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<div class="title">CPosePDFGaussianInf.h</div> </div>
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<a href="_c_pose_p_d_f_gaussian_inf_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 CPosePDFGaussianInf_H</span>
<a name="l00029"></a>00029 <span class="preprocessor"></span><span class="preprocessor">#define CPosePDFGaussianInf_H</span>
<a name="l00030"></a>00030 <span class="preprocessor"></span>
<a name="l00031"></a>00031 <span class="preprocessor">#include <<a class="code" href="_c_pose_p_d_f_8h.html">mrpt/poses/CPosePDF.h</a>></span>
<a name="l00032"></a>00032 <span class="preprocessor">#include <<a class="code" href="_c_matrix_fixed_numeric_8h.html">mrpt/math/CMatrixFixedNumeric.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>poses
<a name="l00037"></a>00037 {
<a name="l00038"></a>00038 <span class="keyword">using namespace </span>mrpt::math;
<a name="l00039"></a>00039
<a name="l00040"></a>00040 <span class="keyword">class </span>CPose3DPDF;
<a name="l00041"></a>00041
<a name="l00042"></a>00042 <span class="comment">// This must be added to any CSerializable derived class:</span>
<a name="l00043"></a><a class="code" href="structmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf_ptr.html#a88248dbdd88c0eba273615ad53e3863b">00043</a> <a class="code" href="_c_serializable_8h.html#ab89b7a3de0a1baf5a5af4454add7d0f8" title="This declaration must be inserted in all CSerializable classes definition, before the class declarati...">DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE</a>( <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a>, <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f.html" title="Declares a class that represents a probability density function (pdf) of a 2D pose (x...">CPosePDF</a> )
<a name="l00044"></a>00044
<a name="l00045"></a>00045 <span class="comment">/** A Probability Density function (PDF) of a 2D pose \f$ p(\mathbf{x}) = [x ~ y ~ \phi ]^t \f$ as a Gaussian with a mean and the inverse of the covariance.</span>
<a name="l00046"></a>00046 <span class="comment"> *</span>
<a name="l00047"></a>00047 <span class="comment"> * This class implements a PDF as a mono-modal Gaussian distribution in its <b>information form</b>, that is,</span>
<a name="l00048"></a>00048 <span class="comment"> * keeping the inverse of the covariance matrix instead of the covariance matrix itself.</span>
<a name="l00049"></a>00049 <span class="comment"> *</span>
<a name="l00050"></a>00050 <span class="comment"> * This class is the dual of CPosePDFGaussian.</span>
<a name="l00051"></a>00051 <span class="comment"> *</span>
<a name="l00052"></a>00052 <span class="comment"> * \sa CPose2D, CPosePDF, CPosePDFParticles</span>
<a name="l00053"></a>00053 <span class="comment"> * \ingroup poses_pdf_grp</span>
<a name="l00054"></a>00054 <span class="comment"> */</span>
<a name="l00055"></a>00055 class <a class="code" href="base_2include_2mrpt_2base_2link__pragmas_8h.html#a6045fa0129b1a3d6c8bf895470e66574">BASE_IMPEXP</a> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> : public <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f.html" title="Declares a class that represents a probability density function (pdf) of a 2D pose (x...">CPosePDF</a>
<a name="l00056"></a>00056 {
<a name="l00057"></a>00057 <span class="comment">// This must be added to any CSerializable derived class:</span>
<a name="l00058"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#ab276a8592a859accdf378e899ab59ccf">00058</a> <a class="code" href="_c_serializable_8h.html#a72ab55bf7ae009c89b75715cfa21e84d" title="This declaration must be inserted in all CSerializable classes definition, within the class declarati...">DEFINE_SERIALIZABLE</a>( <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> )
<a name="l00059"></a>00059
<a name="l00060"></a>00060 protected:<span class="comment"></span>
<a name="l00061"></a>00061 <span class="comment"> /** Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)</span>
<a name="l00062"></a>00062 <span class="comment"> */</span>
<a name="l00063"></a>00063 <span class="keywordtype">void</span> assureSymmetry();
<a name="l00064"></a>00064
<a name="l00065"></a>00065 public:<span class="comment"></span>
<a name="l00066"></a>00066 <span class="comment"> /** @name Data fields</span>
<a name="l00067"></a>00067 <span class="comment"> @{ */</span>
<a name="l00068"></a>00068
<a name="l00069"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#ad7ca9a20eeb844d44b72d306e3185a1d">00069</a> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> <a class="code" href="eigen__plugins_8h.html#a378ef7ee1218e4aa29b595c6e0f8ee4a" title="Computes the mean of the entire matrix.">mean</a>; <span class="comment">//!< The mean value</span>
<a name="l00070"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#a587a5280102e9da590535670249e0c0c">00070</a> <span class="comment"></span> <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixDouble33</a> cov_inv; <span class="comment">//!< The inverse of the 3x3 covariance matrix (the "information" matrix)</span>
<a name="l00071"></a>00071 <span class="comment"></span><span class="comment"></span>
<a name="l00072"></a>00072 <span class="comment"> /** @} */</span>
<a name="l00073"></a>00073
<a name="l00074"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#a61abdcd4106d875473a14c091db12b1a">00074</a> inline const <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> & getPoseMean()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="eigen__plugins_8h.html#a378ef7ee1218e4aa29b595c6e0f8ee4a" title="Computes the mean of the entire matrix.">mean</a>; }
<a name="l00075"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#a192ed469cad0982db28bda8e9fe4a0e6">00075</a> <span class="keyword">inline</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> & <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#a192ed469cad0982db28bda8e9fe4a0e6">getPoseMean</a>() { <span class="keywordflow">return</span> <a class="code" href="eigen__plugins_8h.html#a378ef7ee1218e4aa29b595c6e0f8ee4a" title="Computes the mean of the entire matrix.">mean</a>; }
<a name="l00076"></a>00076 <span class="comment"></span>
<a name="l00077"></a>00077 <span class="comment"> /** Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!) */</span>
<a name="l00078"></a>00078 <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a>();
<a name="l00079"></a>00079 <span class="comment"></span>
<a name="l00080"></a>00080 <span class="comment"> /** Constructor with a mean value (inverse covariance=all zeros -> so be careful!) */</span>
<a name="l00081"></a>00081 <span class="keyword">explicit</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &init_Mean );
<a name="l00082"></a>00082 <span class="comment"></span>
<a name="l00083"></a>00083 <span class="comment"> /** Constructor */</span>
<a name="l00084"></a>00084 <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &init_Mean, <span class="keyword">const</span> <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixDouble33</a> &init_CovInv );
<a name="l00085"></a>00085 <span class="comment"></span>
<a name="l00086"></a>00086 <span class="comment"> /** Copy constructor, including transformations between other PDFs */</span>
<a name="l00087"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#ad209018a285d32552887876c11a68c86">00087</a> <span class="keyword">explicit</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#ad209018a285d32552887876c11a68c86" title="Copy constructor, including transformations between other PDFs.">CPosePDFGaussianInf</a>( <span class="keyword">const</span> CPosePDF &o ) { copyFrom( o ); }
<a name="l00088"></a>00088 <span class="comment"></span>
<a name="l00089"></a>00089 <span class="comment"> /** Copy constructor, including transformations between other PDFs */</span>
<a name="l00090"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#aba5c24c498c9472873c73b5cd9ec4928">00090</a> <span class="keyword">explicit</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#aba5c24c498c9472873c73b5cd9ec4928" title="Copy constructor, including transformations between other PDFs.">CPosePDFGaussianInf</a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose3_d_p_d_f.html" title="Declares a class that represents a Probability Density Function (PDF) of a 3D pose (6D actually)...">CPose3DPDF</a> &o ) { copyFrom( o ); }
<a name="l00091"></a>00091
<a name="l00092"></a>00092 <span class="comment"></span>
<a name="l00093"></a>00093 <span class="comment"> /** Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).</span>
<a name="l00094"></a>00094 <span class="comment"> * \sa getCovariance</span>
<a name="l00095"></a>00095 <span class="comment"> */</span>
<a name="l00096"></a>00096 <span class="keywordtype">void</span> getMean(<a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &mean_pose) <span class="keyword">const</span>;
<a name="l00097"></a>00097 <span class="comment"></span>
<a name="l00098"></a>00098 <span class="comment"> /** Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.</span>
<a name="l00099"></a>00099 <span class="comment"> * \sa getMean</span>
<a name="l00100"></a>00100 <span class="comment"> */</span>
<a name="l00101"></a>00101 <span class="keywordtype">void</span> getCovarianceAndMean(<a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixDouble33</a> &<a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>,<a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &mean_point) <span class="keyword">const</span>;
<a name="l00102"></a>00102 <span class="comment"></span>
<a name="l00103"></a>00103 <span class="comment"> /** Copy operator, translating if necesary (for example, between particles and gaussian representations)</span>
<a name="l00104"></a>00104 <span class="comment"> */</span>
<a name="l00105"></a>00105 <span class="keywordtype">void</span> copyFrom(<span class="keyword">const</span> CPosePDF &o);
<a name="l00106"></a>00106 <span class="comment"></span>
<a name="l00107"></a>00107 <span class="comment"> /** Copy operator, translating if necesary (for example, between particles and gaussian representations)</span>
<a name="l00108"></a>00108 <span class="comment"> */</span>
<a name="l00109"></a>00109 <span class="keywordtype">void</span> copyFrom(<span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose3_d_p_d_f.html" title="Declares a class that represents a Probability Density Function (PDF) of a 3D pose (6D actually)...">CPose3DPDF</a> &o);
<a name="l00110"></a>00110 <span class="comment"></span>
<a name="l00111"></a>00111 <span class="comment"> /** Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines.</span>
<a name="l00112"></a>00112 <span class="comment"> */</span>
<a name="l00113"></a>00113 <span class="keywordtype">void</span> <a class="code" href="eigen__plugins_8h.html#abea6659e38ab7a50b625ea1a4af3ec72" title="Save matrix to a text file, compatible with MATLAB text format (see also the methods of matrix classe...">saveToTextFile</a>(<span class="keyword">const</span> <a class="code" href="classstd_1_1string.html" title="STL class.">std::string</a> &file) <span class="keyword">const</span>;
<a name="l00114"></a>00114 <span class="comment"></span>
<a name="l00115"></a>00115 <span class="comment"> /** This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which</span>
<a name="l00116"></a>00116 <span class="comment"> * "to project" the current pdf. Result PDF substituted the currently stored one in the object.</span>
<a name="l00117"></a>00117 <span class="comment"> */</span>
<a name="l00118"></a>00118 <span class="keywordtype">void</span> changeCoordinatesReference( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose3_d.html" title="A class used to store a 3D pose (a 3D translation + a rotation in 3D).">CPose3D</a> &newReferenceBase );
<a name="l00119"></a>00119 <span class="comment"></span>
<a name="l00120"></a>00120 <span class="comment"> /** This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which</span>
<a name="l00121"></a>00121 <span class="comment"> * "to project" the current pdf. Result PDF substituted the currently stored one in the object.</span>
<a name="l00122"></a>00122 <span class="comment"> */</span>
<a name="l00123"></a>00123 <span class="keywordtype">void</span> changeCoordinatesReference( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &newReferenceBase );
<a name="l00124"></a>00124 <span class="comment"></span>
<a name="l00125"></a>00125 <span class="comment"> /** Rotate the covariance matrix by replacing it by \f$ \mathbf{R}~\mathbf{COV}~\mathbf{R}^t \f$, where \f$ \mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right] \f$.</span>
<a name="l00126"></a>00126 <span class="comment"> */</span>
<a name="l00127"></a>00127 <span class="keywordtype">void</span> rotateCov(<span class="keyword">const</span> <span class="keywordtype">double</span> ang);
<a name="l00128"></a>00128 <span class="comment"></span>
<a name="l00129"></a>00129 <span class="comment"> /** Set \f$ this = x1 \ominus x0 \f$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (For 'x0' and 'x1' being independent variables!).</span>
<a name="l00130"></a>00130 <span class="comment"> */</span>
<a name="l00131"></a>00131 <span class="keywordtype">void</span> inverseComposition( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &x, <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &ref );
<a name="l00132"></a>00132 <span class="comment"></span>
<a name="l00133"></a>00133 <span class="comment"> /** Set \f$ this = x1 \ominus x0 \f$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (Given the 3x3 cross-covariance matrix of variables x0 and x1).</span>
<a name="l00134"></a>00134 <span class="comment"> */</span>
<a name="l00135"></a>00135 <span class="keywordtype">void</span> inverseComposition(
<a name="l00136"></a>00136 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &x1,
<a name="l00137"></a>00137 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &x0,
<a name="l00138"></a>00138 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixDouble33</a> &COV_01
<a name="l00139"></a>00139 );
<a name="l00140"></a>00140 <span class="comment"></span>
<a name="l00141"></a>00141 <span class="comment"> /** Draws a single sample from the distribution</span>
<a name="l00142"></a>00142 <span class="comment"> */</span>
<a name="l00143"></a>00143 <span class="keywordtype">void</span> drawSingleSample( <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &outPart ) <span class="keyword">const</span>;
<a name="l00144"></a>00144 <span class="comment"></span>
<a name="l00145"></a>00145 <span class="comment"> /** Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum.</span>
<a name="l00146"></a>00146 <span class="comment"> */</span>
<a name="l00147"></a>00147 <span class="keywordtype">void</span> drawManySamples( <span class="keywordtype">size_t</span> N, <a class="code" href="classstd_1_1vector.html">std::vector<vector_double></a> & outSamples ) <span class="keyword">const</span>;
<a name="l00148"></a>00148 <span class="comment"></span>
<a name="l00149"></a>00149 <span class="comment"> /** Bayesian fusion of two points gauss. distributions, then save the result in this object.</span>
<a name="l00150"></a>00150 <span class="comment"> * The process is as follows:<br></span>
<a name="l00151"></a>00151 <span class="comment"> * - (x1,S1): Mean and variance of the p1 distribution.</span>
<a name="l00152"></a>00152 <span class="comment"> * - (x2,S2): Mean and variance of the p2 distribution.</span>
<a name="l00153"></a>00153 <span class="comment"> * - (x,S): Mean and variance of the resulting distribution.</span>
<a name="l00154"></a>00154 <span class="comment"> *</span>
<a name="l00155"></a>00155 <span class="comment"> * S = (S1<sup>-1</sup> + S2<sup>-1</sup>)<sup>-1</sup>;</span>
<a name="l00156"></a>00156 <span class="comment"> * x = S * ( S1<sup>-1</sup>*x1 + S2<sup>-1</sup>*x2 );</span>
<a name="l00157"></a>00157 <span class="comment"> */</span>
<a name="l00158"></a>00158 <span class="keywordtype">void</span> bayesianFusion(<span class="keyword">const</span> CPosePDF &p1,<span class="keyword">const</span> CPosePDF &p2, <span class="keyword">const</span> <span class="keywordtype">double</span> &minMahalanobisDistToDrop = 0 );
<a name="l00159"></a>00159 <span class="comment"></span>
<a name="l00160"></a>00160 <span class="comment"> /** Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF</span>
<a name="l00161"></a>00161 <span class="comment"> */</span>
<a name="l00162"></a>00162 <span class="keywordtype">void</span> inverse(CPosePDF &o) <span class="keyword">const</span>;
<a name="l00163"></a>00163 <span class="comment"></span>
<a name="l00164"></a>00164 <span class="comment"> /** Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated). */</span>
<a name="l00165"></a>00165 <span class="keywordtype">void</span> <a class="code" href="group__container__ops__grp.html#ga28127b8dfe78fea7644c4f2a3517cdef" title="a+=b (element-wise sum)">operator += </a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &Ap);
<a name="l00166"></a>00166 <span class="comment"></span>
<a name="l00167"></a>00167 <span class="comment"> /** Evaluates the PDF at a given point.</span>
<a name="l00168"></a>00168 <span class="comment"> */</span>
<a name="l00169"></a>00169 <span class="keywordtype">double</span> evaluatePDF( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &x ) <span class="keyword">const</span>;
<a name="l00170"></a>00170 <span class="comment"></span>
<a name="l00171"></a>00171 <span class="comment"> /** Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1].</span>
<a name="l00172"></a>00172 <span class="comment"> */</span>
<a name="l00173"></a>00173 <span class="keywordtype">double</span> evaluateNormalizedPDF( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">CPose2D</a> &x ) <span class="keyword">const</span>;
<a name="l00174"></a>00174 <span class="comment"></span>
<a name="l00175"></a>00175 <span class="comment"> /** Computes the Mahalanobis distance between the centers of two Gaussians.</span>
<a name="l00176"></a>00176 <span class="comment"> */</span>
<a name="l00177"></a>00177 <span class="keywordtype">double</span> mahalanobisDistanceTo( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a>& theOther );
<a name="l00178"></a>00178 <span class="comment"></span>
<a name="l00179"></a>00179 <span class="comment"> /** Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ).</span>
<a name="l00180"></a>00180 <span class="comment"> */</span>
<a name="l00181"></a>00181 <span class="keywordtype">void</span> <a class="code" href="group__container__ops__grp.html#ga28127b8dfe78fea7644c4f2a3517cdef" title="a+=b (element-wise sum)">operator += </a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &Ap);
<a name="l00182"></a>00182 <span class="comment"></span>
<a name="l00183"></a>00183 <span class="comment"> /** Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated)</span>
<a name="l00184"></a>00184 <span class="comment"> */</span>
<a name="l00185"></a><a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#a48aa41bbd3fc54d2a4ea5d876be3c813">00185</a> <span class="keyword">inline</span> <span class="keywordtype">void</span> operator -=( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &ref ) {
<a name="l00186"></a>00186 this->inverseComposition(*<span class="keyword">this</span>,ref);
<a name="l00187"></a>00187 }
<a name="l00188"></a>00188
<a name="l00189"></a>00189
<a name="l00190"></a>00190 <span class="comment"></span>
<a name="l00191"></a>00191 <span class="comment"> /** This static method computes the pose composition Jacobians, with these formulas:</span>
<a name="l00192"></a>00192 <span class="comment"> \code</span>
<a name="l00193"></a>00193 <span class="comment"> df_dx =</span>
<a name="l00194"></a>00194 <span class="comment"> [ 1, 0, -sin(phi_x)*x_u-cos(phi_x)*y_u ]</span>
<a name="l00195"></a>00195 <span class="comment"> [ 0, 1, cos(phi_x)*x_u-sin(phi_x)*y_u ]</span>
<a name="l00196"></a>00196 <span class="comment"> [ 0, 0, 1 ]</span>
<a name="l00197"></a>00197 <span class="comment"></span>
<a name="l00198"></a>00198 <span class="comment"> df_du =</span>
<a name="l00199"></a>00199 <span class="comment"> [ cos(phi_x) , -sin(phi_x) , 0 ]</span>
<a name="l00200"></a>00200 <span class="comment"> [ sin(phi_x) , cos(phi_x) , 0 ]</span>
<a name="l00201"></a>00201 <span class="comment"> [ 0 , 0 , 1 ]</span>
<a name="l00202"></a>00202 <span class="comment"> \endcode</span>
<a name="l00203"></a>00203 <span class="comment"> */</span>
<a name="l00204"></a>00204 <span class="keyword">static</span> <span class="keywordtype">void</span> jacobiansPoseComposition(
<a name="l00205"></a>00205 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &x,
<a name="l00206"></a>00206 <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &u,
<a name="l00207"></a>00207 <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixDouble33</a> &df_dx,
<a name="l00208"></a>00208 <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixDouble33</a> &df_du);
<a name="l00209"></a>00209
<a name="l00210"></a>00210
<a name="l00211"></a>00211
<a name="l00212"></a>00212 }; <span class="comment">// End of class def.</span>
<a name="l00213"></a>00213
<a name="l00214"></a>00214 <span class="comment"></span>
<a name="l00215"></a>00215 <span class="comment"> /** Pose compose operator: RES = A (+) B , computing both the mean and the covariance */</span>
<a name="l00216"></a><a class="code" href="namespacemrpt_1_1poses.html#a6b8402491fc4b1c483cd6560c483e5dc">00216</a> <span class="keyword">inline</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> <a class="code" href="namespacemrpt_1_1poses.html#afb287beee02202a14b09f1011b648e6f" title="Compose a 2D point from a new coordinate base given by a 2D pose.">operator +</a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &a, <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &b ) {
<a name="l00217"></a>00217 <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> res(a);
<a name="l00218"></a>00218 res+=b;
<a name="l00219"></a>00219 <span class="keywordflow">return</span> res;
<a name="l00220"></a>00220 }
<a name="l00221"></a>00221 <span class="comment"></span>
<a name="l00222"></a>00222 <span class="comment"> /** Pose inverse compose operator: RES = A (-) B , computing both the mean and the covariance */</span>
<a name="l00223"></a><a class="code" href="namespacemrpt_1_1poses.html#ad75c37a127b64eb5bb0f9a1759022b83">00223</a> <span class="keyword">inline</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> <a class="code" href="namespacemrpt_1_1poses.html#a678c1606b35876eae036755599a22d84" title="Unary - operator: return the inverse pose "-p" (Note that is NOT the same than a pose with negative x...">operator -</a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &a, <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> &b ) {
<a name="l00224"></a>00224 <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">CPosePDFGaussianInf</a> res;
<a name="l00225"></a>00225 res.<a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html#aaebfc5aef18c88c1c6f068faf1318589" title="Set , computing the mean using the "-" operator and the covariances through the corresponding Jaco...">inverseComposition</a>(a,b);
<a name="l00226"></a>00226 <span class="keywordflow">return</span> res;
<a name="l00227"></a>00227 }
<a name="l00228"></a>00228 <span class="comment"></span>
<a name="l00229"></a>00229 <span class="comment"> /** Dumps the mean and covariance matrix to a text stream.</span>
<a name="l00230"></a>00230 <span class="comment"> */</span>
<a name="l00231"></a>00231 std::ostream <a class="code" href="base_2include_2mrpt_2base_2link__pragmas_8h.html#a6045fa0129b1a3d6c8bf895470e66574">BASE_IMPEXP</a> & <a class="code" href="namespacemrpt_1_1poses.html#aa4247c4d793d20edb770e56f22b286f1" title="Dumps a point as a string [x,y] or [x,y,z].">operator << </a>(<a class="code" href="classstd_1_1ostream.html" title="STL class.">std::ostream</a> & out, <span class="keyword">const</span> CPosePDFGaussianInf& obj);
<a name="l00232"></a>00232 <span class="comment"></span>
<a name="l00233"></a>00233 <span class="comment"> /** Returns the Gaussian distribution of \f$ \mathbf{C} \f$, for \f$ \mathbf{C} = \mathbf{A} \oplus \mathbf{B} \f$.</span>
<a name="l00234"></a>00234 <span class="comment"> */</span>
<a name="l00235"></a>00235 poses::CPosePDFGaussianInf <a class="code" href="base_2include_2mrpt_2base_2link__pragmas_8h.html#a6045fa0129b1a3d6c8bf895470e66574">BASE_IMPEXP</a> <a class="code" href="namespacemrpt_1_1poses.html#afb287beee02202a14b09f1011b648e6f" title="Compose a 2D point from a new coordinate base given by a 2D pose.">operator + </a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose2_d.html" title="A class used to store a 2D pose.">mrpt::poses::CPose2D</a> &A, <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian_inf.html" title="A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...">mrpt::poses::CPosePDFGaussianInf</a> &B );
<a name="l00236"></a>00236
<a name="l00237"></a>00237 <span class="keywordtype">bool</span> <a class="code" href="base_2include_2mrpt_2base_2link__pragmas_8h.html#a6045fa0129b1a3d6c8bf895470e66574">BASE_IMPEXP</a> <a class="code" href="namespacemrpt_1_1poses.html#acd8c946fdfab1501027f3a9347181ebf">operator==</a>(<span class="keyword">const</span> CPosePDFGaussianInf &p1,<span class="keyword">const</span> CPosePDFGaussianInf &p2);
<a name="l00238"></a>00238
<a name="l00239"></a>00239 } <span class="comment">// End of namespace</span>
<a name="l00240"></a>00240 } <span class="comment">// End of namespace</span>
<a name="l00241"></a>00241
<a name="l00242"></a>00242 <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>
