gaussian_pos_vel.cpp
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00034 
00035 /* Author: Wim Meeussen */
00036 
00037 
00038 #include "people_tracking_filter/gaussian_pos_vel.h"
00039 #include <wrappers/rng/rng.h>
00040 #include <cmath>
00041 #include <cassert>
00042 
00043 using namespace tf;
00044 
00045 namespace BFL
00046 {
00047 GaussianPosVel::GaussianPosVel(const StatePosVel& mu, const StatePosVel& sigma)
00048   : Pdf<StatePosVel> (1),
00049     mu_(mu),
00050     sigma_(sigma),
00051     gauss_pos_(mu.pos_, sigma.pos_),
00052     gauss_vel_(mu.vel_, sigma.vel_)
00053 {}
00054 
00055 
00056 GaussianPosVel::~GaussianPosVel() {}
00057 
00058 GaussianPosVel* GaussianPosVel::Clone() const
00059 {
00060   return new GaussianPosVel(mu_, sigma_);
00061 }
00062 
00063 std::ostream& operator<< (std::ostream& os, const GaussianPosVel& g)
00064 {
00065   os << "\nMu pos :\n"    << g.ExpectedValueGet().pos_ << endl
00066      << "\nMu vel :\n"    << g.ExpectedValueGet().vel_ << endl
00067      << "\nSigma:\n" << g.CovarianceGet() << endl;
00068   return os;
00069 }
00070 
00071 
00072 Probability GaussianPosVel::ProbabilityGet(const StatePosVel& input) const
00073 {
00074   return gauss_pos_.ProbabilityGet(input.pos_) * gauss_vel_.ProbabilityGet(input.vel_);
00075 }
00076 
00077 
00078 bool
00079 GaussianPosVel::SampleFrom(vector<Sample<StatePosVel> >& list_samples, const int num_samples, int method, void * args) const
00080 {
00081   list_samples.resize(num_samples);
00082   vector<Sample<StatePosVel> >::iterator sample_it = list_samples.begin();
00083   for (sample_it = list_samples.begin(); sample_it != list_samples.end(); sample_it++)
00084     SampleFrom(*sample_it, method, args);
00085 
00086   return true;
00087 }
00088 
00089 
00090 bool
00091 GaussianPosVel::SampleFrom(Sample<StatePosVel>& one_sample, int method, void * args) const
00092 {
00093   one_sample.ValueSet(StatePosVel(Vector3(rnorm(mu_.pos_[0], sigma_.pos_[0]*dt_),
00094                                           rnorm(mu_.pos_[1], sigma_.pos_[1]*dt_),
00095                                           rnorm(mu_.pos_[2], sigma_.pos_[2]*dt_)),
00096                                   Vector3(rnorm(mu_.vel_[0], sigma_.vel_[0]*dt_),
00097                                           rnorm(mu_.vel_[1], sigma_.vel_[1]*dt_),
00098                                           rnorm(mu_.vel_[2], sigma_.vel_[2]*dt_))));
00099   return true;
00100 }
00101 
00102 
00103 StatePosVel
00104 GaussianPosVel::ExpectedValueGet() const
00105 {
00106   return mu_;
00107 }
00108 
00109 SymmetricMatrix
00110 GaussianPosVel::CovarianceGet() const
00111 {
00112   SymmetricMatrix sigma(6);
00113   sigma = 0;
00114   for (unsigned int i = 0; i < 3; i++)
00115   {
00116     sigma(i + 1, i + 1) = pow(sigma_.pos_[i], 2);
00117     sigma(i + 4, i + 4) = pow(sigma_.vel_[i], 2);
00118   }
00119   return sigma;
00120 }
00121 
00122 } // End namespace BFL


people_tracking_filter
Author(s): Caroline Pantofaru
autogenerated on Sat Jun 8 2019 18:40:22