian(
    const CPose3D& init_Mean, const CMatrixDouble66& init_Cov)
    : mean(init_Mean), cov(init_Cov)
{
}

/*---------------------------------------------------------------
    Copy Constructor from 2D PDF
  ---------------------------------------------------------------*/
CPose3DPDFGaussian::CPose3DPDFGaussian(const CPosePDFGaussian& o)
    : mean(o.mean.x(), o.mean.y(), 0, o.mean.phi(), 0, 0), cov()
{
    for (size_t i = 0; i < 3; i++)
    {
        const size_t ii = (i == 2) ? 3 : i;
        for (size_t j = 0; j < 3; j++)
        {
            const size_t jj = (j == 2) ? 3 : j;
            cov(ii, jj) = o.cov(i, j);
        }
    }
}

/*---------------------------------------------------------------
    Constructor
  ---------------------------------------------------------------*/
CPose3DPDFGaussian::CPose3DPDFGaussian(const CPose3D& init_Mean)
    : mean(init_Mean), cov()
{
}

//#define DO_TEST_JACOB

#ifdef DO_TEST_JACOB
void ffff(
    const CVectorDouble& x, const CQuaternionDouble& Q, CVectorDouble& OUT)
{
    OUT.resize(3);
    CQuaternionDouble q(x[0], x[1], x[2], x[3]);
    q.normalize();
    q.rpy(OUT[2], OUT[1], OUT[0]);
}
#endif

static void aux_posequat2poseypr(
    const CVectorFixedDouble<7>& x, [[maybe_unused]] const double& dummy,
    CVectorFixedDouble<6>& y)
{
    y[0] = x[0];
    y[1] = x[1];
    y[2] = x[2];
    CQuaternionDouble q(x[3], x[4], x[5], x[6]);
    q.normalize();
    q.rpy(y[5], y[4], y[3]);
}

/*---------------------------------------------------------------
                    CPose3DPDFGaussian
 ---------------------------------------------------------------*/
CPose3DPDFGaussian::CPose3DPDFGaussian(const CPose3DQuatPDFGaussian& o)
    : mean(UNINITIALIZED_POSE), cov(UNINITIALIZED_MATRIX)
{
    this->copyFrom(o);
}

/*---------------------------------------------------------------
                    asString
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::asString(std::string& s) const
{
    ostringstream ss;
    ss << *this;
    s = ss.str();
}

/*---------------------------------------------------------------
                        copyFrom
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::copyFrom(const CPose3DQuatPDFGaussian& o)
{
    MRPT_START
    if (!USE_SUT_QUAT2EULER_CONVERSION_value)
    {
// Convert using Jacobians and first order approximation:

//         [  I_3   |    0         ]
// dr_dq = [ -------+------------- ]
//         [  0     | dr_dq_angles ]
#ifdef DO_TEST_JACOB
        // Test Jacob:
        {
            CVectorDouble x(4);
            for (int i = 0; i < 4; i++) x[i] = o.mean.quat()[i];
            CVectorDouble Ax(4);
            Ax.assign(1e-7);
            CMatrixDouble H;
            jacobians::jacob_numeric_estimate(x, ffff, Ax, o.mean.quat(), H);
            cout << "num:" << endl << H << endl << endl;
            CMatrixDouble J;
            double a, b, c;
            o.mean.quat().rpy_and_jacobian(a, b, c, &J);
            CMatrixDouble NJ;
            o.mean.quat().normalizationJacobian(NJ);
            cout << "lin:" << endl << J * NJ << endl << endl;
        }
#endif

        double yaw, pitch, roll;
        CMatrixFixed<double, 3, 4> dr_dq_sub_aux(UNINITIALIZED_MATRIX);

        o.mean.quat().rpy_and_jacobian(roll, pitch, yaw, &dr_dq_sub_aux, false);

        CMatrixDouble44 dnorm_dq(UNINITIALIZED_MATRIX);
        o.mean.quat().normalizationJacobian(dnorm_dq);

        CMatrixFixed<double, 3, 4> dr_dq_sub(UNINITIALIZED_MATRIX);
        dr_dq_sub.asEigen() = dr_dq_sub_aux * dnorm_dq;

        // Set the mean:
        this->mean.setFromValues(
            o.mean.x(), o.mean.y(), o.mean.z(), yaw, pitch, roll);

        // Cov:
        const CMatrixDouble44 cov_Q = o.cov.blockCopy<4, 4>(3, 3);
        const CMatrixDouble33 cov_T = o.cov.blockCopy<3, 3>(0, 0);
        const CMatrixFixed<double, 3, 4> cov_TQ = o.cov.blockCopy<3, 4>(0, 3);

        // [        S_T       |   S_TQ * H^t    ]
        // [ -----------------+---------------- ]
        // [  (S_TQ * H^t)^t  |  H * S_Q * H^t  ]

        // top-left:
        this->cov.insertMatrix(0, 0, cov_T);

        // diagonals:
        const Eigen::Matrix3d cov_TR = cov_TQ.asEigen() * dr_dq_sub.transpose();
        this->cov.block<3, 3>(0, 3) = cov_TR;
        this->cov.block<3, 3>(3, 0) = cov_TR.transpose();

        // bottom-right:
        CMatrixDouble33 cov_r = mrpt::math::multiply_HCHt(dr_dq_sub, cov_Q);
        this->cov.insertMatrix(3, 3, cov_r);
    }
    else
    {
        // Use UT transformation:
        //   f: R^7 => R^6
        const CVectorFixedDouble<7> x_mean(o.mean);
        CVectorFixedDouble<6> y_mean;
        static const bool elements_do_wrapPI[6] = {
            false, false, false, true, true, true};  // xyz yaw pitch roll

        const double dummy = 0;
        mrpt::math::transform_gaussian_unscented(
            x_mean, o.cov, aux_posequat2poseypr, dummy, y_mean, this->cov,
            elements_do_wrapPI);
        this->mean.setFromValues(
            y_mean[0], y_mean[1], y_mean[2], y_mean[3], y_mean[4], y_mean[5]);
    }
    MRPT_END
}

uint8_t CPose3DPDFGaussian::serializeGetVersion() const { return 1; }
void CPose3DPDFGaussian::serializeTo(mrpt::serialization::CArchive& out) const
{
    out << mean;
    mrpt::math::serializeSymmetricMatrixTo(cov, out);
}
void CPose3DPDFGaussian::serializeFrom(
    mrpt::serialization::CArchive& in, uint8_t version)
{
    switch (version)
    {
        case 1:
        {
            in >> mean;
            mrpt::math::deserializeSymmetricMatrixFrom(cov, in);
        }
        break;
        default:
            MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION(version);
    };
}

void CPose3DPDFGaussian::copyFrom(const CPose3DPDF& o)
{
    if (this == &o) return;  // It may be used sometimes

    // Convert to gaussian pdf:
    o.getCovarianceAndMean(cov, mean);
}

void CPose3DPDFGaussian::copyFrom(const CPosePDF& o)
{
    // Convert to gaussian pdf:
    CMatrixDouble33 C;
    CPose2D p;
    o.getCovarianceAndMean(C, p);
    mean = CPose3D(p);

    cov.setZero();
    cov(0, 0) = C(0, 0);
    cov(1, 1) = C(1, 1);
    cov(3, 3) = C(2, 2);

    cov(0, 1) = cov(1, 0) = C(0, 1);

    cov(0, 3) = cov(3, 0) = C(0, 2);

    cov(1, 3) = cov(3, 1) = C(1, 2);
}

/*---------------------------------------------------------------

  ---------------------------------------------------------------*/
bool CPose3DPDFGaussian::saveToTextFile(const string& file) const
{
    FILE* f = os::fopen(file.c_str(), "wt");
    if (!f) return false;

    os::fprintf(
        f, "%e %e %e %e %e %e\n", mean.x(), mean.y(), mean.z(), mean.yaw(),
        mean.pitch(), mean.roll());

    for (unsigned int i = 0; i < 6; i++)
        os::fprintf(
            f, "%e %e %e %e %e %e\n", cov(i, 0), cov(i, 1), cov(i, 2),
            cov(i, 3), cov(i, 4), cov(i, 5));

    os::fclose(f);
    return true;
}

/*---------------------------------------------------------------
                        changeCoordinatesReference
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::changeCoordinatesReference(
    const CPose3D& newReferenceBase)
{
    MRPT_START
    // this = p (+) this

    // COV:
    const CMatrixDouble66 OLD_COV = this->cov;
    CMatrixDouble66 df_dx(UNINITIALIZED_MATRIX), df_du(UNINITIALIZED_MATRIX);

    CPose3DPDF::jacobiansPoseComposition(
        newReferenceBase,  // x
        this->mean,  // u
        df_dx, df_du);

    // this->cov = H1*this->cov*H1' + H2* 0 *H2';
    cov = mrpt::math::multiply_HCHt(df_du, OLD_COV);

    // MEAN:
    this->mean.composeFrom(newReferenceBase, this->mean);

    MRPT_END
}

/*---------------------------------------------------------------
                    drawSingleSample
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::drawSingleSample(CPose3D& outPart) const
{
    MRPT_START

    CVectorDouble v;
    getRandomGenerator().drawGaussianMultivariate(v, cov);

    outPart.setFromValues(
        mean.x() + v[0], mean.y() + v[1], mean.z() + v[2], mean.yaw() + v[3],
        mean.pitch() + v[4], mean.roll() + v[5]);

    MRPT_END_WITH_CLEAN_UP(
        cov.saveToTextFile("__DEBUG_EXC_DUMP_drawSingleSample_COV.txt"););
}

/*---------------------------------------------------------------
                    drawManySamples
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::drawManySamples(
    size_t N, vector<CVectorDouble>& outSamples) const
{
    MRPT_START

    getRandomGenerator().drawGaussianMultivariateMany(outSamples, N, cov);

    for (auto& outSample : outSamples)
    {
        outSample[0] += mean.x();
        outSample[1] += mean.y();
        outSample[2] += mean.z();
        outSample[3] = math::wrapToPi(outSample[3] + mean.yaw());
        outSample[4] = math::wrapToPi(outSample[4] + mean.pitch());
        outSample[5] = math::wrapToPi(outSample[5] + mean.roll());
    }

    MRPT_END
}

/*---------------------------------------------------------------
                    bayesianFusion
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::bayesianFusion(
    [[maybe_unused]] const CPose3DPDF& p1_,
    [[maybe_unused]] const CPose3DPDF& p2_)
{
    MRPT_START

    THROW_EXCEPTION("TO DO!!!");

    /*  ASSERT_( p1_.GetRuntimeClass() == CLASS_ID( CPose3DPDFGaussian )  );
        ASSERT_( p2_.GetRuntimeClass() == CLASS_ID( CPose3DPDFGaussian )  );

        CPose3DPDFGaussian  *p1 = (CPose3DPDFGaussian*) &p1_;
        CPose3DPDFGaussian  *p2 = (CPose3DPDFGaussian*) &p2_;


        CMatrixD    x1(3,1),x2(3,1),x(3,1);
        CMatrixD    C1( p1->cov );
        CMatrixD    C2( p2->cov );
        CMatrixD    C1_inv = C1.inverse_LLt();
        CMatrixD    C2_inv = C2.inverse_LLt();
        CMatrixD    C;

        x1(0,0) = p1->mean.x; x1(1,0) = p1->mean.y; x1(2,0) = p1->mean.phi;
        x2(0,0) = p2->mean.x; x2(1,0) = p2->mean.y; x2(2,0) = p2->mean.phi;

        C = !(C1_inv + C2_inv);

        this->cov = C;
        this->enforceCovSymmetry();

        x = C * ( C1_inv*x1 + C2_inv*x2 );

        this->mean.x = x(0,0);
        this->mean.y = x(1,0);
        this->mean.phi = x(2,0);
        this->mean.normalizePhi();
    */
    MRPT_END
}

/*---------------------------------------------------------------
                    inverse
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::inverse(CPose3DPDF& o) const
{
    ASSERT_(o.GetRuntimeClass() == CLASS_ID(CPose3DPDFGaussian));
    auto& out = dynamic_cast<CPose3DPDFGaussian&>(o);

    // This is like: b=(0,0,0)
    //  OUT = b - THIS
    CPose3DPDFGaussian p_zero(
        CPose3D(0, 0, 0, 0, 0, 0), CMatrixDouble66());  // COV=All zeros

    out = p_zero - *this;
}

/*---------------------------------------------------------------
                            +=
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::operator+=(const CPose3D& Ap)
{
    // COV:
    const CMatrixDouble66 OLD_COV = this->cov;
    CMatrixDouble66 df_dx(UNINITIALIZED_MATRIX), df_du(UNINITIALIZED_MATRIX);

    CPose3DPDF::jacobiansPoseComposition(
        this->mean,  // x
        Ap,  // u
        df_dx, df_du);

    // this->cov = H1*this->cov*H1' + H2*Ap.cov*H2';
    cov = mrpt::math::multiply_HCHt(df_dx, OLD_COV);
    // df_du: Nothing to do, since COV(Ap) = zeros

    // MEAN:
    this->mean.composeFrom(this->mean, Ap);
}

/*---------------------------------------------------------------
                            +=
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::operator+=(const CPose3DPDFGaussian& Ap)
{
    // Direct equations (for the covariances) in yaw-pitch-roll are too complex.
    //  Make a way around them and consider instead this path:
    //
    //      X(6D)       U(6D)
    //        |           |
    //        v           v
    //      X(7D)       U(7D)
    //        |           |
    //        +--- (+) ---+
    //              |
    //              v
    //            RES(7D)
    //              |
    //              v
    //            RES(6D)
    //
    CPose3DQuatPDFGaussian X7(*this);
    const CPose3DQuatPDFGaussian U7(Ap);

    X7 += U7;

    this->copyFrom(X7);
}

/*---------------------------------------------------------------
                            -=
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::operator-=(const CPose3DPDFGaussian& Ap)
{
    // Direct equations (for the covariances) in yaw-pitch-roll are too complex.
    //  Make a way around them and consider instead this path:
    //
    //      X(6D)       U(6D)
    //        |           |
    //        v           v
    //      X(7D)       U(7D)
    //        |           |
    //        +--- (-) ---+
    //              |
    //              v
    //            RES(7D)
    //              |
    //              v
    //            RES(6D)
    //
    CPose3DQuatPDFGaussian X7(*this);
    const CPose3DQuatPDFGaussian U7(Ap);

    X7 -= U7;

    this->copyFrom(X7);
}

/*---------------------------------------------------------------
                        evaluatePDF
 ---------------------------------------------------------------*/
double CPose3DPDFGaussian::evaluatePDF([[maybe_unused]] const CPose3D& x) const
{
    THROW_EXCEPTION("TO DO!!!");

    /*  CMatrixD    X(6,1);
        X(0,0) = x.x;
        X(1,0) = x.y;
        X(2,0) = x.z;

        CMatrixD    MU(6,1);
        MU(0,0) = mean.x;
        MU(1,0) = mean.y;
        MU(2,0) = mean.z;

        return math::normalPDF( X, MU, this->cov );
    */
}

/*---------------------------------------------------------------
                        evaluateNormalizedPDF
 ---------------------------------------------------------------*/
double CPose3DPDFGaussian::evaluateNormalizedPDF([
    [maybe_unused]] const CPose3D& x) const
{
    THROW_EXCEPTION("TO DO!!!");
    /*  CMatrixD    X(3,1);
        X(0,0) = x.x;
        X(1,0) = x.y;
        X(2,0) = x.phi;

        CMatrixD    MU(3,1);
        MU(0,0) = mean.x;
        MU(1,0) = mean.y;
        MU(2,0) = mean.phi;

        return math::normalPDF( X, MU, this->cov ) / math::normalPDF( MU, MU,
       this->cov );
    */
}

void CPose3DPDFGaussian::enforceCovSymmetry()
{
    // Differences, when they exist, appear in the ~15'th significant
    //  digit, so... just take one of them arbitrarily!
    for (int i = 0; i < cov.rows() - 1; i++)
        for (int j = i + 1; j < cov.rows(); j++) cov(i, j) = cov(j, i);
}

/*---------------------------------------------------------------
                        mahalanobisDistanceTo
 ---------------------------------------------------------------*/
double CPose3DPDFGaussian::mahalanobisDistanceTo(
    const CPose3DPDFGaussian& theOther)
{
    MRPT_START

    CMatrixDouble66 COV_ = cov + theOther.cov;
    CMatrixDouble61 MU = CMatrixDouble61(theOther.mean) - CMatrixDouble61(mean);

    for (int i = 0; i < 6; i++)
    {
        if (COV_(i, i) == 0)
        {
            if (MU(i, 0) != 0)
                return std::numeric_limits<double>::infinity();
            else
                COV_(i, i) = 1;  // Any arbitrary value since
            // MU(i)=0, and this value doesn't
            // affect the result.
        }
    }

    return std::sqrt(mrpt::math::multiply_HtCH_scalar(MU, COV_.inverse_LLt()));

    MRPT_END
}

/*---------------------------------------------------------------
                        operator <<
 ---------------------------------------------------------------*/
ostream& mrpt::poses::operator<<(ostream& out, const CPose3DPDFGaussian& obj)
{
    out << "Mean: " << obj.mean << "\n";
    out << "Covariance:\n" << obj.cov << "\n";

    return out;
}

/*---------------------------------------------------------------
                        getCovSubmatrix2D
 ---------------------------------------------------------------*/
void CPose3DPDFGaussian::getCovSubmatrix2D(CMatrixDouble& out_cov) const
{
    out_cov.setSize(3, 3);

    for (int i = 0; i < 3; i++)
    {
        int a = i == 2 ? 3 : i;
        for (int j = i; j < 3; j++)
        {
            int b = j == 2 ? 3 : j;
            double f = cov(a, b);
            out_cov(i, j) = f;
            out_cov(j, i) = f;
        }
    }
}

bool mrpt::poses::operator==(
    const CPose3DPDFGaussian& p1, const CPose3DPDFGaussian& p2)
{
    return p1.mean == p2.mean && p1.cov == p2.cov;
}