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00001 /********************************************************************* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Copyright (c) 2008, Willow Garage, Inc. 00005 * All rights reserved. 00006 * 00007 * Redistribution and use in source and binary forms, with or without 00008 * modification, are permitted provided that the following conditions 00009 * are met: 00010 * 00011 * * Redistributions of source code must retain the above copyright 00012 * notice, this list of conditions and the following disclaimer. 00013 * * Redistributions in binary form must reproduce the above 00014 * copyright notice, this list of conditions and the following 00015 * disclaimer in the documentation and/or other materials provided 00016 * with the distribution. 00017 * * Neither the name of the Willow Garage nor the names of its 00018 * contributors may be used to endorse or promote products derived 00019 * from this software without specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00022 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00023 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00024 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00025 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00026 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00027 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00028 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00029 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00030 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00031 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00032 * POSSIBILITY OF SUCH DAMAGE. 00033 *********************************************************************/ 00034 00035 /* Author: Wim Meeussen */ 00036 /* Modified by Alex Noyvirt for SRS */ 00037 00038 00039 #include "srs_people_tracking_filter/gaussian_pos_vel.h" 00040 #include <wrappers/rng/rng.h> 00041 #include <cmath> 00042 #include <cassert> 00043 00044 using namespace tf; 00045 00046 namespace BFL 00047 { 00048 GaussianPosVel::GaussianPosVel (const StatePosVel& mu, const StatePosVel& sigma) 00049 : Pdf<StatePosVel> ( 1 ), 00050 mu_(mu), 00051 sigma_(sigma), 00052 gauss_pos_(mu.pos_, sigma.pos_), 00053 gauss_vel_(mu.vel_, sigma.vel_) 00054 {} 00055 00056 00057 GaussianPosVel::~GaussianPosVel(){} 00058 00059 GaussianPosVel* GaussianPosVel::Clone() const 00060 { 00061 return new GaussianPosVel(mu_, sigma_); 00062 } 00063 00064 std::ostream& operator<< (std::ostream& os, const GaussianPosVel& g) 00065 { 00066 os << "\nMu pos :\n" << g.ExpectedValueGet().pos_ << endl 00067 << "\nMu vel :\n" << g.ExpectedValueGet().vel_ << endl 00068 << "\nSigma:\n" << g.CovarianceGet() << endl; 00069 return os; 00070 } 00071 00072 00073 Probability GaussianPosVel::ProbabilityGet(const StatePosVel& input) const 00074 { 00075 return gauss_pos_.ProbabilityGet(input.pos_) * gauss_vel_.ProbabilityGet(input.vel_); 00076 } 00077 00078 00079 bool 00080 GaussianPosVel::SampleFrom (vector<Sample<StatePosVel> >& list_samples, const int num_samples, int method, void * args) const 00081 { 00082 list_samples.resize(num_samples); 00083 vector<Sample<StatePosVel> >::iterator sample_it = list_samples.begin(); 00084 for (sample_it=list_samples.begin(); sample_it!=list_samples.end(); sample_it++) 00085 SampleFrom( *sample_it, method, args); 00086 00087 return true; 00088 } 00089 00090 00091 bool 00092 GaussianPosVel::SampleFrom (Sample<StatePosVel>& one_sample, int method, void * args) const 00093 { 00094 one_sample.ValueSet( StatePosVel(Vector3(rnorm(mu_.pos_[0], sigma_.pos_[0]*dt_), 00095 rnorm(mu_.pos_[1], sigma_.pos_[1]*dt_), 00096 rnorm(mu_.pos_[2], sigma_.pos_[2]*dt_)), 00097 Vector3(rnorm(mu_.vel_[0], sigma_.vel_[0]*dt_), 00098 rnorm(mu_.vel_[1], sigma_.vel_[1]*dt_), 00099 rnorm(mu_.vel_[2], sigma_.vel_[2]*dt_))) ); 00100 return true; 00101 } 00102 00103 00104 StatePosVel 00105 GaussianPosVel::ExpectedValueGet ( ) const 00106 { 00107 return mu_; 00108 } 00109 00110 SymmetricMatrix 00111 GaussianPosVel::CovarianceGet () const 00112 { 00113 SymmetricMatrix sigma(6); sigma = 0; 00114 for (unsigned int i=0; i<3; i++){ 00115 sigma(i+1,i+1) = pow(sigma_.pos_[i],2); 00116 sigma(i+4,i+4) = pow(sigma_.vel_[i],2); 00117 } 00118 return sigma; 00119 } 00120 00121 } // End namespace BFL