measmodel_pos.cpp

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/* Author: Wim Meeussen */

#include <people_tracking_filter/measmodel_pos.h>

namespace BFL
{
static const unsigned int NUM_MEASMODEL_POS_COND_ARGS   = 1;
static const unsigned int DIM_MEASMODEL_POS             = 13;

// Constructor
MeasPdfPos::MeasPdfPos(const tf::Vector3& sigma)
  : ConditionalPdf<tf::Vector3, StatePosVel>(DIM_MEASMODEL_POS, NUM_MEASMODEL_POS_COND_ARGS),
    meas_noise_(tf::Vector3(0, 0, 0), sigma)
{}

// Destructor
MeasPdfPos::~MeasPdfPos()
{}

Probability
MeasPdfPos::ProbabilityGet(const tf::Vector3& measurement) const
{
  return meas_noise_.ProbabilityGet(measurement - ConditionalArgumentGet(0).pos_);
}

bool
MeasPdfPos::SampleFrom(Sample<tf::Vector3>& one_sample, int method, void *args) const
{
  std::cerr << "MeasPdfPos::SampleFrom Method not applicable" << std::endl;
  assert(0);
  return false;
}

tf::Vector3
MeasPdfPos::ExpectedValueGet() const
{
  std::cerr << "MeasPdfPos::ExpectedValueGet Method not applicable" << std::endl;
  tf::Vector3 result;
  assert(0);
  return result;
}

SymmetricMatrix
MeasPdfPos::CovarianceGet() const
{
  std::cerr << "MeasPdfPos::CovarianceGet Method not applicable" << std::endl;
  SymmetricMatrix Covar(DIM_MEASMODEL_POS);
  assert(0);
  return Covar;
}

void
MeasPdfPos::CovarianceSet(const MatrixWrapper::SymmetricMatrix& cov)
{
  tf::Vector3 cov_vec(sqrt(cov(1, 1)), sqrt(cov(2, 2)), sqrt(cov(3, 3)));
  meas_noise_.sigmaSet(cov_vec);
}
}  // namespace BFL