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<div class="title">CParticleFilterCapable.h</div> </div>
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<a href="_c_particle_filter_capable_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/* +---------------------------------------------------------------------------+</span>
<a name="l00002"></a>00002 <span class="comment"> | The Mobile Robot Programming Toolkit (MRPT) C++ library |</span>
<a name="l00003"></a>00003 <span class="comment"> | |</span>
<a name="l00004"></a>00004 <span class="comment"> | http://www.mrpt.org/ |</span>
<a name="l00005"></a>00005 <span class="comment"> | |</span>
<a name="l00006"></a>00006 <span class="comment"> | Copyright (C) 2005-2011 University of Malaga |</span>
<a name="l00007"></a>00007 <span class="comment"> | |</span>
<a name="l00008"></a>00008 <span class="comment"> | This software was written by the Machine Perception and Intelligent |</span>
<a name="l00009"></a>00009 <span class="comment"> | Robotics Lab, University of Malaga (Spain). |</span>
<a name="l00010"></a>00010 <span class="comment"> | Contact: Jose-Luis Blanco <jlblanco@ctima.uma.es> |</span>
<a name="l00011"></a>00011 <span class="comment"> | |</span>
<a name="l00012"></a>00012 <span class="comment"> | This file is part of the MRPT project. |</span>
<a name="l00013"></a>00013 <span class="comment"> | |</span>
<a name="l00014"></a>00014 <span class="comment"> | MRPT is free software: you can redistribute it and/or modify |</span>
<a name="l00015"></a>00015 <span class="comment"> | it under the terms of the GNU General Public License as published by |</span>
<a name="l00016"></a>00016 <span class="comment"> | the Free Software Foundation, either version 3 of the License, or |</span>
<a name="l00017"></a>00017 <span class="comment"> | (at your option) any later version. |</span>
<a name="l00018"></a>00018 <span class="comment"> | |</span>
<a name="l00019"></a>00019 <span class="comment"> | MRPT is distributed in the hope that it will be useful, |</span>
<a name="l00020"></a>00020 <span class="comment"> | but WITHOUT ANY WARRANTY; without even the implied warranty of |</span>
<a name="l00021"></a>00021 <span class="comment"> | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |</span>
<a name="l00022"></a>00022 <span class="comment"> | GNU General Public License for more details. |</span>
<a name="l00023"></a>00023 <span class="comment"> | |</span>
<a name="l00024"></a>00024 <span class="comment"> | You should have received a copy of the GNU General Public License |</span>
<a name="l00025"></a>00025 <span class="comment"> | along with MRPT. If not, see <http://www.gnu.org/licenses/>. |</span>
<a name="l00026"></a>00026 <span class="comment"> | |</span>
<a name="l00027"></a>00027 <span class="comment"> +---------------------------------------------------------------------------+ */</span>
<a name="l00028"></a>00028 <span class="preprocessor">#ifndef CPARTICLEFILTERCAPABLE_H</span>
<a name="l00029"></a>00029 <span class="preprocessor"></span><span class="preprocessor">#define CPARTICLEFILTERCAPABLE_H</span>
<a name="l00030"></a>00030 <span class="preprocessor"></span>
<a name="l00031"></a>00031 <span class="preprocessor">#include <<a class="code" href="utils__defs_8h.html">mrpt/utils/utils_defs.h</a>></span>
<a name="l00032"></a>00032 <span class="preprocessor">#include <<a class="code" href="_c_particle_filter_8h.html">mrpt/bayes/CParticleFilter.h</a>></span>
<a name="l00033"></a>00033
<a name="l00034"></a>00034 <span class="keyword">namespace </span>mrpt
<a name="l00035"></a>00035 {
<a name="l00036"></a>00036 <span class="keyword">namespace </span>bayes
<a name="l00037"></a>00037 {
<a name="l00038"></a><a class="code" href="_c_particle_filter_capable_8h.html#acf80e35e34b1c4db82ffb680dc74227e">00038</a> <span class="preprocessor"> #define INVALID_LIKELIHOOD_VALUE (-1e300) // An invalid log-likelihood value, used to signal non-initialized likelihood variables.</span>
<a name="l00039"></a>00039 <span class="preprocessor"></span><span class="comment"></span>
<a name="l00040"></a>00040 <span class="comment"> /** This virtual class defines the interface that any particles based PDF class must implement in order to be executed by a mrpt::bayes::CParticleFilter.</span>
<a name="l00041"></a>00041 <span class="comment"> *</span>
<a name="l00042"></a>00042 <span class="comment"> * See the <a href="http://www.mrpt.org/Particle_Filter_Tutorial" >Particle Filter tutorial</a> explaining how to use the particle filter-related classes.</span>
<a name="l00043"></a>00043 <span class="comment"> * \sa CParticleFilter, CParticleFilterData</span>
<a name="l00044"></a>00044 <span class="comment"> * \ingroup mrpt_base_grp</span>
<a name="l00045"></a>00045 <span class="comment"> */</span>
<a name="l00046"></a>00046 <span class="keyword">class </span><a class="code" href="base_2include_2mrpt_2base_2link__pragmas_8h.html#a6045fa0129b1a3d6c8bf895470e66574">BASE_IMPEXP</a> CParticleFilterCapable
<a name="l00047"></a>00047 {
<a name="l00048"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a3afe8d786cf4c244b4f83e02390459c2">00048</a> <span class="keyword">friend</span> <span class="keyword">class </span><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter.html" title="This class acts as a common interface to the different interfaces (see CParticleFilter::TParticleFilt...">CParticleFilter</a>;
<a name="l00049"></a>00049
<a name="l00050"></a>00050 <span class="keyword">private</span>:
<a name="l00051"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a992c733db99a1b0c12015c8ee6f99fbf">00051</a> <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a992c733db99a1b0c12015c8ee6f99fbf">PARTICLE_FILTER_CAPABLE_FAST_DRAW_BINS</a>;
<a name="l00052"></a>00052
<a name="l00053"></a>00053 <span class="keyword">public</span>:
<a name="l00054"></a>00054
<a name="l00055"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a962214fbf62e0ced82450f032c3b65d9">00055</a> <a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html" title="This virtual class defines the interface that any particles based PDF class must implement in order t...">CParticleFilterCapable</a>() : m_fastDrawAuxiliary()
<a name="l00056"></a>00056 { }
<a name="l00057"></a>00057
<a name="l00058"></a>00058 <span class="comment"></span>
<a name="l00059"></a>00059 <span class="comment"> /** Virtual destructor</span>
<a name="l00060"></a>00060 <span class="comment"> */</span>
<a name="l00061"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a7a75d65311441163eba4dacc2a596174">00061</a> <span class="keyword">virtual</span> ~<a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html" title="This virtual class defines the interface that any particles based PDF class must implement in order t...">CParticleFilterCapable</a>()
<a name="l00062"></a>00062 {
<a name="l00063"></a>00063 }
<a name="l00064"></a>00064 <span class="comment"></span>
<a name="l00065"></a>00065 <span class="comment"> /** A callback function type for evaluating the probability of m_particles of being selected, used in "fastDrawSample".</span>
<a name="l00066"></a>00066 <span class="comment"> * The default evaluator function "defaultEvaluator" simply returns the particle weight.</span>
<a name="l00067"></a>00067 <span class="comment"> * \param index This is the index of the particle its probability is being computed.</span>
<a name="l00068"></a>00068 <span class="comment"> * \param action The value of this is the parameter passed to "prepareFastDrawSample"</span>
<a name="l00069"></a>00069 <span class="comment"> * \param observation The value of this is the parameter passed to "prepareFastDrawSample"</span>
<a name="l00070"></a>00070 <span class="comment"> * The action and the observation are declared as "void*" for a greater flexibility.</span>
<a name="l00071"></a>00071 <span class="comment"> * \sa prepareFastDrawSample</span>
<a name="l00072"></a>00072 <span class="comment"> */</span>
<a name="l00073"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a6a77d17782b7527dd6cdd4e024ac9f1b">00073</a> <span class="keyword">typedef</span> double ( *TParticleProbabilityEvaluator) (
<a name="l00074"></a>00074 <span class="keyword">const</span> bayes<a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">::CParticleFilter::TParticleFilterOptions</a> &PF_options,
<a name="l00075"></a>00075 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html" title="This virtual class defines the interface that any particles based PDF class must implement in order t...">CParticleFilterCapable</a> *obj,
<a name="l00076"></a>00076 <span class="keywordtype">size_t</span> index,
<a name="l00077"></a>00077 <span class="keyword">const</span> <span class="keywordtype">void</span> * action,
<a name="l00078"></a>00078 <span class="keyword">const</span> <span class="keywordtype">void</span> * observation );
<a name="l00079"></a>00079 <span class="comment"></span>
<a name="l00080"></a>00080 <span class="comment"> /** The default evaluator function, which simply returns the particle weight.</span>
<a name="l00081"></a>00081 <span class="comment"> * The action and the observation are declared as "void*" for a greater flexibility.</span>
<a name="l00082"></a>00082 <span class="comment"> * \sa prepareFastDrawSample</span>
<a name="l00083"></a>00083 <span class="comment"> */</span>
<a name="l00084"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#aca935576d796515781dfd8456f4c3025">00084</a> <span class="keyword">static</span> <span class="keywordtype">double</span> defaultEvaluator(
<a name="l00085"></a>00085 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options,
<a name="l00086"></a>00086 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html" title="This virtual class defines the interface that any particles based PDF class must implement in order t...">CParticleFilterCapable</a> *obj,
<a name="l00087"></a>00087 <span class="keywordtype">size_t</span> index,
<a name="l00088"></a>00088 <span class="keyword">const</span> <span class="keywordtype">void</span> * action,
<a name="l00089"></a>00089 <span class="keyword">const</span> <span class="keywordtype">void</span> * observation )
<a name="l00090"></a>00090 {
<a name="l00091"></a>00091 <a class="code" href="mrpt__macros_8h.html#acc2e7c5641dd177b8a1c6f2d2470c8b7" title="Can be used to avoid "not used parameters" warnings from the compiler.">MRPT_UNUSED_PARAM</a>(action); <a class="code" href="mrpt__macros_8h.html#acc2e7c5641dd177b8a1c6f2d2470c8b7" title="Can be used to avoid "not used parameters" warnings from the compiler.">MRPT_UNUSED_PARAM</a>(observation);
<a name="l00092"></a>00092 <span class="keywordflow">return</span> obj-><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a6ca16ca0217cdac4b586df5df9cdaea2" title="Access to i'th particle (logarithm) weight, where first one is index 0.">getW</a>(index);
<a name="l00093"></a>00093 }
<a name="l00094"></a>00094 <span class="comment"></span>
<a name="l00095"></a>00095 <span class="comment"> /** Prepares data structures for calling fastDrawSample method next.</span>
<a name="l00096"></a>00096 <span class="comment"> * This method must be called once before using "fastDrawSample" (calling this more than once has no effect, but it takes time for nothing!)</span>
<a name="l00097"></a>00097 <span class="comment"> * The behavior depends on the configuration of the PF (see CParticleFilter::TParticleFilterOptions):</span>
<a name="l00098"></a>00098 <span class="comment"> * - <b>DYNAMIC SAMPLE SIZE=NO</b>: In this case this method fills out an internal array (m_fastDrawAuxiliary.alreadyDrawnIndexes) with</span>
<a name="l00099"></a>00099 <span class="comment"> * the random indexes generated according to the selected resample scheme in TParticleFilterOptions. Those indexes are</span>
<a name="l00100"></a>00100 <span class="comment"> * read sequentially by subsequent calls to fastDrawSample.</span>
<a name="l00101"></a>00101 <span class="comment"> * - <b>DYNAMIC SAMPLE SIZE=YES</b>: Then:</span>
<a name="l00102"></a>00102 <span class="comment"> * - If TParticleFilterOptions.resamplingMethod = prMultinomial, the internal buffers will be filled out (m_fastDrawAuxiliary.CDF, CDF_indexes & PDF) and</span>
<a name="l00103"></a>00103 <span class="comment"> * then fastDrawSample can be called an arbitrary number of times to generate random indexes.</span>
<a name="l00104"></a>00104 <span class="comment"> * - For the rest of resampling algorithms, an exception will be raised since they are not appropriate for a dynamic (unknown in advance) number of particles.</span>
<a name="l00105"></a>00105 <span class="comment"> *</span>
<a name="l00106"></a>00106 <span class="comment"> * The function pointed by "partEvaluator" should take into account the particle filter algorithm selected in "m_PFAlgorithm".</span>
<a name="l00107"></a>00107 <span class="comment"> * If called without arguments (defaultEvaluator), the default behavior is to draw samples with a probability proportional to their current weights.</span>
<a name="l00108"></a>00108 <span class="comment"> * The action and the observation are declared as "void*" for a greater flexibility.</span>
<a name="l00109"></a>00109 <span class="comment"> * For a more detailed information see the <a href="http://www.mrpt.org/Particle_Filters" >Particle Filter tutorial</a>.</span>
<a name="l00110"></a>00110 <span class="comment"> * Custom supplied "partEvaluator" functions must take into account the previous particle weight, i.e. multiplying the current observation likelihood by the weights.</span>
<a name="l00111"></a>00111 <span class="comment"> * \sa fastDrawSample</span>
<a name="l00112"></a>00112 <span class="comment"> */</span>
<a name="l00113"></a>00113 <span class="keywordtype">void</span> prepareFastDrawSample(
<a name="l00114"></a>00114 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options,
<a name="l00115"></a>00115 TParticleProbabilityEvaluator partEvaluator = defaultEvaluator,
<a name="l00116"></a>00116 <span class="keyword">const</span> <span class="keywordtype">void</span> * action = NULL,
<a name="l00117"></a>00117 <span class="keyword">const</span> <span class="keywordtype">void</span> * observation = NULL
<a name="l00118"></a>00118 ) <span class="keyword">const</span>;
<a name="l00119"></a>00119 <span class="comment"></span>
<a name="l00120"></a>00120 <span class="comment"> /** Draws a random sample from the particle filter, in such a way that each particle has a probability proportional to its weight (in the standard PF algorithm).</span>
<a name="l00121"></a>00121 <span class="comment"> * This method can be used to generate a variable number of m_particles when resampling: to vary the number of m_particles in the filter.</span>
<a name="l00122"></a>00122 <span class="comment"> * See prepareFastDrawSample for more information, or the <a href="http://www.mrpt.org/Particle_Filters" >Particle Filter tutorial</a>.</span>
<a name="l00123"></a>00123 <span class="comment"> *</span>
<a name="l00124"></a>00124 <span class="comment"> * NOTES:</span>
<a name="l00125"></a>00125 <span class="comment"> * - You MUST call "prepareFastDrawSample" ONCE before calling this method. That method must be called after modifying the particle filter (executing one step, resampling, etc...)</span>
<a name="l00126"></a>00126 <span class="comment"> * - This method returns ONE index for the selected ("drawn") particle, in the range [0,M-1]</span>
<a name="l00127"></a>00127 <span class="comment"> * - You do not need to call "normalizeWeights" before calling this.</span>
<a name="l00128"></a>00128 <span class="comment"> * \sa prepareFastDrawSample</span>
<a name="l00129"></a>00129 <span class="comment"> */</span>
<a name="l00130"></a>00130 <span class="keywordtype">size_t</span> fastDrawSample( <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options ) <span class="keyword">const</span>;
<a name="l00131"></a>00131 <span class="comment"></span>
<a name="l00132"></a>00132 <span class="comment"> /** Access to i'th particle (logarithm) weight, where first one is index 0.</span>
<a name="l00133"></a>00133 <span class="comment"> */</span>
<a name="l00134"></a>00134 <span class="keyword">virtual</span> <span class="keywordtype">double</span> getW(<span class="keywordtype">size_t</span> i) <span class="keyword">const</span> = 0;
<a name="l00135"></a>00135 <span class="comment"></span>
<a name="l00136"></a>00136 <span class="comment"> /** Modifies i'th particle (logarithm) weight, where first one is index 0.</span>
<a name="l00137"></a>00137 <span class="comment"> */</span>
<a name="l00138"></a>00138 <span class="keyword">virtual</span> <span class="keywordtype">void</span> setW(<span class="keywordtype">size_t</span> i, <span class="keywordtype">double</span> w) = 0;
<a name="l00139"></a>00139 <span class="comment"></span>
<a name="l00140"></a>00140 <span class="comment"> /** Get the m_particles count.</span>
<a name="l00141"></a>00141 <span class="comment"> */</span>
<a name="l00142"></a>00142 <span class="keyword">virtual</span> <span class="keywordtype">size_t</span> particlesCount() <span class="keyword">const</span> = 0;
<a name="l00143"></a>00143 <span class="comment"></span>
<a name="l00144"></a>00144 <span class="comment"> /** Performs the prediction stage of the Particle Filter.</span>
<a name="l00145"></a>00145 <span class="comment"> * This method simply selects the appropiate protected method according to the particle filter algorithm to run.</span>
<a name="l00146"></a>00146 <span class="comment"> * \sa prediction_and_update_pfStandardProposal,prediction_and_update_pfAuxiliaryPFStandard,prediction_and_update_pfOptimalProposal,prediction_and_update_pfAuxiliaryPFOptimal</span>
<a name="l00147"></a>00147 <span class="comment"> */</span>
<a name="l00148"></a>00148 <span class="keywordtype">void</span> prediction_and_update(
<a name="l00149"></a>00149 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_action_collection.html" title="Declares a class for storing a collection of robot actions.">mrpt::slam::CActionCollection</a> * action,
<a name="l00150"></a>00150 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_sensory_frame.html" title="Declares a class for storing a "sensory frame", a set of "observations" taken by the robot approximat...">mrpt::slam::CSensoryFrame</a> * observation,
<a name="l00151"></a>00151 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options
<a name="l00152"></a>00152 );
<a name="l00153"></a>00153 <span class="comment"></span>
<a name="l00154"></a>00154 <span class="comment"> /** Performs the substitution for internal use of resample in particle filter algorithm, don't call it directly.</span>
<a name="l00155"></a>00155 <span class="comment"> * \param indx The indices of current m_particles to be saved as the new m_particles set.</span>
<a name="l00156"></a>00156 <span class="comment"> */</span>
<a name="l00157"></a>00157 <span class="keyword">virtual</span> <span class="keywordtype">void</span> performSubstitution( <span class="keyword">const</span> <a class="code" href="classstd_1_1vector.html">std::vector<size_t></a> &indx) = 0;
<a name="l00158"></a>00158 <span class="comment"></span>
<a name="l00159"></a>00159 <span class="comment"> /** Normalize the (logarithmic) weights, such as the maximum weight is zero.</span>
<a name="l00160"></a>00160 <span class="comment"> * \param out_max_log_w If provided, will return with the maximum log_w before normalizing, such as new_weights = old_weights - max_log_w.</span>
<a name="l00161"></a>00161 <span class="comment"> * \return The max/min ratio of weights ("dynamic range")</span>
<a name="l00162"></a>00162 <span class="comment"> */</span>
<a name="l00163"></a>00163 <span class="keyword">virtual</span> <span class="keywordtype">double</span> normalizeWeights( <span class="keywordtype">double</span> *out_max_log_w = NULL ) =0;
<a name="l00164"></a>00164 <span class="comment"></span>
<a name="l00165"></a>00165 <span class="comment"> /** Returns the normalized ESS (Estimated Sample Size), in the range [0,1].</span>
<a name="l00166"></a>00166 <span class="comment"> * Note that you do NOT need to normalize the weights before calling this.</span>
<a name="l00167"></a>00167 <span class="comment"> */</span>
<a name="l00168"></a>00168 <span class="keyword">virtual</span> <span class="keywordtype">double</span> ESS() = 0;
<a name="l00169"></a>00169 <span class="comment"></span>
<a name="l00170"></a>00170 <span class="comment"> /** Performs a resample of the m_particles, using the method selected in the constructor.</span>
<a name="l00171"></a>00171 <span class="comment"> * After computing the surviving samples, this method internally calls "performSubstitution" to actually perform the particle replacement.</span>
<a name="l00172"></a>00172 <span class="comment"> * This method is called automatically by CParticleFilter::execute, andshould not be invoked manually normally.</span>
<a name="l00173"></a>00173 <span class="comment"> * To just obtaining the sequence of resampled indexes from a sequence of weights, use "resample"</span>
<a name="l00174"></a>00174 <span class="comment"> * \sa resample</span>
<a name="l00175"></a>00175 <span class="comment"> */</span>
<a name="l00176"></a>00176 <span class="keywordtype">void</span> performResampling( <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options );
<a name="l00177"></a>00177 <span class="comment"></span>
<a name="l00178"></a>00178 <span class="comment"> /** A static method to perform the computation of the samples resulting from resampling a given set of particles, given their logarithmic weights, and a resampling method.</span>
<a name="l00179"></a>00179 <span class="comment"> * It returns the sequence of indexes from the resampling. The number of output samples is the same than the input population.</span>
<a name="l00180"></a>00180 <span class="comment"> * This generic method just computes these indexes, to actually perform a resampling in a particle filter object, call performResampling</span>
<a name="l00181"></a>00181 <span class="comment"> * \sa performResampling</span>
<a name="l00182"></a>00182 <span class="comment"> */</span>
<a name="l00183"></a>00183 <span class="keyword">static</span> <span class="keywordtype">void</span> computeResampling(
<a name="l00184"></a>00184 <a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter.html#a5a2e5c42fba6719b5f2f4b8fa1f4154c" title="Defines the different resampling algorithms.">CParticleFilter::TParticleResamplingAlgorithm</a> method,
<a name="l00185"></a>00185 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1dynamicsize__vector.html" title="The base class of MRPT vectors, actually, Eigen column matrices of dynamic size with specialized cons...">vector_double</a> &in_logWeights,
<a name="l00186"></a>00186 <a class="code" href="classstd_1_1vector.html">std::vector<size_t></a> &out_indexes
<a name="l00187"></a>00187 );
<a name="l00188"></a>00188 <span class="comment"></span>
<a name="l00189"></a>00189 <span class="comment"> /** A static method to compute the linear, normalized (the sum the unity) weights from log-weights.</span>
<a name="l00190"></a>00190 <span class="comment"> * \sa performResampling</span>
<a name="l00191"></a>00191 <span class="comment"> */</span>
<a name="l00192"></a>00192 <span class="keyword">static</span> <span class="keywordtype">void</span> log2linearWeights(
<a name="l00193"></a>00193 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1dynamicsize__vector.html" title="The base class of MRPT vectors, actually, Eigen column matrices of dynamic size with specialized cons...">vector_double</a> &in_logWeights,
<a name="l00194"></a>00194 <a class="code" href="structmrpt_1_1dynamicsize__vector.html" title="The base class of MRPT vectors, actually, Eigen column matrices of dynamic size with specialized cons...">vector_double</a> &out_linWeights );
<a name="l00195"></a>00195
<a name="l00196"></a>00196
<a name="l00197"></a>00197 <span class="keyword">protected</span>:<span class="comment"></span>
<a name="l00198"></a>00198 <span class="comment"> /** Performs the particle filter prediction/update stages for the algorithm "pfStandardProposal" (if not implemented in heritated class, it will raise a 'non-implemented' exception).</span>
<a name="l00199"></a>00199 <span class="comment"> * \sa prediction_and_update</span>
<a name="l00200"></a>00200 <span class="comment"> */</span>
<a name="l00201"></a>00201 <span class="keyword">virtual</span> <span class="keywordtype">void</span> prediction_and_update_pfStandardProposal(
<a name="l00202"></a>00202 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_action_collection.html" title="Declares a class for storing a collection of robot actions.">mrpt::slam::CActionCollection</a> * action,
<a name="l00203"></a>00203 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_sensory_frame.html" title="Declares a class for storing a "sensory frame", a set of "observations" taken by the robot approximat...">mrpt::slam::CSensoryFrame</a> * observation,
<a name="l00204"></a>00204 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options );<span class="comment"></span>
<a name="l00205"></a>00205 <span class="comment"> /** Performs the particle filter prediction/update stages for the algorithm "pfAuxiliaryPFStandard" (if not implemented in heritated class, it will raise a 'non-implemented' exception).</span>
<a name="l00206"></a>00206 <span class="comment"> * \sa prediction_and_update</span>
<a name="l00207"></a>00207 <span class="comment"> */</span>
<a name="l00208"></a>00208 <span class="keyword">virtual</span> <span class="keywordtype">void</span> prediction_and_update_pfAuxiliaryPFStandard(
<a name="l00209"></a>00209 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_action_collection.html" title="Declares a class for storing a collection of robot actions.">mrpt::slam::CActionCollection</a> * action,
<a name="l00210"></a>00210 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_sensory_frame.html" title="Declares a class for storing a "sensory frame", a set of "observations" taken by the robot approximat...">mrpt::slam::CSensoryFrame</a> * observation,
<a name="l00211"></a>00211 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options );<span class="comment"></span>
<a name="l00212"></a>00212 <span class="comment"> /** Performs the particle filter prediction/update stages for the algorithm "pfOptimalProposal" (if not implemented in heritated class, it will raise a 'non-implemented' exception).</span>
<a name="l00213"></a>00213 <span class="comment"> * \sa prediction_and_update</span>
<a name="l00214"></a>00214 <span class="comment"> */</span>
<a name="l00215"></a>00215 <span class="keyword">virtual</span> <span class="keywordtype">void</span> prediction_and_update_pfOptimalProposal(
<a name="l00216"></a>00216 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_action_collection.html" title="Declares a class for storing a collection of robot actions.">mrpt::slam::CActionCollection</a> * action,
<a name="l00217"></a>00217 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_sensory_frame.html" title="Declares a class for storing a "sensory frame", a set of "observations" taken by the robot approximat...">mrpt::slam::CSensoryFrame</a> * observation,
<a name="l00218"></a>00218 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options );<span class="comment"></span>
<a name="l00219"></a>00219 <span class="comment"> /** Performs the particle filter prediction/update stages for the algorithm "pfAuxiliaryPFOptimal" (if not implemented in heritated class, it will raise a 'non-implemented' exception).</span>
<a name="l00220"></a>00220 <span class="comment"> * \sa prediction_and_update</span>
<a name="l00221"></a>00221 <span class="comment"> */</span>
<a name="l00222"></a>00222 <span class="keyword">virtual</span> <span class="keywordtype">void</span> prediction_and_update_pfAuxiliaryPFOptimal(
<a name="l00223"></a>00223 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_action_collection.html" title="Declares a class for storing a collection of robot actions.">mrpt::slam::CActionCollection</a> * action,
<a name="l00224"></a>00224 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1slam_1_1_c_sensory_frame.html" title="Declares a class for storing a "sensory frame", a set of "observations" taken by the robot approximat...">mrpt::slam::CSensoryFrame</a> * observation,
<a name="l00225"></a>00225 <span class="keyword">const</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_1_1_t_particle_filter_options.html" title="The configuration of a particle filter.">bayes::CParticleFilter::TParticleFilterOptions</a> &PF_options );
<a name="l00226"></a>00226 <span class="comment"></span>
<a name="l00227"></a>00227 <span class="comment"> /** Auxiliary vectors, see CParticleFilterCapable::prepareFastDrawSample for more information</span>
<a name="l00228"></a>00228 <span class="comment"> */</span>
<a name="l00229"></a>00229 <span class="keyword">struct </span><a class="code" href="base_2include_2mrpt_2base_2link__pragmas_8h.html#a6045fa0129b1a3d6c8bf895470e66574">BASE_IMPEXP</a> TFastDrawAuxVars
<a name="l00230"></a>00230 {
<a name="l00231"></a><a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#aa351f48eed1b2a609c3ceb76dae31354">00231</a> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html" title="Auxiliary vectors, see CParticleFilterCapable::prepareFastDrawSample for more information.">TFastDrawAuxVars</a>() :
<a name="l00232"></a>00232 CDF(),
<a name="l00233"></a>00233 CDF_indexes(),
<a name="l00234"></a>00234 PDF(),
<a name="l00235"></a>00235 alreadyDrawnIndexes(),
<a name="l00236"></a>00236 alreadyDrawnNextOne(0)
<a name="l00237"></a>00237 { }
<a name="l00238"></a>00238
<a name="l00239"></a><a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#a7155cd1e5580f020e716560c7504dd27">00239</a> <a class="code" href="structmrpt_1_1dynamicsize__vector.html" title="The base class of MRPT vectors, actually, Eigen column matrices of dynamic size with specialized cons...">vector_double</a> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#a7155cd1e5580f020e716560c7504dd27">CDF</a>;
<a name="l00240"></a><a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#a3956e2035d9883b58e02f6d67435cf4f">00240</a> <a class="code" href="classstd_1_1vector.html" title="STL class.">vector_uint</a> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#a3956e2035d9883b58e02f6d67435cf4f">CDF_indexes</a>;
<a name="l00241"></a><a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#a78de64fdb55518d1f2876109bfa2b7ae">00241</a> <a class="code" href="structmrpt_1_1dynamicsize__vector.html" title="The base class of MRPT vectors, actually, Eigen column matrices of dynamic size with specialized cons...">vector_double</a> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#a78de64fdb55518d1f2876109bfa2b7ae">PDF</a>;
<a name="l00242"></a>00242
<a name="l00243"></a><a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#af5570e5c880e9c1dfc370761f4348ffd">00243</a> <a class="code" href="classstd_1_1vector.html" title="STL class.">vector_uint</a> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#af5570e5c880e9c1dfc370761f4348ffd">alreadyDrawnIndexes</a>;
<a name="l00244"></a><a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#abd9be7ca7cc6b44548c4e15a31583981">00244</a> <span class="keywordtype">size_t</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html#abd9be7ca7cc6b44548c4e15a31583981">alreadyDrawnNextOne</a>;
<a name="l00245"></a>00245 };
<a name="l00246"></a>00246 <span class="comment"></span>
<a name="l00247"></a>00247 <span class="comment"> /** Auxiliary vectors, see CParticleFilterCapable::prepareFastDrawSample for more information</span>
<a name="l00248"></a>00248 <span class="comment"> */</span>
<a name="l00249"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a0f9ce972442bcd3324711dd2211ce659">00249</a> <span class="keyword">mutable</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_particle_filter_capable_1_1_t_fast_draw_aux_vars.html" title="Auxiliary vectors, see CParticleFilterCapable::prepareFastDrawSample for more information.">TFastDrawAuxVars</a> <a class="code" href="classmrpt_1_1bayes_1_1_c_particle_filter_capable.html#a0f9ce972442bcd3324711dd2211ce659" title="Auxiliary vectors, see CParticleFilterCapable::prepareFastDrawSample for more information.">m_fastDrawAuxiliary</a>;
<a name="l00250"></a>00250
<a name="l00251"></a>00251 }; <span class="comment">// End of class def.</span>
<a name="l00252"></a>00252
<a name="l00253"></a>00253 } <span class="comment">// end namespace</span>
<a name="l00254"></a>00254 } <span class="comment">// end namespace</span>
<a name="l00255"></a>00255 <span class="preprocessor">#endif</span>
</pre></div></div>
</div>
<br><hr><br> <table border="0" width="100%"> <tr> <td> Page generated by <a href="http://www.doxygen.org" target="_blank">Doxygen 1.7.5</a> for MRPT 0.9.5 SVN: at Sun Sep 25 17:20:18 UTC 2011</td><td></td> <td width="100"> </td> <td width="150"> </td></tr> </table> </body></html>
