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<title>mrpt::slam::CRangeBearingKFSLAM2D Class Reference</title>
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<li class="navelem"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html">CRangeBearingKFSLAM2D</a> </li>
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<div class="title">mrpt::slam::CRangeBearingKFSLAM2D Class Reference<div class="ingroups"><a class="el" href="group__metric__slam__grp.html">Metric SLAM algorithms</a></div></div> </div>
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<!-- doxytag: class="mrpt::slam::CRangeBearingKFSLAM2D" --><!-- doxytag: inherits="CKalmanFilterCapable< 3, 2, 2, 3 >" --><hr/><a name="details" id="details"></a><h2>Detailed Description</h2>
<div class="textblock"><p>An implementation of EKF-based SLAM with range-bearing sensors, odometry, and a 2D (+heading) robot pose, and 2D landmarks. </p>
<p>The main method is "processActionObservation" which processes pairs of action/observation.</p>
<p>The following pages describe front-end applications based on this class:</p>
<ul>
<li><a href="http://www.mrpt.org/Application:2d-slam-demo">http://www.mrpt.org/Application:2d-slam-demo</a></li>
<li><a href="http://www.mrpt.org/Application:kf-slam">http://www.mrpt.org/Application:kf-slam</a></li>
</ul>
<dl class="see"><dt><b>See also:</b></dt><dd><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html" title="An implementation of EKF-based SLAM with range-bearing sensors, odometry, a full 6D robot pose...">CRangeBearingKFSLAM</a> </dd></dl>
</div>
<p><code>#include <<a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">mrpt/slam/CRangeBearingKFSLAM2D.h</a>></code></p>
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Inheritance diagram for mrpt::slam::CRangeBearingKFSLAM2D:</div>
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<div class="center"><img src="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d__inherit__graph.png" border="0" usemap="#mrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_inherit__map" alt="Inheritance graph"/></div>
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<area shape="rect" id="node2" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html" title="mrpt::bayes::CKalmanFilterCapable\< 3, 2, 2, 3 \>" alt="" coords="4,173,309,200"/><area shape="rect" id="node4" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html" title="Virtual base for Kalman Filter (EKF,IEKF,UKF) implementations." alt="" coords="42,83,272,109"/><area shape="rect" id="node6" href="classmrpt_1_1utils_1_1_c_debug_output_capable.html" title="This base class provides a common printf-like method to send debug information to std::cout..." alt="" coords="46,5,268,32"/></map>
<center><span class="legend">[<a href="graph_legend.html">legend</a>]</span></center></div>
<p><a href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d-members.html">List of all members.</a></p>
<table class="memberdecls">
<tr><td colspan="2"><h2><a name="nested-classes"></a>
Classes</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_data_assoc_info.html">TDataAssocInfo</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Information for data-association: <a href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_data_assoc_info.html#details">More...</a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">struct  </td><td class="memItemRight" valign="bottom"><a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_options.html">TOptions</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The options for the algorithm. <a href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_options.html#details">More...</a><br/></td></tr>
<tr><td colspan="2"><h2><a name="pub-types"></a>
Public Types</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef KFTYPE </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad66228d2cc13705900669ccbab41f3d9">kftype</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The numeric type used in the Kalman Filter (default=double) <a href="#ad66228d2cc13705900669ccbab41f3d9"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html">CKalmanFilterCapable</a><br class="typebreak"/>
< VEH_SIZE, OBS_SIZE, <br class="typebreak"/>
FEAT_SIZE, ACT_SIZE, KFTYPE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6195a8efec17869133a1fd31105d6a64">KFCLASS</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">My class, in a shorter name! <a href="#a6195a8efec17869133a1fd31105d6a64"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <br class="typebreak"/>
<a class="el" href="structmrpt_1_1dynamicsize__vector.html">mrpt::dynamicsize_vector</a><br class="typebreak"/>
< KFTYPE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a9a120b286d286048985b059aa721e0c1">KFVector</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">CMatrixTemplateNumeric</a><br class="typebreak"/>
< KFTYPE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad214112622ea8531c9a7c052f93600bd">KFMatrix</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, VEH_SIZE, VEH_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8dd3e63dd847fd98ef59b472e46cad2c">KFMatrix_VxV</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, OBS_SIZE, OBS_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a521a75ae040b78365ebf57f97967bc84">KFMatrix_OxO</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, FEAT_SIZE, FEAT_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad8a2b4b92969f736bf6c147804b50614">KFMatrix_FxF</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, ACT_SIZE, ACT_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#af20d435cc094724e00949ea137aa832b">KFMatrix_AxA</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, VEH_SIZE, OBS_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a60912a7a33cd8e77605e4761848609b2">KFMatrix_VxO</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, VEH_SIZE, FEAT_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a7277a24dd3aae42b96708b4669e74a12">KFMatrix_VxF</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, FEAT_SIZE, VEH_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#affb2aa897e6434f6572d48ff1be1988e">KFMatrix_FxV</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, FEAT_SIZE, OBS_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a253bf3d53d25e20ec0592868efdba607">KFMatrix_FxO</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, OBS_SIZE, FEAT_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ada78f649a58aa64c3db6c8b436b5ceba">KFMatrix_OxF</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><br class="typebreak"/>
< KFTYPE, OBS_SIZE, VEH_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ab0ddb67c05616e7fc1fcabe9cc04c753">KFMatrix_OxV</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a>< KFTYPE, <br class="typebreak"/>
VEH_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a>< KFTYPE, <br class="typebreak"/>
ACT_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6454c68e3c45da92e2bbb3e8aa8f6f70">KFArray_ACT</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a>< KFTYPE, <br class="typebreak"/>
OBS_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <br class="typebreak"/>
<a class="el" href="structmrpt_1_1aligned__containers.html">mrpt::aligned_containers</a><br class="typebreak"/>
< <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> >::vector_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a>< KFTYPE, <br class="typebreak"/>
FEAT_SIZE > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a></td></tr>
<tr><td colspan="2"><h2><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#af235f0832757e3cc9d01b056b2d5b253">CRangeBearingKFSLAM2D</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Default constructor. <a href="#af235f0832757e3cc9d01b056b2d5b253"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a47ee95b1f499095822bbf42f7bc0c9e3">~CRangeBearingKFSLAM2D</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Destructor. <a href="#a47ee95b1f499095822bbf42f7bc0c9e3"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aa357feee7d822d0089f8082fb7b64442">reset</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Reset the state of the SLAM filter: The map is emptied and the robot put back to (0,0,0). <a href="#aa357feee7d822d0089f8082fb7b64442"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a7e49c6adb04d37516a76beed1e24d357">processActionObservation</a> (<a class="el" href="structmrpt_1_1slam_1_1_c_action_collection_ptr.html">CActionCollectionPtr</a> &action, <a class="el" href="structmrpt_1_1slam_1_1_c_sensory_frame_ptr.html">CSensoryFramePtr</a> &SF)</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Process one new action and observations to update the map and robot pose estimate. <a href="#a7e49c6adb04d37516a76beed1e24d357"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#ad0d4e090dfe951bffb4f4dd19df5e25c">getCurrentState</a> (<a class="el" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian.html">CPosePDFGaussian</a> &out_robotPose, <a class="el" href="classstd_1_1vector.html">std::vector</a>< <a class="el" href="structmrpt_1_1math_1_1_t_point2_d.html">TPoint2D</a> > &out_landmarksPositions, <a class="el" href="classstd_1_1map.html">std::map</a>< unsigned int, <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a> > &out_landmarkIDs, <a class="el" href="namespacemrpt_1_1math.html#abe5956b4804ecb9ae70f0bd8ebc4d150">CVectorDouble</a> &out_fullState, <a class="el" href="namespacemrpt_1_1math.html#a3814c2b868f059d6a7ab0d8ecd2311d6">CMatrixDouble</a> &out_fullCovariance) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the complete mean and cov. <a href="#ad0d4e090dfe951bffb4f4dd19df5e25c"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a939ee0eb252c86ce3ae61b33d8016473">getCurrentRobotPose</a> (<a class="el" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian.html">CPosePDFGaussian</a> &out_robotPose) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the mean & 3x3 covariance matrix of the robot 2D pose. <a href="#a939ee0eb252c86ce3ae61b33d8016473"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a4be0af67e3f2b1c36bebe160e0ba1b6e">getAs3DObject</a> (<a class="el" href="structmrpt_1_1opengl_1_1_c_set_of_objects_ptr.html">mrpt::opengl::CSetOfObjectsPtr</a> &outObj) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns a 3D representation of the landmarks in the map and the robot 3D position according to the current filter state. <a href="#a4be0af67e3f2b1c36bebe160e0ba1b6e"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a7f73fb0c1df49df486bc4010721762a8">loadOptions</a> (const <a class="el" href="classmrpt_1_1utils_1_1_c_config_file_base.html">mrpt::utils::CConfigFileBase</a> &ini)</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Load options from a ini-like file/text. <a href="#a7f73fb0c1df49df486bc4010721762a8"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a64f299d6a113132637a54342dc3da1cc">saveMapAndPath2DRepresentationAsMATLABFile</a> (const <a class="el" href="classstd_1_1string.html">std::string</a> &fil, float stdCount=3.0f, const std::string &styleLandmarks=std::string("b"), const std::string &stylePath=std::string("r"), const std::string &styleRobot=std::string("r")) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Save the current state of the filter (robot pose & map) to a MATLAB script which displays all the elements in 2D. <a href="#a64f299d6a113132637a54342dc3da1cc"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">const <a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_data_assoc_info.html">TDataAssocInfo</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a1cd426f4152e3f4fb08fe394010038ab">getLastDataAssociation</a> () const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns a read-only reference to the information on the last data-association. <a href="#a1cd426f4152e3f4fb08fe394010038ab"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1ac5b0adbbd3a0e5122ebb148ff3e7ad">getNumberOfLandmarksInTheMap</a> () const </td></tr>
<tr><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a48adbb9852e76624b16e7fa115c19e65">isMapEmpty</a> () const </td></tr>
<tr><td class="memItemLeft" align="right" valign="top">size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aabe244779fd4694bc5e6d336874396de">getStateVectorLength</a> () const </td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a4cc933fc0dacdd126b08b08591c617f4">getLandmarkMean</a> (size_t idx, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> &feat) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the mean of the estimated value of the idx'th landmark (not applicable to non-SLAM problems). <a href="#a4cc933fc0dacdd126b08b08591c617f4"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ae32eeb6c71cb7ea1acf21ae09ac19827">getLandmarkCov</a> (size_t idx, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad8a2b4b92969f736bf6c147804b50614">KFMatrix_FxF</a> &feat_cov) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the covariance of the idx'th landmark (not applicable to non-SLAM problems). <a href="#ae32eeb6c71cb7ea1acf21ae09ac19827"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1utils_1_1_c_time_logger.html">mrpt::utils::CTimeLogger</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a4c2d71f07ef0501d157988ebccf9f3c0">getProfiler</a> ()</td></tr>
<tr><td colspan="2"><h2><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">static size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6229386413a59a767a5197fca67e56cf">get_vehicle_size</a> ()</td></tr>
<tr><td class="memItemLeft" align="right" valign="top">static size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ae1bc73d658a9a0e1ca3615a523624434">get_observation_size</a> ()</td></tr>
<tr><td class="memItemLeft" align="right" valign="top">static size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad19146ca0b12bed3c2aace9329ece0fd">get_feature_size</a> ()</td></tr>
<tr><td class="memItemLeft" align="right" valign="top">static size_t </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#abaeadbd68b3a68d35e530a29b7c193b2">get_action_size</a> ()</td></tr>
<tr><td colspan="2"><h2><a name="pub-attribs"></a>
Public Attributes</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_options.html">TOptions</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aaac671183aab10c91682e180b1d4dddf">options</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The options for the algorithm. <a href="#aaac671183aab10c91682e180b1d4dddf"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="structmrpt_1_1bayes_1_1_t_k_f__options.html">TKF_options</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a88651951bad5ea93ae84d848aeed6414">KF_options</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Generic options for the Kalman Filter algorithm itself. <a href="#a88651951bad5ea93ae84d848aeed6414"></a><br/></td></tr>
<tr><td colspan="2"><h2><a name="pro-methods"></a>
Protected Member Functions</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a76474c9e8d0e66ec08c55df763394656">getLandmarkIDsFromIndexInStateVector</a> (<a class="el" href="classstd_1_1map.html">std::map</a>< unsigned int, <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a> > &out_id2index) const </td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aeebd325f91acbf7d27134c8c7388649e">runOneKalmanIteration</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The main entry point, executes one complete step: prediction + update. <a href="#aeebd325f91acbf7d27134c8c7388649e"></a><br/></td></tr>
<tr><td colspan="2"><div class="groupHeader">Virtual methods for Kalman Filter implementation</div></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#abc536347b81003fc8c3e0902a435e151">OnGetAction</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6454c68e3c45da92e2bbb3e8aa8f6f70">KFArray_ACT</a> &out_u) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Must return the action vector u. <a href="#abc536347b81003fc8c3e0902a435e151"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a3ea632d9fe8529f381c4c6d259a2ff9d">OnTransitionModel</a> (const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6454c68e3c45da92e2bbb3e8aa8f6f70">KFArray_ACT</a> &in_u, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a> &inout_x, bool &out_skipPrediction) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the transition model <img class="formulaInl" alt="$ \hat{x}_{k|k-1} = f( \hat{x}_{k-1|k-1}, u_k ) $" src="form_86.png"/>. <a href="#a3ea632d9fe8529f381c4c6d259a2ff9d"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a40f4a9cbe853526f05abbeb93b535102">OnTransitionJacobian</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8dd3e63dd847fd98ef59b472e46cad2c">KFMatrix_VxV</a> &out_F) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the transition Jacobian <img class="formulaInl" alt="$ \frac{\partial f}{\partial x} $" src="form_29.png"/>. <a href="#a40f4a9cbe853526f05abbeb93b535102"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#afb9ddb3cff1724e22e616fe0610681ab">OnTransitionJacobianNumericGetIncrements</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a> &out_increments) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Only called if using a numeric approximation of the transition Jacobian, this method must return the increments in each dimension of the vehicle state vector while estimating the Jacobian. <a href="#afb9ddb3cff1724e22e616fe0610681ab"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a492735723c8e453b8bda0acbb6d4f271">OnTransitionNoise</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8dd3e63dd847fd98ef59b472e46cad2c">KFMatrix_VxV</a> &out_Q) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the transition noise covariance <img class="formulaInl" alt="$ Q_k $" src="form_90.png"/>. <a href="#a492735723c8e453b8bda0acbb6d4f271"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a1c01bffffcf1384d0863f2000e019258">OnGetObservationsAndDataAssociation</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> &out_z, <a class="el" href="namespacemrpt.html#ac2e04951e7bd82f53b6ecaa0fd8a2662">vector_int</a> &out_data_association, const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> &in_all_predictions, const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad214112622ea8531c9a7c052f93600bd">KFMatrix</a> &in_S, const <a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> &in_lm_indices_in_S, const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a521a75ae040b78365ebf57f97967bc84">KFMatrix_OxO</a> &in_R)</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">This is called between the KF prediction step and the update step, and the application must return the observations and, when applicable, the data association between these observations and the current map. <a href="#a1c01bffffcf1384d0863f2000e019258"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aa8a021990239ac720ee2c44dd2b715e9">OnObservationModel</a> (const <a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> &idx_landmarks_to_predict, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> &out_predictions) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the observation prediction <img class="formulaInl" alt="$ h_i(x) $" src="form_91.png"/>. <a href="#aa8a021990239ac720ee2c44dd2b715e9"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#accfee66b72edc2288df16e0686792879">OnObservationJacobians</a> (const size_t &idx_landmark_to_predict, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ab0ddb67c05616e7fc1fcabe9cc04c753">KFMatrix_OxV</a> &Hx, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ada78f649a58aa64c3db6c8b436b5ceba">KFMatrix_OxF</a> &Hy) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the observation Jacobians <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial x} $" src="form_92.png"/> and (when applicable) <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial y_i} $" src="form_93.png"/>. <a href="#accfee66b72edc2288df16e0686792879"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a6527eb56311535ab9b84dc48f3faf9b0">OnObservationJacobiansNumericGetIncrements</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a> &out_veh_increments, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> &out_feat_increments) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Only called if using a numeric approximation of the observation Jacobians, this method must return the increments in each dimension of the vehicle state vector while estimating the Jacobian. <a href="#a6527eb56311535ab9b84dc48f3faf9b0"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#ac209037604fb37a25d7b56f4c1fb4781">OnSubstractObservationVectors</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> &A, const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> &B) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Computes A=A-B, which may need to be re-implemented depending on the topology of the individual scalar components (eg, angles). <a href="#ac209037604fb37a25d7b56f4c1fb4781"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a79de30811b3c0aa710cdebf7521215fb">OnGetObservationNoise</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a521a75ae040b78365ebf57f97967bc84">KFMatrix_OxO</a> &out_R) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Return the observation NOISE covariance matrix, that is, the model of the Gaussian additive noise of the sensor. <a href="#a79de30811b3c0aa710cdebf7521215fb"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a5d32610c2440162beb39617879d1b79c">OnPreComputingPredictions</a> (const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> &in_all_prediction_means, <a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> &out_LM_indices_to_predict) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">This will be called before OnGetObservationsAndDataAssociation to allow the application to reduce the number of covariance landmark predictions to be made. <a href="#a5d32610c2440162beb39617879d1b79c"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a4f261c0cc2bce890b65fdbc07f1cdb25">OnInverseObservationModel</a> (const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> &in_z, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> &out_yn, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#affb2aa897e6434f6572d48ff1be1988e">KFMatrix_FxV</a> &out_dyn_dxv, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a253bf3d53d25e20ec0592868efdba607">KFMatrix_FxO</a> &out_dyn_dhn) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">If applicable to the given problem, this method implements the inverse observation model needed to extend the "map" with a new "element". <a href="#a4f261c0cc2bce890b65fdbc07f1cdb25"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a1073193e03d2f4ff2038fa84ccdd4653">OnNewLandmarkAddedToMap</a> (const size_t in_obsIdx, const size_t in_idxNewFeat)</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">If applicable to the given problem, do here any special handling of adding a new landmark to the map. <a href="#a1073193e03d2f4ff2038fa84ccdd4653"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aa3d99ee710bbdbdcd21bc2512ef52f9d">OnNormalizeStateVector</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">This method is called after the prediction and after the update, to give the user an opportunity to normalize the state vector (eg, keep angles within -pi,pi range) if the application requires it. <a href="#aa3d99ee710bbdbdcd21bc2512ef52f9d"></a><br/></td></tr>
<tr><td colspan="2"><div class="groupHeader">Virtual methods for Kalman Filter implementation</div></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#af7c70d63832d8d45d8c5de0ed6041109">OnInverseObservationModel</a> (const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> &in_z, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> &out_yn, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#affb2aa897e6434f6572d48ff1be1988e">KFMatrix_FxV</a> &out_dyn_dxv, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a253bf3d53d25e20ec0592868efdba607">KFMatrix_FxO</a> &out_dyn_dhn, <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad8a2b4b92969f736bf6c147804b50614">KFMatrix_FxF</a> &out_dyn_dhn_R_dyn_dhnT, bool &out_use_dyn_dhn_jacobian) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">If applicable to the given problem, this method implements the inverse observation model needed to extend the "map" with a new "element". <a href="#af7c70d63832d8d45d8c5de0ed6041109"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a5a3514fd81d6f81b8ff7b2c72dfae33e">OnPostIteration</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">This method is called after finishing one KF iteration and before returning from runOneKalmanIteration(). <a href="#a5a3514fd81d6f81b8ff7b2c72dfae33e"></a><br/></td></tr>
<tr><td colspan="2"><h2><a name="pro-attribs"></a>
Protected Attributes</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="structmrpt_1_1slam_1_1_c_action_collection_ptr.html">CActionCollectionPtr</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aa252e8d11ce89ce7ff01696269bf0f74">m_action</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Set up by processActionObservation. <a href="#aa252e8d11ce89ce7ff01696269bf0f74"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="structmrpt_1_1slam_1_1_c_sensory_frame_ptr.html">CSensoryFramePtr</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#ae2df87aa3d1cc8cbf8a88fab1ea68dbd">m_SF</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Set up by processActionObservation. <a href="#ae2df87aa3d1cc8cbf8a88fab1ea68dbd"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1utils_1_1bimap.html">mrpt::utils::bimap</a><br class="typebreak"/>
< <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a>, <br class="typebreak"/>
unsigned int > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a804919da59c1ddc75e6b481a24ee6749">m_IDs</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The mapping between landmark IDs and indexes in the Pkk cov. <a href="#a804919da59c1ddc75e6b481a24ee6749"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1slam_1_1_c_simple_map.html">CSimpleMap</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a7add6e75a3f51e219bbb3d7e0e428c63">m_SFs</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The sequence of all the observations and the robot path (kept for debugging, statistics,etc) <a href="#a7add6e75a3f51e219bbb3d7e0e428c63"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_data_assoc_info.html">TDataAssocInfo</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#abc2f94171c9219ee807c5bbafc2ac611">m_last_data_association</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Last data association. <a href="#abc2f94171c9219ee807c5bbafc2ac611"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1utils_1_1_c_time_logger.html">mrpt::utils::CTimeLogger</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a3eff55c428065c52bd2f9418e3944e48">m_timLogger</a></td></tr>
<tr><td colspan="2"><div class="groupHeader">Kalman filter state</div></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a9a120b286d286048985b059aa721e0c1">KFVector</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a7e8948c9d209c23517c45c6494b46147">m_xkk</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The system state vector. <a href="#a7e8948c9d209c23517c45c6494b46147"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad214112622ea8531c9a7c052f93600bd">KFMatrix</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a15c291ca9eb40996381dc0e60f01d533">m_pkk</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The system full covariance matrix. <a href="#a15c291ca9eb40996381dc0e60f01d533"></a><br/></td></tr>
<tr><td colspan="2"><h2><a name="friends"></a>
Friends</h2></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">struct </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1f7c0688afe03ffd6f14c4e9f4e5a050">detail::CRunOneKalmanIteration_addNewLandmarks</a></td></tr>
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<hr/><h2>Member Typedef Documentation</h2>
<a class="anchor" id="a6454c68e3c45da92e2bbb3e8aa8f6f70"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFArray_ACT" ref="a6454c68e3c45da92e2bbb3e8aa8f6f70" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a><KFTYPE,ACT_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6454c68e3c45da92e2bbb3e8aa8f6f70">mrpt::bayes::CKalmanFilterCapable::KFArray_ACT</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00179">179</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a0b5b72d68126a91918ce085789da06bd"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFArray_FEAT" ref="a0b5b72d68126a91918ce085789da06bd" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a><KFTYPE,FEAT_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">mrpt::bayes::CKalmanFilterCapable::KFArray_FEAT</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00182">182</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a6c1b24a2c7b35e77411888a06de4e59d"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFArray_OBS" ref="a6c1b24a2c7b35e77411888a06de4e59d" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a><KFTYPE,OBS_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">mrpt::bayes::CKalmanFilterCapable::KFArray_OBS</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00180">180</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ad4f1667845ca7553925160142821cff0"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFArray_VEH" ref="ad4f1667845ca7553925160142821cff0" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">CArrayNumeric</a><KFTYPE,VEH_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">mrpt::bayes::CKalmanFilterCapable::KFArray_VEH</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00178">178</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a6195a8efec17869133a1fd31105d6a64"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFCLASS" ref="a6195a8efec17869133a1fd31105d6a64" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html">CKalmanFilterCapable</a><VEH_SIZE,OBS_SIZE,FEAT_SIZE,ACT_SIZE,KFTYPE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6195a8efec17869133a1fd31105d6a64">mrpt::bayes::CKalmanFilterCapable::KFCLASS</a><code> [inherited]</code></td>
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<p>My class, in a shorter name! </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00158">158</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ad214112622ea8531c9a7c052f93600bd"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix" ref="ad214112622ea8531c9a7c052f93600bd" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">CMatrixTemplateNumeric</a><KFTYPE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad214112622ea8531c9a7c052f93600bd">mrpt::bayes::CKalmanFilterCapable::KFMatrix</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00162">162</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="af20d435cc094724e00949ea137aa832b"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_AxA" ref="af20d435cc094724e00949ea137aa832b" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,ACT_SIZE,ACT_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#af20d435cc094724e00949ea137aa832b">mrpt::bayes::CKalmanFilterCapable::KFMatrix_AxA</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00167">167</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ad8a2b4b92969f736bf6c147804b50614"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_FxF" ref="ad8a2b4b92969f736bf6c147804b50614" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,FEAT_SIZE,FEAT_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad8a2b4b92969f736bf6c147804b50614">mrpt::bayes::CKalmanFilterCapable::KFMatrix_FxF</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00166">166</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a253bf3d53d25e20ec0592868efdba607"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_FxO" ref="a253bf3d53d25e20ec0592868efdba607" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,FEAT_SIZE,OBS_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a253bf3d53d25e20ec0592868efdba607">mrpt::bayes::CKalmanFilterCapable::KFMatrix_FxO</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00173">173</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="affb2aa897e6434f6572d48ff1be1988e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_FxV" ref="affb2aa897e6434f6572d48ff1be1988e" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,FEAT_SIZE,VEH_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#affb2aa897e6434f6572d48ff1be1988e">mrpt::bayes::CKalmanFilterCapable::KFMatrix_FxV</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00172">172</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ada78f649a58aa64c3db6c8b436b5ceba"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_OxF" ref="ada78f649a58aa64c3db6c8b436b5ceba" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,OBS_SIZE,FEAT_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ada78f649a58aa64c3db6c8b436b5ceba">mrpt::bayes::CKalmanFilterCapable::KFMatrix_OxF</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00175">175</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a521a75ae040b78365ebf57f97967bc84"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_OxO" ref="a521a75ae040b78365ebf57f97967bc84" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,OBS_SIZE,OBS_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a521a75ae040b78365ebf57f97967bc84">mrpt::bayes::CKalmanFilterCapable::KFMatrix_OxO</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00165">165</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ab0ddb67c05616e7fc1fcabe9cc04c753"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_OxV" ref="ab0ddb67c05616e7fc1fcabe9cc04c753" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,OBS_SIZE,VEH_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ab0ddb67c05616e7fc1fcabe9cc04c753">mrpt::bayes::CKalmanFilterCapable::KFMatrix_OxV</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00176">176</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a7277a24dd3aae42b96708b4669e74a12"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_VxF" ref="a7277a24dd3aae42b96708b4669e74a12" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,VEH_SIZE,FEAT_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a7277a24dd3aae42b96708b4669e74a12">mrpt::bayes::CKalmanFilterCapable::KFMatrix_VxF</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00170">170</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a60912a7a33cd8e77605e4761848609b2"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_VxO" ref="a60912a7a33cd8e77605e4761848609b2" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,VEH_SIZE,OBS_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a60912a7a33cd8e77605e4761848609b2">mrpt::bayes::CKalmanFilterCapable::KFMatrix_VxO</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00169">169</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a8dd3e63dd847fd98ef59b472e46cad2c"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFMatrix_VxV" ref="a8dd3e63dd847fd98ef59b472e46cad2c" args="" -->
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<td class="memname">typedef <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">CMatrixFixedNumeric</a><KFTYPE,VEH_SIZE,VEH_SIZE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8dd3e63dd847fd98ef59b472e46cad2c">mrpt::bayes::CKalmanFilterCapable::KFMatrix_VxV</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00164">164</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ad66228d2cc13705900669ccbab41f3d9"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::kftype" ref="ad66228d2cc13705900669ccbab41f3d9" args="" -->
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<td class="memname">typedef KFTYPE <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad66228d2cc13705900669ccbab41f3d9">mrpt::bayes::CKalmanFilterCapable::kftype</a><code> [inherited]</code></td>
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<p>The numeric type used in the Kalman Filter (default=double) </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00157">157</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a9a120b286d286048985b059aa721e0c1"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KFVector" ref="a9a120b286d286048985b059aa721e0c1" args="" -->
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<td class="memname">typedef <a class="el" href="structmrpt_1_1dynamicsize__vector.html">mrpt::dynamicsize_vector</a><KFTYPE> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a9a120b286d286048985b059aa721e0c1">mrpt::bayes::CKalmanFilterCapable::KFVector</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00161">161</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="aa0e71d2a45e5d935eba18d817bb31cf9"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::vector_KFArray_OBS" ref="aa0e71d2a45e5d935eba18d817bb31cf9" args="" -->
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<td class="memname">typedef <a class="el" href="structmrpt_1_1aligned__containers.html">mrpt::aligned_containers</a><<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a>>::vector_t <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">mrpt::bayes::CKalmanFilterCapable::vector_KFArray_OBS</a><code> [inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00181">181</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<hr/><h2>Constructor & Destructor Documentation</h2>
<a class="anchor" id="af235f0832757e3cc9d01b056b2d5b253"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::CRangeBearingKFSLAM2D" ref="af235f0832757e3cc9d01b056b2d5b253" args="()" -->
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<td class="memname">mrpt::slam::CRangeBearingKFSLAM2D::CRangeBearingKFSLAM2D </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
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<p>Default constructor. </p>
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<a class="anchor" id="a47ee95b1f499095822bbf42f7bc0c9e3"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::~CRangeBearingKFSLAM2D" ref="a47ee95b1f499095822bbf42f7bc0c9e3" args="()" -->
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<td class="memname">virtual mrpt::slam::CRangeBearingKFSLAM2D::~CRangeBearingKFSLAM2D </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td><code> [virtual]</code></td>
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<p>Destructor. </p>
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<hr/><h2>Member Function Documentation</h2>
<a class="anchor" id="abaeadbd68b3a68d35e530a29b7c193b2"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::get_action_size" ref="abaeadbd68b3a68d35e530a29b7c193b2" args="()" -->
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<td class="memname">static size_t mrpt::bayes::CKalmanFilterCapable::get_action_size </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td><code> [inline, static, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00152">152</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ad19146ca0b12bed3c2aace9329ece0fd"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::get_feature_size" ref="ad19146ca0b12bed3c2aace9329ece0fd" args="()" -->
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<td class="memname">static size_t mrpt::bayes::CKalmanFilterCapable::get_feature_size </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td><code> [inline, static, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00151">151</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ae1bc73d658a9a0e1ca3615a523624434"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::get_observation_size" ref="ae1bc73d658a9a0e1ca3615a523624434" args="()" -->
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<td class="memname">static size_t mrpt::bayes::CKalmanFilterCapable::get_observation_size </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td><code> [inline, static, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00150">150</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a6229386413a59a767a5197fca67e56cf"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::get_vehicle_size" ref="a6229386413a59a767a5197fca67e56cf" args="()" -->
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<td class="memname">static size_t mrpt::bayes::CKalmanFilterCapable::get_vehicle_size </td>
<td>(</td>
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<td><code> [inline, static, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00149">149</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a4be0af67e3f2b1c36bebe160e0ba1b6e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getAs3DObject" ref="a4be0af67e3f2b1c36bebe160e0ba1b6e" args="(mrpt::opengl::CSetOfObjectsPtr &outObj) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::getAs3DObject </td>
<td>(</td>
<td class="paramtype"><a class="el" href="structmrpt_1_1opengl_1_1_c_set_of_objects_ptr.html">mrpt::opengl::CSetOfObjectsPtr</a> & </td>
<td class="paramname"><em>outObj</em></td><td>)</td>
<td> const</td>
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<p>Returns a 3D representation of the landmarks in the map and the robot 3D position according to the current filter state. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_objects</td><td></td></tr>
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</dd>
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<a class="anchor" id="a939ee0eb252c86ce3ae61b33d8016473"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getCurrentRobotPose" ref="a939ee0eb252c86ce3ae61b33d8016473" args="(CPosePDFGaussian &out_robotPose) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::getCurrentRobotPose </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian.html">CPosePDFGaussian</a> & </td>
<td class="paramname"><em>out_robotPose</em></td><td>)</td>
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<p>Returns the mean & 3x3 covariance matrix of the robot 2D pose. </p>
<dl class="see"><dt><b>See also:</b></dt><dd><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#ad0d4e090dfe951bffb4f4dd19df5e25c" title="Returns the complete mean and cov.">getCurrentState</a> </dd></dl>
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<a class="anchor" id="ad0d4e090dfe951bffb4f4dd19df5e25c"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getCurrentState" ref="ad0d4e090dfe951bffb4f4dd19df5e25c" args="(CPosePDFGaussian &out_robotPose, std::vector< TPoint2D > &out_landmarksPositions, std::map< unsigned int, CLandmark::TLandmarkID > &out_landmarkIDs, CVectorDouble &out_fullState, CMatrixDouble &out_fullCovariance) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::getCurrentState </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1poses_1_1_c_pose_p_d_f_gaussian.html">CPosePDFGaussian</a> & </td>
<td class="paramname"><em>out_robotPose</em>, </td>
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<td class="paramtype"><a class="el" href="classstd_1_1vector.html">std::vector</a>< <a class="el" href="structmrpt_1_1math_1_1_t_point2_d.html">TPoint2D</a> > & </td>
<td class="paramname"><em>out_landmarksPositions</em>, </td>
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<td class="paramtype"><a class="el" href="classstd_1_1map.html">std::map</a>< unsigned int, <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a> > & </td>
<td class="paramname"><em>out_landmarkIDs</em>, </td>
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<td class="paramkey"></td>
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<td class="paramtype"><a class="el" href="namespacemrpt_1_1math.html#abe5956b4804ecb9ae70f0bd8ebc4d150">CVectorDouble</a> & </td>
<td class="paramname"><em>out_fullState</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="namespacemrpt_1_1math.html#a3814c2b868f059d6a7ab0d8ecd2311d6">CMatrixDouble</a> & </td>
<td class="paramname"><em>out_fullCovariance</em> </td>
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<tr>
<td></td>
<td>)</td>
<td></td><td> const</td>
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<p>Returns the complete mean and cov. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_robotPose</td><td>The mean & 3x3 covariance matrix of the robot 2D pose </td></tr>
<tr><td class="paramname">out_landmarksPositions</td><td>One entry for each of the M landmark positions (2D). </td></tr>
<tr><td class="paramname">out_landmarkIDs</td><td>Each element[index] (for indices of out_landmarksPositions) gives the corresponding landmark ID. </td></tr>
<tr><td class="paramname">out_fullState</td><td>The complete state vector (3+2M). </td></tr>
<tr><td class="paramname">out_fullCovariance</td><td>The full (3+2M)x(3+2M) covariance matrix of the filter. </td></tr>
</table>
</dd>
</dl>
<dl class="see"><dt><b>See also:</b></dt><dd><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a939ee0eb252c86ce3ae61b33d8016473" title="Returns the mean & 3x3 covariance matrix of the robot 2D pose.">getCurrentRobotPose</a> </dd></dl>
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<a class="anchor" id="ae32eeb6c71cb7ea1acf21ae09ac19827"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getLandmarkCov" ref="ae32eeb6c71cb7ea1acf21ae09ac19827" args="(size_t idx, KFMatrix_FxF &feat_cov) const " -->
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<td class="memname">void mrpt::bayes::CKalmanFilterCapable::getLandmarkCov </td>
<td>(</td>
<td class="paramtype">size_t </td>
<td class="paramname"><em>idx</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad8a2b4b92969f736bf6c147804b50614">KFMatrix_FxF</a> & </td>
<td class="paramname"><em>feat_cov</em> </td>
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<td>)</td>
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<p>Returns the covariance of the idx'th landmark (not applicable to non-SLAM problems). </p>
<dl><dt><b>Exceptions:</b></dt><dd>
<table class="exception">
<tr><td class="paramname"><a class="el" href="classstd_1_1exception.html" title="STL class.">std::exception</a></td><td>On idx>= getNumberOfLandmarksInTheMap() </td></tr>
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</dd>
</dl>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00196">196</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a76474c9e8d0e66ec08c55df763394656"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getLandmarkIDsFromIndexInStateVector" ref="a76474c9e8d0e66ec08c55df763394656" args="(std::map< unsigned int, CLandmark::TLandmarkID > &out_id2index) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::getLandmarkIDsFromIndexInStateVector </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classstd_1_1map.html">std::map</a>< unsigned int, <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a> > & </td>
<td class="paramname"><em>out_id2index</em></td><td>)</td>
<td> const<code> [inline, protected]</code></td>
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<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00335">335</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="a4cc933fc0dacdd126b08b08591c617f4"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getLandmarkMean" ref="a4cc933fc0dacdd126b08b08591c617f4" args="(size_t idx, KFArray_FEAT &feat) const " -->
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<td class="memname">void mrpt::bayes::CKalmanFilterCapable::getLandmarkMean </td>
<td>(</td>
<td class="paramtype">size_t </td>
<td class="paramname"><em>idx</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> & </td>
<td class="paramname"><em>feat</em> </td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td> const<code> [inline, inherited]</code></td>
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<p>Returns the mean of the estimated value of the idx'th landmark (not applicable to non-SLAM problems). </p>
<dl><dt><b>Exceptions:</b></dt><dd>
<table class="exception">
<tr><td class="paramname"><a class="el" href="classstd_1_1exception.html" title="STL class.">std::exception</a></td><td>On idx>= getNumberOfLandmarksInTheMap() </td></tr>
</table>
</dd>
</dl>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00189">189</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a1cd426f4152e3f4fb08fe394010038ab"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getLastDataAssociation" ref="a1cd426f4152e3f4fb08fe394010038ab" args="() const " -->
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<td class="memname">const <a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_data_assoc_info.html">TDataAssocInfo</a>& mrpt::slam::CRangeBearingKFSLAM2D::getLastDataAssociation </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td> const<code> [inline]</code></td>
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<p>Returns a read-only reference to the information on the last data-association. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00194">194</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="a1ac5b0adbbd3a0e5122ebb148ff3e7ad"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getNumberOfLandmarksInTheMap" ref="a1ac5b0adbbd3a0e5122ebb148ff3e7ad" args="() const " -->
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<td class="memname">size_t mrpt::bayes::CKalmanFilterCapable::getNumberOfLandmarksInTheMap </td>
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<td> const<code> [inline, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00153">153</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a4c2d71f07ef0501d157988ebccf9f3c0"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getProfiler" ref="a4c2d71f07ef0501d157988ebccf9f3c0" args="()" -->
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<td class="memname"><a class="el" href="classmrpt_1_1utils_1_1_c_time_logger.html">mrpt::utils::CTimeLogger</a>& mrpt::bayes::CKalmanFilterCapable::getProfiler </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td><code> [inline, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00431">431</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="aabe244779fd4694bc5e6d336874396de"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::getStateVectorLength" ref="aabe244779fd4694bc5e6d336874396de" args="() const " -->
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<td class="memname">size_t mrpt::bayes::CKalmanFilterCapable::getStateVectorLength </td>
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<td> const<code> [inline, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00184">184</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a48adbb9852e76624b16e7fa115c19e65"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::isMapEmpty" ref="a48adbb9852e76624b16e7fa115c19e65" args="() const " -->
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<td class="memname">bool mrpt::bayes::CKalmanFilterCapable::isMapEmpty </td>
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<td> const<code> [inline, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00154">154</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a7f73fb0c1df49df486bc4010721762a8"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::loadOptions" ref="a7f73fb0c1df49df486bc4010721762a8" args="(const mrpt::utils::CConfigFileBase &ini)" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::loadOptions </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1utils_1_1_c_config_file_base.html">mrpt::utils::CConfigFileBase</a> & </td>
<td class="paramname"><em>ini</em></td><td>)</td>
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<p>Load options from a ini-like file/text. </p>
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<a class="anchor" id="abc536347b81003fc8c3e0902a435e151"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnGetAction" ref="abc536347b81003fc8c3e0902a435e151" args="(KFArray_ACT &out_u) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnGetAction </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6454c68e3c45da92e2bbb3e8aa8f6f70">KFArray_ACT</a> & </td>
<td class="paramname"><em>out_u</em></td><td>)</td>
<td> const<code> [protected, virtual]</code></td>
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<p>Must return the action vector u. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_u</td><td>The action vector which will be passed to OnTransitionModel </td></tr>
</table>
</dd>
</dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a987165d6a5082835f2645d32a62b43cd">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a79de30811b3c0aa710cdebf7521215fb"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnGetObservationNoise" ref="a79de30811b3c0aa710cdebf7521215fb" args="(KFMatrix_OxO &out_R) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnGetObservationNoise </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a521a75ae040b78365ebf57f97967bc84">KFMatrix_OxO</a> & </td>
<td class="paramname"><em>out_R</em></td><td>)</td>
<td> const<code> [protected, virtual]</code></td>
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<p>Return the observation NOISE covariance matrix, that is, the model of the Gaussian additive noise of the sensor. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_R</td><td>The noise covariance matrix. It might be non diagonal, but it'll usually be. </td></tr>
</table>
</dd>
</dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a644a7ca4a46f46b704c123671a0b6bc7">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a1c01bffffcf1384d0863f2000e019258"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnGetObservationsAndDataAssociation" ref="a1c01bffffcf1384d0863f2000e019258" args="(vector_KFArray_OBS &out_z, vector_int &out_data_association, const vector_KFArray_OBS &in_all_predictions, const KFMatrix &in_S, const vector_size_t &in_lm_indices_in_S, const KFMatrix_OxO &in_R)" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnGetObservationsAndDataAssociation </td>
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<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> & </td>
<td class="paramname"><em>out_z</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="namespacemrpt.html#ac2e04951e7bd82f53b6ecaa0fd8a2662">vector_int</a> & </td>
<td class="paramname"><em>out_data_association</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> & </td>
<td class="paramname"><em>in_all_predictions</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad214112622ea8531c9a7c052f93600bd">KFMatrix</a> & </td>
<td class="paramname"><em>in_S</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> & </td>
<td class="paramname"><em>in_lm_indices_in_S</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a521a75ae040b78365ebf57f97967bc84">KFMatrix_OxO</a> & </td>
<td class="paramname"><em>in_R</em> </td>
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<td>)</td>
<td></td><td><code> [protected, virtual]</code></td>
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<p>This is called between the KF prediction step and the update step, and the application must return the observations and, when applicable, the data association between these observations and the current map. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_z</td><td>N vectors, each for one "observation" of length OBS_SIZE, N being the number of "observations": how many observed landmarks for a map, or just one if not applicable. </td></tr>
<tr><td class="paramname">out_data_association</td><td>An empty vector or, where applicable, a vector where the i'th element corresponds to the position of the observation in the i'th row of out_z within the system state vector (in the range [0,<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1ac5b0adbbd3a0e5122ebb148ff3e7ad">getNumberOfLandmarksInTheMap()</a>-1]), or -1 if it is a new map element and we want to insert it at the end of this KF iteration. </td></tr>
<tr><td class="paramname">in_S</td><td>The full covariance matrix of the observation predictions (i.e. the "innovation covariance matrix"). This is a M·O x M·O matrix with M=length of "in_lm_indices_in_S". </td></tr>
<tr><td class="paramname">in_lm_indices_in_S</td><td>The indices of the map landmarks (range [0,<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1ac5b0adbbd3a0e5122ebb148ff3e7ad">getNumberOfLandmarksInTheMap()</a>-1]) that can be found in the matrix in_S.</td></tr>
</table>
</dd>
</dl>
<p>This method will be called just once for each complete KF iteration. </p>
<dl class="note"><dt><b>Note:</b></dt><dd>It is assumed that the observations are independent, i.e. there are NO cross-covariances between them. </dd></dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a74490d79d5d8fbf499021af5f66d593b">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a4f261c0cc2bce890b65fdbc07f1cdb25"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnInverseObservationModel" ref="a4f261c0cc2bce890b65fdbc07f1cdb25" args="(const KFArray_OBS &in_z, KFArray_FEAT &out_yn, KFMatrix_FxV &out_dyn_dxv, KFMatrix_FxO &out_dyn_dhn) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnInverseObservationModel </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> & </td>
<td class="paramname"><em>in_z</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> & </td>
<td class="paramname"><em>out_yn</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#affb2aa897e6434f6572d48ff1be1988e">KFMatrix_FxV</a> & </td>
<td class="paramname"><em>out_dyn_dxv</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a253bf3d53d25e20ec0592868efdba607">KFMatrix_FxO</a> & </td>
<td class="paramname"><em>out_dyn_dhn</em> </td>
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<td>)</td>
<td></td><td> const<code> [protected, virtual]</code></td>
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<p>If applicable to the given problem, this method implements the inverse observation model needed to extend the "map" with a new "element". </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">in_z</td><td>The observation vector whose inverse sensor model is to be computed. This is actually one of the vector<> returned by OnGetObservations(). </td></tr>
<tr><td class="paramname">out_yn</td><td>The F-length vector with the inverse observation model <img class="formulaInl" alt="$ y_n=y(x,z_n) $" src="form_94.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dxv</td><td>The <img class="formulaInl" alt="$F \times V$" src="form_95.png"/> Jacobian of the inv. sensor model wrt the robot pose <img class="formulaInl" alt="$ \frac{\partial y_n}{\partial x_v} $" src="form_96.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dhn</td><td>The <img class="formulaInl" alt="$F \times O$" src="form_97.png"/> Jacobian of the inv. sensor model wrt the observation vector <img class="formulaInl" alt="$ \frac{\partial y_n}{\partial h_n} $" src="form_98.png"/>.</td></tr>
</table>
</dd>
</dl>
<ul>
<li>O: OBS_SIZE</li>
<li>V: VEH_SIZE</li>
<li>F: FEAT_SIZE</li>
</ul>
<dl class="note"><dt><b>Note:</b></dt><dd>OnNewLandmarkAddedToMap will be also called after calling this method if a landmark is actually being added to the map. </dd></dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a647a12e0844df2ead68949d5ed33967e">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="af7c70d63832d8d45d8c5de0ed6041109"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnInverseObservationModel" ref="af7c70d63832d8d45d8c5de0ed6041109" args="(const KFArray_OBS &in_z, KFArray_FEAT &out_yn, KFMatrix_FxV &out_dyn_dxv, KFMatrix_FxO &out_dyn_dhn, KFMatrix_FxF &out_dyn_dhn_R_dyn_dhnT, bool &out_use_dyn_dhn_jacobian) const " -->
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<td class="memname">virtual void mrpt::bayes::CKalmanFilterCapable::OnInverseObservationModel </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> & </td>
<td class="paramname"><em>in_z</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> & </td>
<td class="paramname"><em>out_yn</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#affb2aa897e6434f6572d48ff1be1988e">KFMatrix_FxV</a> & </td>
<td class="paramname"><em>out_dyn_dxv</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a253bf3d53d25e20ec0592868efdba607">KFMatrix_FxO</a> & </td>
<td class="paramname"><em>out_dyn_dhn</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad8a2b4b92969f736bf6c147804b50614">KFMatrix_FxF</a> & </td>
<td class="paramname"><em>out_dyn_dhn_R_dyn_dhnT</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">bool & </td>
<td class="paramname"><em>out_use_dyn_dhn_jacobian</em> </td>
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<td>)</td>
<td></td><td> const<code> [inline, protected, virtual, inherited]</code></td>
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<p>If applicable to the given problem, this method implements the inverse observation model needed to extend the "map" with a new "element". </p>
<p>The uncertainty in the new map feature comes from two parts: one from the vehicle uncertainty (through the out_dyn_dxv Jacobian), and another from the uncertainty in the observation itself. By default, out_use_dyn_dhn_jacobian=true on call, and if it's left at "true", the base KalmanFilter class will compute the uncertainty of the landmark relative position from out_dyn_dhn. Only in some problems (e.g. MonoSLAM), it'll be needed for the application to directly return the covariance matrix <em>out_dyn_dhn_R_dyn_dhnT</em>, which is the equivalent to:</p>
<p><img class="formulaInl" alt="$ \frac{\partial y_n}{\partial h_n} R \frac{\partial y_n}{\partial h_n}^\top $" src="form_99.png"/>.</p>
<p>but may be computed from additional terms, or whatever needed by the user.</p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">in_z</td><td>The observation vector whose inverse sensor model is to be computed. This is actually one of the vector<> returned by OnGetObservationsAndDataAssociation(). </td></tr>
<tr><td class="paramname">out_yn</td><td>The F-length vector with the inverse observation model <img class="formulaInl" alt="$ y_n=y(x,z_n) $" src="form_94.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dxv</td><td>The <img class="formulaInl" alt="$F \times V$" src="form_95.png"/> Jacobian of the inv. sensor model wrt the robot pose <img class="formulaInl" alt="$ \frac{\partial y_n}{\partial x_v} $" src="form_96.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dhn</td><td>The <img class="formulaInl" alt="$F \times O$" src="form_97.png"/> Jacobian of the inv. sensor model wrt the observation vector <img class="formulaInl" alt="$ \frac{\partial y_n}{\partial h_n} $" src="form_98.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dhn_R_dyn_dhnT</td><td>See the discussion above.</td></tr>
</table>
</dd>
</dl>
<ul>
<li>O: OBS_SIZE</li>
<li>V: VEH_SIZE</li>
<li>F: FEAT_SIZE</li>
</ul>
<dl class="note"><dt><b>Note:</b></dt><dd>OnNewLandmarkAddedToMap will be also called after calling this method if a landmark is actually being added to the map. </dd></dl>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00383">383</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a1073193e03d2f4ff2038fa84ccdd4653"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnNewLandmarkAddedToMap" ref="a1073193e03d2f4ff2038fa84ccdd4653" args="(const size_t in_obsIdx, const size_t in_idxNewFeat)" -->
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<td>(</td>
<td class="paramtype">const size_t </td>
<td class="paramname"><em>in_obsIdx</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const size_t </td>
<td class="paramname"><em>in_idxNewFeat</em> </td>
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<td></td><td><code> [protected, virtual]</code></td>
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<p>If applicable to the given problem, do here any special handling of adding a new landmark to the map. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">in_obsIndex</td><td>The index of the observation whose inverse sensor is to be computed. It corresponds to the row in in_z where the observation can be found. </td></tr>
<tr><td class="paramname">in_idxNewFeat</td><td>The index that this new feature will have in the state vector (0:just after the vehicle state, 1: after that,...). Save this number so data association can be done according to these indices. </td></tr>
</table>
</dd>
</dl>
<dl class="see"><dt><b>See also:</b></dt><dd><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a4f261c0cc2bce890b65fdbc07f1cdb25" title="If applicable to the given problem, this method implements the inverse observation model needed to ex...">OnInverseObservationModel</a> </dd></dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a41be072d4693b55225b484c249db5fc2">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="aa3d99ee710bbdbdcd21bc2512ef52f9d"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnNormalizeStateVector" ref="aa3d99ee710bbdbdcd21bc2512ef52f9d" args="()" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnNormalizeStateVector </td>
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<td class="paramname"></td><td>)</td>
<td><code> [protected, virtual]</code></td>
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<p>This method is called after the prediction and after the update, to give the user an opportunity to normalize the state vector (eg, keep angles within -pi,pi range) if the application requires it. </p>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8a5246ad413ba2f6121b9f7f261283b8">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="accfee66b72edc2288df16e0686792879"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnObservationJacobians" ref="accfee66b72edc2288df16e0686792879" args="(const size_t &idx_landmark_to_predict, KFMatrix_OxV &Hx, KFMatrix_OxF &Hy) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnObservationJacobians </td>
<td>(</td>
<td class="paramtype">const size_t & </td>
<td class="paramname"><em>idx_landmark_to_predict</em>, </td>
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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ab0ddb67c05616e7fc1fcabe9cc04c753">KFMatrix_OxV</a> & </td>
<td class="paramname"><em>Hx</em>, </td>
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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ada78f649a58aa64c3db6c8b436b5ceba">KFMatrix_OxF</a> & </td>
<td class="paramname"><em>Hy</em> </td>
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<td>)</td>
<td></td><td> const<code> [protected, virtual]</code></td>
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<p>Implements the observation Jacobians <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial x} $" src="form_92.png"/> and (when applicable) <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial y_i} $" src="form_93.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">idx_landmark_to_predict</td><td>The index of the landmark in the map whose prediction is expected as output. For non SLAM-like problems, this will be zero and the expected output is for the whole state vector. </td></tr>
<tr><td class="paramname">Hx</td><td>The output Jacobian <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial x} $" src="form_92.png"/>. </td></tr>
<tr><td class="paramname">Hy</td><td>The output Jacobian <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial y_i} $" src="form_93.png"/>. </td></tr>
</table>
</dd>
</dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a45e3d11533732ae6fdc6f0d8a0c6a16e">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a6527eb56311535ab9b84dc48f3faf9b0"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnObservationJacobiansNumericGetIncrements" ref="a6527eb56311535ab9b84dc48f3faf9b0" args="(KFArray_VEH &out_veh_increments, KFArray_FEAT &out_feat_increments) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnObservationJacobiansNumericGetIncrements </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a> & </td>
<td class="paramname"><em>out_veh_increments</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a0b5b72d68126a91918ce085789da06bd">KFArray_FEAT</a> & </td>
<td class="paramname"><em>out_feat_increments</em> </td>
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<p>Only called if using a numeric approximation of the observation Jacobians, this method must return the increments in each dimension of the vehicle state vector while estimating the Jacobian. </p>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#acbba7768aa0513f67e30628787e429c2">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="aa8a021990239ac720ee2c44dd2b715e9"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnObservationModel" ref="aa8a021990239ac720ee2c44dd2b715e9" args="(const vector_size_t &idx_landmarks_to_predict, vector_KFArray_OBS &out_predictions) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnObservationModel </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> & </td>
<td class="paramname"><em>idx_landmarks_to_predict</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> & </td>
<td class="paramname"><em>out_predictions</em> </td>
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<td>)</td>
<td></td><td> const<code> [protected, virtual]</code></td>
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<p>Implements the observation prediction <img class="formulaInl" alt="$ h_i(x) $" src="form_91.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">idx_landmark_to_predict</td><td>The indices of the landmarks in the map whose predictions are expected as output. For non SLAM-like problems, this input value is undefined and the application should just generate one observation for the given problem. </td></tr>
<tr><td class="paramname">out_predictions</td><td>The predicted observations. </td></tr>
</table>
</dd>
</dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a27de563ddb767f0cf75ff7a53e532b1a">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a5a3514fd81d6f81b8ff7b2c72dfae33e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnPostIteration" ref="a5a3514fd81d6f81b8ff7b2c72dfae33e" args="()" -->
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<td class="memname">virtual void mrpt::bayes::CKalmanFilterCapable::OnPostIteration </td>
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<p>This method is called after finishing one KF iteration and before returning from runOneKalmanIteration(). </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00419">419</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a5d32610c2440162beb39617879d1b79c"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnPreComputingPredictions" ref="a5d32610c2440162beb39617879d1b79c" args="(const vector_KFArray_OBS &in_all_prediction_means, vector_size_t &out_LM_indices_to_predict) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnPreComputingPredictions </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#aa0e71d2a45e5d935eba18d817bb31cf9">vector_KFArray_OBS</a> & </td>
<td class="paramname"><em>in_all_prediction_means</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> & </td>
<td class="paramname"><em>out_LM_indices_to_predict</em> </td>
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<td>)</td>
<td></td><td> const<code> [protected, virtual]</code></td>
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<p>This will be called before OnGetObservationsAndDataAssociation to allow the application to reduce the number of covariance landmark predictions to be made. </p>
<p>For example, features which are known to be "out of sight" shouldn't be added to the output list to speed up the calculations. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">in_all_prediction_means</td><td>The mean of each landmark predictions; the computation or not of the corresponding covariances is what we're trying to determined with this method. </td></tr>
<tr><td class="paramname">out_LM_indices_to_predict</td><td>The list of landmark indices in the map [0,<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1ac5b0adbbd3a0e5122ebb148ff3e7ad">getNumberOfLandmarksInTheMap()</a>-1] that should be predicted. </td></tr>
</table>
</dd>
</dl>
<dl class="note"><dt><b>Note:</b></dt><dd>This is not a pure virtual method, so it should be implemented only if desired. The default implementation returns a vector with all the landmarks in the map. </dd></dl>
<dl class="see"><dt><b>See also:</b></dt><dd>OnGetObservations, OnDataAssociation </dd></dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a505fa1e6eb8a300e0e1171a26b4f5b15">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="ac209037604fb37a25d7b56f4c1fb4781"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnSubstractObservationVectors" ref="ac209037604fb37a25d7b56f4c1fb4781" args="(KFArray_OBS &A, const KFArray_OBS &B) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnSubstractObservationVectors </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> & </td>
<td class="paramname"><em>A</em>, </td>
</tr>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6c1b24a2c7b35e77411888a06de4e59d">KFArray_OBS</a> & </td>
<td class="paramname"><em>B</em> </td>
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<td>)</td>
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<p>Computes A=A-B, which may need to be re-implemented depending on the topology of the individual scalar components (eg, angles). </p>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a2875f05e00d512746e6a39244fb28561">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a40f4a9cbe853526f05abbeb93b535102"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionJacobian" ref="a40f4a9cbe853526f05abbeb93b535102" args="(KFMatrix_VxV &out_F) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionJacobian </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8dd3e63dd847fd98ef59b472e46cad2c">KFMatrix_VxV</a> & </td>
<td class="paramname"><em>out_F</em></td><td>)</td>
<td> const<code> [protected, virtual]</code></td>
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<p>Implements the transition Jacobian <img class="formulaInl" alt="$ \frac{\partial f}{\partial x} $" src="form_29.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_F</td><td>Must return the Jacobian. The returned matrix must be <img class="formulaInl" alt="$V \times V$" src="form_89.png"/> with V being either the size of the whole state vector (for non-SLAM problems) or VEH_SIZE (for SLAM problems). </td></tr>
</table>
</dd>
</dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a9102af2605891c4b76ef1216013da46d">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="afb9ddb3cff1724e22e616fe0610681ab"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionJacobianNumericGetIncrements" ref="afb9ddb3cff1724e22e616fe0610681ab" args="(KFArray_VEH &out_increments) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionJacobianNumericGetIncrements </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a> & </td>
<td class="paramname"><em>out_increments</em></td><td>)</td>
<td> const<code> [protected, virtual]</code></td>
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<p>Only called if using a numeric approximation of the transition Jacobian, this method must return the increments in each dimension of the vehicle state vector while estimating the Jacobian. </p>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6546398d63e8298f0b0a59a86e2395a7">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a3ea632d9fe8529f381c4c6d259a2ff9d"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionModel" ref="a3ea632d9fe8529f381c4c6d259a2ff9d" args="(const KFArray_ACT &in_u, KFArray_VEH &inout_x, bool &out_skipPrediction) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionModel </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a6454c68e3c45da92e2bbb3e8aa8f6f70">KFArray_ACT</a> & </td>
<td class="paramname"><em>in_u</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad4f1667845ca7553925160142821cff0">KFArray_VEH</a> & </td>
<td class="paramname"><em>inout_x</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">bool & </td>
<td class="paramname"><em>out_skipPrediction</em> </td>
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<td>)</td>
<td></td><td> const<code> [protected, virtual]</code></td>
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<p>Implements the transition model <img class="formulaInl" alt="$ \hat{x}_{k|k-1} = f( \hat{x}_{k-1|k-1}, u_k ) $" src="form_86.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">in_u</td><td>The vector returned by OnGetAction. </td></tr>
<tr><td class="paramname">inout_x</td><td>At input has <p class="formulaDsp">
<img class="formulaDsp" alt="\[ \hat{x}_{k-1|k-1} \]" src="form_87.png"/>
</p>
, at output must have <img class="formulaInl" alt="$ \hat{x}_{k|k-1} $" src="form_88.png"/> . </td></tr>
<tr><td class="paramname">out_skip</td><td>Set this to true if for some reason you want to skip the prediction step (to do not modify either the vector or the covariance). Default:false </td></tr>
</table>
</dd>
</dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a006b2619c480312a774ba3443efbe0a5">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a492735723c8e453b8bda0acbb6d4f271"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionNoise" ref="a492735723c8e453b8bda0acbb6d4f271" args="(KFMatrix_VxV &out_Q) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionNoise </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a8dd3e63dd847fd98ef59b472e46cad2c">KFMatrix_VxV</a> & </td>
<td class="paramname"><em>out_Q</em></td><td>)</td>
<td> const<code> [protected, virtual]</code></td>
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<p>Implements the transition noise covariance <img class="formulaInl" alt="$ Q_k $" src="form_90.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">out_Q</td><td>Must return the covariance matrix. The returned matrix must be of the same size than the jacobian from OnTransitionJacobian </td></tr>
</table>
</dd>
</dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a77cdfd45b0173035594248d605b49306">mrpt::bayes::CKalmanFilterCapable< 3, 2, 2, 3 ></a>.</p>
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<a class="anchor" id="a7e49c6adb04d37516a76beed1e24d357"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::processActionObservation" ref="a7e49c6adb04d37516a76beed1e24d357" args="(CActionCollectionPtr &action, CSensoryFramePtr &SF)" -->
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<td class="paramtype"><a class="el" href="structmrpt_1_1slam_1_1_c_action_collection_ptr.html">CActionCollectionPtr</a> & </td>
<td class="paramname"><em>action</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="structmrpt_1_1slam_1_1_c_sensory_frame_ptr.html">CSensoryFramePtr</a> & </td>
<td class="paramname"><em>SF</em> </td>
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<td>)</td>
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<p>Process one new action and observations to update the map and robot pose estimate. </p>
<p>See the description of the class at the top of this page. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">action</td><td>May contain odometry </td></tr>
<tr><td class="paramname">SF</td><td>The set of observations, must contain at least one <a class="el" href="classmrpt_1_1slam_1_1_c_observation_bearing_range.html" title="This observation represents a number of range-bearing value pairs, each one for a detected landmark...">CObservationBearingRange</a> </td></tr>
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</dd>
</dl>
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<a class="anchor" id="aa357feee7d822d0089f8082fb7b64442"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::reset" ref="aa357feee7d822d0089f8082fb7b64442" args="()" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM2D::reset </td>
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<p>Reset the state of the SLAM filter: The map is emptied and the robot put back to (0,0,0). </p>
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<a class="anchor" id="aeebd325f91acbf7d27134c8c7388649e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::runOneKalmanIteration" ref="aeebd325f91acbf7d27134c8c7388649e" args="()" -->
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<td class="memname">void mrpt::bayes::CKalmanFilterCapable::runOneKalmanIteration </td>
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<p>The main entry point, executes one complete step: prediction + update. </p>
<p>It is protected since derived classes must provide a problem-specific entry point for users. The exact order in which this method calls the virtual method is explained in <a href="http://www.mrpt.org/Kalman_Filters">http://www.mrpt.org/Kalman_Filters</a> </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00459">459</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a64f299d6a113132637a54342dc3da1cc"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::saveMapAndPath2DRepresentationAsMATLABFile" ref="a64f299d6a113132637a54342dc3da1cc" args="(const std::string &fil, float stdCount=3.0f, const std::string &styleLandmarks=std::string("b"), const std::string &stylePath=std::string("r"), const std::string &styleRobot=std::string("r")) const " -->
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<td class="paramtype">const <a class="el" href="classstd_1_1string.html">std::string</a> & </td>
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<td class="paramtype">const <a class="el" href="classstd_1_1string.html">std::string</a> & </td>
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<td class="paramtype">const <a class="el" href="classstd_1_1string.html">std::string</a> & </td>
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<p>Save the current state of the filter (robot pose & map) to a MATLAB script which displays all the elements in 2D. </p>
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<hr/><h2>Friends And Related Function Documentation</h2>
<a class="anchor" id="a1f7c0688afe03ffd6f14c4e9f4e5a050"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::detail::CRunOneKalmanIteration_addNewLandmarks" ref="a1f7c0688afe03ffd6f14c4e9f4e5a050" args="" -->
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<td class="memname">friend struct detail::CRunOneKalmanIteration_addNewLandmarks<code> [friend, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l01499">1499</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<hr/><h2>Member Data Documentation</h2>
<a class="anchor" id="a88651951bad5ea93ae84d848aeed6414"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::KF_options" ref="a88651951bad5ea93ae84d848aeed6414" args="" -->
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<td class="memname"><a class="el" href="structmrpt_1_1bayes_1_1_t_k_f__options.html">TKF_options</a> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a88651951bad5ea93ae84d848aeed6414">mrpt::bayes::CKalmanFilterCapable::KF_options</a><code> [inherited]</code></td>
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<p>Generic options for the Kalman Filter algorithm itself. </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00433">433</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="aa252e8d11ce89ce7ff01696269bf0f74"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_action" ref="aa252e8d11ce89ce7ff01696269bf0f74" args="" -->
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<td class="memname"><a class="el" href="structmrpt_1_1slam_1_1_c_action_collection_ptr.html">CActionCollectionPtr</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aa252e8d11ce89ce7ff01696269bf0f74">mrpt::slam::CRangeBearingKFSLAM2D::m_action</a><code> [protected]</code></td>
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<p>Set up by processActionObservation. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00344">344</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="a804919da59c1ddc75e6b481a24ee6749"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_IDs" ref="a804919da59c1ddc75e6b481a24ee6749" args="" -->
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<td class="memname"><a class="el" href="classmrpt_1_1utils_1_1bimap.html">mrpt::utils::bimap</a><<a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a>,unsigned int> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a804919da59c1ddc75e6b481a24ee6749">mrpt::slam::CRangeBearingKFSLAM2D::m_IDs</a><code> [protected]</code></td>
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<p>The mapping between landmark IDs and indexes in the Pkk cov. </p>
<p>matrix: </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00352">352</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="abc2f94171c9219ee807c5bbafc2ac611"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_last_data_association" ref="abc2f94171c9219ee807c5bbafc2ac611" args="" -->
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<td class="memname"><a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_data_assoc_info.html">TDataAssocInfo</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#abc2f94171c9219ee807c5bbafc2ac611">mrpt::slam::CRangeBearingKFSLAM2D::m_last_data_association</a><code> [protected]</code></td>
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<p>Last data association. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00358">358</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="a15c291ca9eb40996381dc0e60f01d533"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_pkk" ref="a15c291ca9eb40996381dc0e60f01d533" args="" -->
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<td class="memname"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#ad214112622ea8531c9a7c052f93600bd">KFMatrix</a> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a15c291ca9eb40996381dc0e60f01d533">mrpt::bayes::CKalmanFilterCapable::m_pkk</a><code> [protected, inherited]</code></td>
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<p>The system full covariance matrix. </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00205">205</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="ae2df87aa3d1cc8cbf8a88fab1ea68dbd"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_SF" ref="ae2df87aa3d1cc8cbf8a88fab1ea68dbd" args="" -->
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<td class="memname"><a class="el" href="structmrpt_1_1slam_1_1_c_sensory_frame_ptr.html">CSensoryFramePtr</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#ae2df87aa3d1cc8cbf8a88fab1ea68dbd">mrpt::slam::CRangeBearingKFSLAM2D::m_SF</a><code> [protected]</code></td>
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<p>Set up by processActionObservation. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00348">348</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="a7add6e75a3f51e219bbb3d7e0e428c63"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_SFs" ref="a7add6e75a3f51e219bbb3d7e0e428c63" args="" -->
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<td class="memname"><a class="el" href="classmrpt_1_1slam_1_1_c_simple_map.html">CSimpleMap</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#a7add6e75a3f51e219bbb3d7e0e428c63">mrpt::slam::CRangeBearingKFSLAM2D::m_SFs</a><code> [protected]</code></td>
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<p>The sequence of all the observations and the robot path (kept for debugging, statistics,etc) </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00356">356</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<a class="anchor" id="a3eff55c428065c52bd2f9418e3944e48"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_timLogger" ref="a3eff55c428065c52bd2f9418e3944e48" args="" -->
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<td class="memname"><a class="el" href="classmrpt_1_1utils_1_1_c_time_logger.html">mrpt::utils::CTimeLogger</a> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a3eff55c428065c52bd2f9418e3944e48">mrpt::bayes::CKalmanFilterCapable::m_timLogger</a><code> [protected, inherited]</code></td>
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<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00209">209</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<a class="anchor" id="a7e8948c9d209c23517c45c6494b46147"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM2D::m_xkk" ref="a7e8948c9d209c23517c45c6494b46147" args="" -->
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<td class="memname"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a9a120b286d286048985b059aa721e0c1">KFVector</a> <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a7e8948c9d209c23517c45c6494b46147">mrpt::bayes::CKalmanFilterCapable::m_xkk</a><code> [protected, inherited]</code></td>
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<p>The system state vector. </p>
<p>Definition at line <a class="el" href="_c_kalman_filter_capable_8h_source.html#l00204">204</a> of file <a class="el" href="_c_kalman_filter_capable_8h_source.html">CKalmanFilterCapable.h</a>.</p>
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<td class="memname"><a class="el" href="structmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d_1_1_t_options.html">TOptions</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html#aaac671183aab10c91682e180b1d4dddf">mrpt::slam::CRangeBearingKFSLAM2D::options</a></td>
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<p>The options for the algorithm. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html#l00151">151</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m2_d_8h_source.html">CRangeBearingKFSLAM2D.h</a>.</p>
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<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>
