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<title>The MRPT project: mrpt::slam::CRangeBearingKFSLAM Class Reference</title>
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<h1>mrpt::slam::CRangeBearingKFSLAM Class Reference</h1> </div>
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<!-- doxytag: class="mrpt::slam::CRangeBearingKFSLAM" --><!-- doxytag: inherits="mrpt::bayes::CKalmanFilterCapable" --><hr/><a name="_details"></a><h2>Detailed Description</h2>
<p>An implementation of EKF-based SLAM with range-bearing sensors, odometry, a full 6D robot pose, and 3D landmarks. </p>
<p>The main method is "processActionObservation" which processes pairs of action/observation. The state vector comprises: 3D robot position, a quaternion for its attitude, and the 3D landmarks in the map.</p>
<p>The following Wiki page describes an front-end application based on this class: <a href="http://www.mrpt.org/Application:kf-slam">http://www.mrpt.org/Application:kf-slam</a></p>
<p>For the theory behind this implementation, see the technical report in: <a href="http://www.mrpt.org/6D-SLAM">http://www.mrpt.org/6D-SLAM</a></p>
<dl class="see"><dt><b>See also:</b></dt><dd>An implementation for 2D only: <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m2_d.html" title="An implementation of EKF-based SLAM with range-bearing sensors, odometry, and a 2D (+heading) robot p...">CRangeBearingKFSLAM2D</a> </dd></dl>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00073">73</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
<p><code>#include <<a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">mrpt/slam/CRangeBearingKFSLAM.h</a>></code></p>
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Inheritance diagram for mrpt::slam::CRangeBearingKFSLAM:<!-- endSectionHeader --></div>
<!-- startSectionSummary --><!-- endSectionSummary --><!-- startSectionContent --><div class="dyncontent">
<div class="center"><img src="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m__inherit__graph.png" border="0" usemap="#mrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m_inherit__map" alt="Inheritance graph"/></div>
<map name="mrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m_inherit__map" id="mrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m_inherit__map">
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<center><span class="legend">[<a href="graph_legend.html">legend</a>]</span></center><!-- endSectionContent --></div>
<p><a href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m-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_m_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_m_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_m_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_m_1_1_t_options.html#_details">More...</a><br/></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_m.html#ab311777a3ee4d32e3ec9a63c4700982e">CRangeBearingKFSLAM</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Constructor. <a href="#ab311777a3ee4d32e3ec9a63c4700982e"></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_m.html#a599b5a6803bfbb9ff50bd02e8345ec16">~CRangeBearingKFSLAM</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Destructor: <a href="#a599b5a6803bfbb9ff50bd02e8345ec16"></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_m.html#af9059f0687f3232c0193df0d89109b3b">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="#af9059f0687f3232c0193df0d89109b3b"></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_m.html#a4078708d1e866ff4811fee64e4dba56f">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="#a4078708d1e866ff4811fee64e4dba56f"></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_m.html#a1acf405f8438ca684f3070deec305a51">getCurrentState</a> (<a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat_p_d_f_gaussian.html">CPose3DQuatPDFGaussian</a> &out_robotPose, std::vector< <a class="el" href="classmrpt_1_1poses_1_1_c_point3_d.html">CPoint3D</a> > &out_landmarksPositions, std::map< unsigned int, <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a> > &out_landmarkIDs, <a class="el" href="structmrpt_1_1dynamicsize__vector.html">CVectorDouble</a> &out_fullState, <a class="el" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">CMatrixDouble</a> &out_fullCovariance) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the complete mean and cov. <a href="#a1acf405f8438ca684f3070deec305a51"></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_m.html#ad1fd063b3d4d844943452dec21b351bc">getCurrentState</a> (<a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_p_d_f_gaussian.html">CPose3DPDFGaussian</a> &out_robotPose, std::vector< <a class="el" href="classmrpt_1_1poses_1_1_c_point3_d.html">CPoint3D</a> > &out_landmarksPositions, std::map< unsigned int, <a class="el" href="classmrpt_1_1slam_1_1_c_landmark.html#a7d42fbd58a31278cb344b78ce8af3cf9">CLandmark::TLandmarkID</a> > &out_landmarkIDs, <a class="el" href="structmrpt_1_1dynamicsize__vector.html">CVectorDouble</a> &out_fullState, <a class="el" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">CMatrixDouble</a> &out_fullCovariance) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the complete mean and cov. <a href="#ad1fd063b3d4d844943452dec21b351bc"></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_m.html#a2e7bda8569961196979350e86be73364">getCurrentRobotPose</a> (<a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat_p_d_f_gaussian.html">CPose3DQuatPDFGaussian</a> &out_robotPose) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the mean & the 7x7 covariance matrix of the robot 6D pose (with rotation as a quaternion). <a href="#a2e7bda8569961196979350e86be73364"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat.html">mrpt::poses::CPose3DQuat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#aaf63d77982fb598a3859ecdca7f45c7c">getCurrentRobotPoseMean</a> () const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Get the current robot pose mean, as a 3D+quaternion pose. <a href="#aaf63d77982fb598a3859ecdca7f45c7c"></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_m.html#a99a9e916ddc3b00015732bd6f971750e">getCurrentRobotPose</a> (<a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_p_d_f_gaussian.html">CPose3DPDFGaussian</a> &out_robotPose) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Returns the mean & the 6x6 covariance matrix of the robot 6D pose (with rotation as 3 angles). <a href="#a99a9e916ddc3b00015732bd6f971750e"></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_m.html#a36fc338a038b682c3c41ac4073d64763">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="#a36fc338a038b682c3c41ac4073d64763"></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_m.html#aba9f4e0e1ee10f0b75f812910d62e90c">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="#aba9f4e0e1ee10f0b75f812910d62e90c"></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_m_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_m.html#a33ef299adf1aa1774b4be0c3a0eaa9a4">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="#a33ef299adf1aa1774b4be0c3a0eaa9a4"></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_m.html#aa27ce863f1d277c07acddde20a664e52">getLastPartition</a> (std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > &parts)</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Return the last partition of the sequence of sensoryframes (it is NOT a partition of the map!!) Only if options.doPartitioningExperiment = true. <a href="#aa27ce863f1d277c07acddde20a664e52"></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_m.html#af51ee48428140f4e9acba5681a1628c9">getLastPartitionLandmarks</a> (std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > &landmarksMembership) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Return the partitioning of the landmarks in clusters accoring to the last partition. <a href="#af51ee48428140f4e9acba5681a1628c9"></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_m.html#a75aad7ea4eebbd9423e6fae90f660261">getLastPartitionLandmarksAsIfFixedSubmaps</a> (size_t <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a2bc3c77992071ac4cb84db74e912ed05">K</a>, std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > &landmarksMembership)</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">For testing only: returns the partitioning as "getLastPartitionLandmarks" but as if a fixed-size submaps (size K) were have been used. <a href="#a75aad7ea4eebbd9423e6fae90f660261"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">double </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a4d5ef9d10eafb2da571de792f29ca08a">computeOffDiagonalBlocksApproximationError</a> (const std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > &landmarksMembership) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Computes the ratio of the missing information matrix elements which are ignored under a certain partitioning of the landmarks. <a href="#a4d5ef9d10eafb2da571de792f29ca08a"></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_m.html#abd45878bf309cc13e4f1d191735c9b66">reconsiderPartitionsNow</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">The partitioning of the entire map is recomputed again. <a href="#abd45878bf309cc13e4f1d191735c9b66"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="structmrpt_1_1slam_1_1_c_incremental_map_partitioner_1_1_t_options.html">CIncrementalMapPartitioner::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_m.html#afbaf941fcb4fa7acd32092835d400f41">mapPartitionOptions</a> ()</td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Provides access to the parameters of the map partitioning algorithm. <a href="#afbaf941fcb4fa7acd32092835d400f41"></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_m.html#a352973625e66b155037052e034fb1cbc">saveMapAndPath2DRepresentationAsMATLABFile</a> (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 </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="#a352973625e66b155037052e034fb1cbc"></a><br/></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_m_1_1_t_options.html">mrpt::slam::CRangeBearingKFSLAM::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_m.html#a267ffb78c2afd09a7f5b2b81acf31be1">options</a></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"><a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat.html">mrpt::poses::CPose3DQuat</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#ab4077c1ca51cb945fdada8ade91e27d9">getIncrementFromOdometry</a> () const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Return the last odometry, as a pose increment. <a href="#ab4077c1ca51cb945fdada8ade91e27d9"></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_m.html#afd5c9c6ce16f81f5639e511bc1e474f8">OnGetAction</a> (<a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_ACT</a> &out_u) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Must return the action vector u. <a href="#afd5c9c6ce16f81f5639e511bc1e474f8"></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_m.html#a068baea8f069e9016c9a1e7336cfdfd1">OnTransitionModel</a> (const <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_ACT</a> &in_u, <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">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 ) $" src="form_87.png"/>. <a href="#a068baea8f069e9016c9a1e7336cfdfd1"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#abfa7d23c6a1b88b6877345ec68fac4b9">OnTransitionJacobian</a> (<a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_VxV</a> &out_F) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the transition Jacobian <img class="formulaInl" alt="$ \frac{\partial f}{\partial x} $" src="form_29.png"/>. <a href="#abfa7d23c6a1b88b6877345ec68fac4b9"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a671e5190f4701458ae0a784c8d65ffa8">OnTransitionNoise</a> (<a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_VxV</a> &out_Q) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the transition noise covariance <img class="formulaInl" alt="$ Q_k $" src="form_91.png"/>. <a href="#a671e5190f4701458ae0a784c8d65ffa8"></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_m.html#a74f93f0a9a398aee4e51de1689127d11">OnGetObservationsAndDataAssociation</a> (<a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1321c340469c9905fca4a8682afcea4f">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#a1321c340469c9905fca4a8682afcea4f">vector_KFArray_OBS</a> &in_all_predictions, const <a class="el" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">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_1math_1_1_c_matrix_fixed_numeric.html">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="#a74f93f0a9a398aee4e51de1689127d11"></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_m.html#ad985328f6b30810aee2da489f505ddb1">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#a1321c340469c9905fca4a8682afcea4f">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) $" src="form_92.png"/>. <a href="#ad985328f6b30810aee2da489f505ddb1"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a16b2fccffc944e6e0af70a17b8c234e8">OnObservationJacobians</a> (const size_t &idx_landmark_to_predict, <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_OxV</a> &Hx, <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_OxF</a> &Hy) const </td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Implements the observation Jacobians <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial x} $" src="form_93.png"/> and (when applicable) <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial y_i} $" src="form_94.png"/>. <a href="#a16b2fccffc944e6e0af70a17b8c234e8"></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_m.html#a4debf44b3dd2ea88b9f5c37c2d0fd024">OnSubstractObservationVectors</a> (<a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_OBS</a> &A, const <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">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="#a4debf44b3dd2ea88b9f5c37c2d0fd024"></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_m.html#afd569099f5505026e762547e143dc629">OnGetObservationNoise</a> (<a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">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="#afd569099f5505026e762547e143dc629"></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_m.html#af56a4f99f7f558fb7ac383b5d5c1febc">OnPreComputingPredictions</a> (const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1321c340469c9905fca4a8682afcea4f">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="#af56a4f99f7f558fb7ac383b5d5c1febc"></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_m.html#a61b31c958f5ef1f119588538818de59c">OnInverseObservationModel</a> (const <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_OBS</a> &in_z, <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_FEAT</a> &out_yn, <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_FxV</a> &out_dyn_dxv, <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">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="#a61b31c958f5ef1f119588538818de59c"></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_m.html#a21d5fd42e86d10792e530aef75d9baf2">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="#a21d5fd42e86d10792e530aef75d9baf2"></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_m.html#abcc9fe624ee79796dd0db27b4b29f084">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="#abcc9fe624ee79796dd0db27b4b29f084"></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_m.html#a325aa177708f2e1203f9a8b1ad060b3e">m_action</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Set up by processActionObservation. <a href="#a325aa177708f2e1203f9a8b1ad060b3e"></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_m.html#a9ceb909016d80c7c1f8ea9080eef89cb">m_SF</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Set up by processActionObservation. <a href="#a9ceb909016d80c7c1f8ea9080eef89cb"></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_m.html#a63ce956a06ecc55a8e8c7de2b59244d8">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="#a63ce956a06ecc55a8e8c7de2b59244d8"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top"><a class="el" href="classmrpt_1_1slam_1_1_c_incremental_map_partitioner.html">CIncrementalMapPartitioner</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a97aa37a9b59183096fe486544b1b4d87">mapPartitioner</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Used for map partitioning experiments. <a href="#a97aa37a9b59183096fe486544b1b4d87"></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_m.html#a7bce6dc04978cb42d426c00c476b9e77">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="#a7bce6dc04978cb42d426c00c476b9e77"></a><br/></td></tr>
<tr><td class="memItemLeft" align="right" valign="top">std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a099e1451f9addc6543c737f749deb60a">m_lastPartitionSet</a></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_m_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_m.html#a129a478e617bb6f5be7ded15fee98a7b">m_last_data_association</a></td></tr>
<tr><td class="mdescLeft"> </td><td class="mdescRight">Last data association. <a href="#a129a478e617bb6f5be7ded15fee98a7b"></a><br/></td></tr>
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<hr/><h2>Constructor & Destructor Documentation</h2>
<a class="anchor" id="ab311777a3ee4d32e3ec9a63c4700982e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::CRangeBearingKFSLAM" ref="ab311777a3ee4d32e3ec9a63c4700982e" args="()" -->
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<td class="memname">mrpt::slam::CRangeBearingKFSLAM::CRangeBearingKFSLAM </td>
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<p>Constructor. </p>
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<a class="anchor" id="a599b5a6803bfbb9ff50bd02e8345ec16"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::~CRangeBearingKFSLAM" ref="a599b5a6803bfbb9ff50bd02e8345ec16" args="()" -->
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<td class="memname">virtual mrpt::slam::CRangeBearingKFSLAM::~CRangeBearingKFSLAM </td>
<td>(</td>
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<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="a4d5ef9d10eafb2da571de792f29ca08a"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::computeOffDiagonalBlocksApproximationError" ref="a4d5ef9d10eafb2da571de792f29ca08a" args="(const std::vector< vector_uint > &landmarksMembership) const " -->
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<td class="memname">double mrpt::slam::CRangeBearingKFSLAM::computeOffDiagonalBlocksApproximationError </td>
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<td class="paramtype">const std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > & </td>
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<p>Computes the ratio of the missing information matrix elements which are ignored under a certain partitioning of the landmarks. </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_m.html#af51ee48428140f4e9acba5681a1628c9" title="Return the partitioning of the landmarks in clusters accoring to the last partition.">getLastPartitionLandmarks</a>, <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a75aad7ea4eebbd9423e6fae90f660261" title="For testing only: returns the partitioning as "getLastPartitionLandmarks" but as if a fixed...">getLastPartitionLandmarksAsIfFixedSubmaps</a> </dd></dl>
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<a class="anchor" id="a36fc338a038b682c3c41ac4073d64763"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getAs3DObject" ref="a36fc338a038b682c3c41ac4073d64763" args="(mrpt::opengl::CSetOfObjectsPtr &outObj) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::getAs3DObject </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>
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<a class="anchor" id="a2e7bda8569961196979350e86be73364"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getCurrentRobotPose" ref="a2e7bda8569961196979350e86be73364" args="(CPose3DQuatPDFGaussian &out_robotPose) const " -->
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<p>Returns the mean & the 7x7 covariance matrix of the robot 6D pose (with rotation as a quaternion). </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_m.html#a1acf405f8438ca684f3070deec305a51" title="Returns the complete mean and cov.">getCurrentState</a>, <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#aaf63d77982fb598a3859ecdca7f45c7c" title="Get the current robot pose mean, as a 3D+quaternion pose.">getCurrentRobotPoseMean</a> </dd></dl>
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<a class="anchor" id="a99a9e916ddc3b00015732bd6f971750e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getCurrentRobotPose" ref="a99a9e916ddc3b00015732bd6f971750e" args="(CPose3DPDFGaussian &out_robotPose) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::getCurrentRobotPose </td>
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<p>Returns the mean & the 6x6 covariance matrix of the robot 6D pose (with rotation as 3 angles). </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_m.html#a1acf405f8438ca684f3070deec305a51" title="Returns the complete mean and cov.">getCurrentState</a> </dd></dl>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00146">146</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
<p>References <a class="el" href="_c_quaternion_8h_source.html#l00042">mrpt::math::UNINITIALIZED_QUATERNION</a>.</p>
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<a class="anchor" id="aaf63d77982fb598a3859ecdca7f45c7c"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getCurrentRobotPoseMean" ref="aaf63d77982fb598a3859ecdca7f45c7c" args="() const " -->
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<td class="memname"><a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat.html">mrpt::poses::CPose3DQuat</a> mrpt::slam::CRangeBearingKFSLAM::getCurrentRobotPoseMean </td>
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<p>Get the current robot pose mean, as a 3D+quaternion 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_m.html#a2e7bda8569961196979350e86be73364" title="Returns the mean & the 7x7 covariance matrix of the robot 6D pose (with rotation as a quaternion)...">getCurrentRobotPose</a> </dd></dl>
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<a class="anchor" id="a1acf405f8438ca684f3070deec305a51"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getCurrentState" ref="a1acf405f8438ca684f3070deec305a51" args="(CPose3DQuatPDFGaussian &out_robotPose, std::vector< CPoint3D > &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::CRangeBearingKFSLAM::getCurrentState </td>
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<td class="paramtype"><a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat_p_d_f_gaussian.html">CPose3DQuatPDFGaussian</a> & </td>
<td class="paramname"> <em>out_robotPose</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::vector< <a class="el" href="classmrpt_1_1poses_1_1_c_point3_d.html">CPoint3D</a> > & </td>
<td class="paramname"> <em>out_landmarksPositions</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::map< 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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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="structmrpt_1_1dynamicsize__vector.html">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="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">CMatrixDouble</a> & </td>
<td class="paramname"> <em>out_fullCovariance</em> </td>
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<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 and the 7x7 covariance matrix of the robot 6D pose </td></tr>
<tr><td class="paramname">out_landmarksPositions</td><td>One entry for each of the M landmark positions (3D). </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 (7+3M). </td></tr>
<tr><td class="paramname">out_fullCovariance</td><td>The full (7+3M)x(7+3M) 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_m.html#a2e7bda8569961196979350e86be73364" title="Returns the mean & the 7x7 covariance matrix of the robot 6D pose (with rotation as a quaternion)...">getCurrentRobotPose</a> </dd></dl>
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<a class="anchor" id="ad1fd063b3d4d844943452dec21b351bc"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getCurrentState" ref="ad1fd063b3d4d844943452dec21b351bc" args="(CPose3DPDFGaussian &out_robotPose, std::vector< CPoint3D > &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::CRangeBearingKFSLAM::getCurrentState </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_p_d_f_gaussian.html">CPose3DPDFGaussian</a> & </td>
<td class="paramname"> <em>out_robotPose</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::vector< <a class="el" href="classmrpt_1_1poses_1_1_c_point3_d.html">CPoint3D</a> > & </td>
<td class="paramname"> <em>out_landmarksPositions</em>, </td>
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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::map< 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>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="structmrpt_1_1dynamicsize__vector.html">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="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">CMatrixDouble</a> & </td>
<td class="paramname"> <em>out_fullCovariance</em> </td>
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<td>)</td>
<td></td><td> const<code> [inline]</code></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 and the 7x7 covariance matrix of the robot 6D pose </td></tr>
<tr><td class="paramname">out_landmarksPositions</td><td>One entry for each of the M landmark positions (3D). </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 (7+3M). </td></tr>
<tr><td class="paramname">out_fullCovariance</td><td>The full (7+3M)x(7+3M) 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_m.html#a2e7bda8569961196979350e86be73364" title="Returns the mean & the 7x7 covariance matrix of the robot 6D pose (with rotation as a quaternion)...">getCurrentRobotPose</a> </dd></dl>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00120">120</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
<p>References <a class="el" href="_c_quaternion_8h_source.html#l00042">mrpt::math::UNINITIALIZED_QUATERNION</a>.</p>
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<a class="anchor" id="ab4077c1ca51cb945fdada8ade91e27d9"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getIncrementFromOdometry" ref="ab4077c1ca51cb945fdada8ade91e27d9" args="() const " -->
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<td class="memname"><a class="el" href="classmrpt_1_1poses_1_1_c_pose3_d_quat.html">mrpt::poses::CPose3DQuat</a> mrpt::slam::CRangeBearingKFSLAM::getIncrementFromOdometry </td>
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<p>Return the last odometry, as a pose increment. </p>
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<a class="anchor" id="a33ef299adf1aa1774b4be0c3a0eaa9a4"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getLastDataAssociation" ref="a33ef299adf1aa1774b4be0c3a0eaa9a4" 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_m_1_1_t_data_assoc_info.html">TDataAssocInfo</a>& mrpt::slam::CRangeBearingKFSLAM::getLastDataAssociation </td>
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<td class="paramname"> )</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_m_8h_source.html#l00248">248</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="aa27ce863f1d277c07acddde20a664e52"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getLastPartition" ref="aa27ce863f1d277c07acddde20a664e52" args="(std::vector< vector_uint > &parts)" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::getLastPartition </td>
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<td class="paramtype">std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > & </td>
<td class="paramname"> <em>parts</em> )</td>
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<p>Return the last partition of the sequence of sensoryframes (it is NOT a partition of the map!!) Only if options.doPartitioningExperiment = true. </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_m.html#af51ee48428140f4e9acba5681a1628c9" title="Return the partitioning of the landmarks in clusters accoring to the last partition.">getLastPartitionLandmarks</a> </dd></dl>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00257">257</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="af51ee48428140f4e9acba5681a1628c9"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getLastPartitionLandmarks" ref="af51ee48428140f4e9acba5681a1628c9" args="(std::vector< vector_uint > &landmarksMembership) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::getLastPartitionLandmarks </td>
<td>(</td>
<td class="paramtype">std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > & </td>
<td class="paramname"> <em>landmarksMembership</em> )</td>
<td> const</td>
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<p>Return the partitioning of the landmarks in clusters accoring to the last partition. </p>
<p>Note that the same landmark may appear in different clusters (the partition is not in the space of landmarks) Only if options.doPartitioningExperiment = true </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">landmarksMembership</td><td>The i'th element of this vector is the set of clusters to which the i'th landmark in the map belongs to (landmark index != landmark ID !!). </td></tr>
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</dd>
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<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#aa27ce863f1d277c07acddde20a664e52" title="Return the last partition of the sequence of sensoryframes (it is NOT a partition of the map!!) Only ...">getLastPartition</a> </dd></dl>
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<a class="anchor" id="a75aad7ea4eebbd9423e6fae90f660261"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::getLastPartitionLandmarksAsIfFixedSubmaps" ref="a75aad7ea4eebbd9423e6fae90f660261" args="(size_t K, std::vector< vector_uint > &landmarksMembership)" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::getLastPartitionLandmarksAsIfFixedSubmaps </td>
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<td class="paramtype">size_t </td>
<td class="paramname"> <em>K</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">std::vector< <a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a> > & </td>
<td class="paramname"> <em>landmarksMembership</em> </td>
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<p>For testing only: returns the partitioning as "getLastPartitionLandmarks" but as if a fixed-size submaps (size K) were have been used. </p>
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<a class="anchor" id="aba9f4e0e1ee10f0b75f812910d62e90c"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::loadOptions" ref="aba9f4e0e1ee10f0b75f812910d62e90c" args="(const mrpt::utils::CConfigFileBase &ini)" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::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>
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<p>Load options from a ini-like file/text. </p>
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<a class="anchor" id="afbaf941fcb4fa7acd32092835d400f41"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::mapPartitionOptions" ref="afbaf941fcb4fa7acd32092835d400f41" args="()" -->
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<td class="memname"><a class="el" href="structmrpt_1_1slam_1_1_c_incremental_map_partitioner_1_1_t_options.html">CIncrementalMapPartitioner::TOptions</a>* mrpt::slam::CRangeBearingKFSLAM::mapPartitionOptions </td>
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<td><code> [inline]</code></td>
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<p>Provides access to the parameters of the map partitioning algorithm. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00292">292</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="afd5c9c6ce16f81f5639e511bc1e474f8"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnGetAction" ref="afd5c9c6ce16f81f5639e511bc1e474f8" args="(KFArray_ACT &out_u) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnGetAction </td>
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<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_ACT</a> & </td>
<td class="paramname"> <em>out_u</em> )</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#af0571c2b4712bb04d4d84d98629441f2">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="afd569099f5505026e762547e143dc629"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnGetObservationNoise" ref="afd569099f5505026e762547e143dc629" args="(KFMatrix_OxO &out_R) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnGetObservationNoise </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_OxO</a> & </td>
<td class="paramname"> <em>out_R</em> )</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>
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<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a15034c16b93b06e9706d794984ac6a62">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a74f93f0a9a398aee4e51de1689127d11"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnGetObservationsAndDataAssociation" ref="a74f93f0a9a398aee4e51de1689127d11" 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::CRangeBearingKFSLAM::OnGetObservationsAndDataAssociation </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1321c340469c9905fca4a8682afcea4f">vector_KFArray_OBS</a> & </td>
<td class="paramname"> <em>out_z</em>, </td>
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<tr>
<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#a1321c340469c9905fca4a8682afcea4f">vector_KFArray_OBS</a> & </td>
<td class="paramname"> <em>in_all_predictions</em>, </td>
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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html">KFMatrix</a> & </td>
<td class="paramname"> <em>in_S</em>, </td>
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<tr>
<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></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_OxO</a> & </td>
<td class="paramname"> <em>in_R</em> </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#a3baae43b5ad2163c6e1e1f358401b01f">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#a3baae43b5ad2163c6e1e1f358401b01f">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#a3440aba56f5e4042aceff9c51a352641">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a61b31c958f5ef1f119588538818de59c"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnInverseObservationModel" ref="a61b31c958f5ef1f119588538818de59c" 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::CRangeBearingKFSLAM::OnInverseObservationModel </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">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_1math_1_1_c_array_numeric.html">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_1math_1_1_c_matrix_fixed_numeric.html">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_1math_1_1_c_matrix_fixed_numeric.html">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) $" src="form_95.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dxv</td><td>The <img class="formulaInl" alt="$F \times V$" src="form_96.png"/> Jacobian of the inv. sensor model wrt the robot pose <img class="formulaInl" alt="$ \frac{\partial y_n}{\partial x_v} $" src="form_97.png"/>. </td></tr>
<tr><td class="paramname">out_dyn_dhn</td><td>The <img class="formulaInl" alt="$F \times O$" src="form_98.png"/> Jacobian of the inv. sensor model wrt the observation vector <img class="formulaInl" alt="$ \frac{\partial y_n}{\partial h_n} $" src="form_99.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#a1cd2de266f01ca4e14deba7a73762b94">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a21d5fd42e86d10792e530aef75d9baf2"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnNewLandmarkAddedToMap" ref="a21d5fd42e86d10792e530aef75d9baf2" args="(const size_t in_obsIdx, const size_t in_idxNewFeat)" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnNewLandmarkAddedToMap </td>
<td>(</td>
<td class="paramtype">const size_t </td>
<td class="paramname"> <em>in_obsIdx</em>, </td>
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<td></td>
<td class="paramtype">const size_t </td>
<td class="paramname"> <em>in_idxNewFeat</em> </td>
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<td>)</td>
<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_m.html#a61b31c958f5ef1f119588538818de59c" 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#a0b83d09403191f8bb6e9d92394a77f76">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="abcc9fe624ee79796dd0db27b4b29f084"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnNormalizeStateVector" ref="abcc9fe624ee79796dd0db27b4b29f084" args="()" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnNormalizeStateVector </td>
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<td class="paramname"> )</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#a874aaa8d07b3cc46b8a197c78e71c128">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a16b2fccffc944e6e0af70a17b8c234e8"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnObservationJacobians" ref="a16b2fccffc944e6e0af70a17b8c234e8" 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::CRangeBearingKFSLAM::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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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_OxV</a> & </td>
<td class="paramname"> <em>Hx</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">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} $" src="form_93.png"/> and (when applicable) <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial y_i} $" src="form_94.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
<table class="params">
<tr><td class="paramname">idx_landmark_to_predict</td><td>The index of the landmark in the map whose prediction is expected as output. For non SLAM-like problems, this will be zero and the expected output is for the whole state vector. </td></tr>
<tr><td class="paramname">Hx</td><td>The output Jacobian <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial x} $" src="form_93.png"/>. </td></tr>
<tr><td class="paramname">Hy</td><td>The output Jacobian <img class="formulaInl" alt="$ \frac{\partial h_i}{\partial y_i} $" src="form_94.png"/>. </td></tr>
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</dd>
</dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a2a09f65213aec8d6e4f93f414d917bd2">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="ad985328f6b30810aee2da489f505ddb1"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnObservationModel" ref="ad985328f6b30810aee2da489f505ddb1" args="(const vector_size_t &idx_landmarks_to_predict, vector_KFArray_OBS &out_predictions) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnObservationModel </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="namespacemrpt.html#ad4d2b1efd37ed750302c76ebbcfc310d">vector_size_t</a> & </td>
<td class="paramname"> <em>idx_landmarks_to_predict</em>, </td>
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<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1321c340469c9905fca4a8682afcea4f">vector_KFArray_OBS</a> & </td>
<td class="paramname"> <em>out_predictions</em> </td>
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<td>)</td>
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<p>Implements the observation prediction <img class="formulaInl" alt="$ h_i(x) $" src="form_92.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#ab921e280efd7549feefb10368f0dbbea">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="af56a4f99f7f558fb7ac383b5d5c1febc"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnPreComputingPredictions" ref="af56a4f99f7f558fb7ac383b5d5c1febc" 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::CRangeBearingKFSLAM::OnPreComputingPredictions </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a1321c340469c9905fca4a8682afcea4f">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>
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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#a3baae43b5ad2163c6e1e1f358401b01f">getNumberOfLandmarksInTheMap()</a>-1] that should be predicted. </td></tr>
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</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#a00212cd80a7e6794183434f65bf30b41">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a4debf44b3dd2ea88b9f5c37c2d0fd024"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnSubstractObservationVectors" ref="a4debf44b3dd2ea88b9f5c37c2d0fd024" args="(KFArray_OBS &A, const KFArray_OBS &B) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnSubstractObservationVectors </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_OBS</a> & </td>
<td class="paramname"> <em>A</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_OBS</a> & </td>
<td class="paramname"> <em>B</em> </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#a2d3991388ab2becb7439d63dcc048dc5">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="abfa7d23c6a1b88b6877345ec68fac4b9"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnTransitionJacobian" ref="abfa7d23c6a1b88b6877345ec68fac4b9" args="(KFMatrix_VxV &out_F) const " -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::OnTransitionJacobian </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_VxV</a> & </td>
<td class="paramname"> <em>out_F</em> )</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$" src="form_90.png"/> with V being either the size of the whole state vector (for non-SLAM problems) or VEH_SIZE (for SLAM problems). </td></tr>
</table>
</dd>
</dl>
<p>Reimplemented from <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#acdd27ca076677ff3360976040c73a42d">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a068baea8f069e9016c9a1e7336cfdfd1"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnTransitionModel" ref="a068baea8f069e9016c9a1e7336cfdfd1" args="(const KFArray_ACT &in_u, KFArray_VEH &inout_x, bool &out_skipPrediction) const " -->
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<td class="paramname"> <em>in_u</em>, </td>
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<td></td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_array_numeric.html">KFArray_VEH</a> & </td>
<td class="paramname"> <em>inout_x</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">bool & </td>
<td class="paramname"> <em>out_skipPrediction</em> </td>
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<td>)</td>
<td></td><td> const<code> [protected, virtual]</code></td>
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<p>Implements the transition model <img class="formulaInl" alt="$ \hat{x}_{k|k-1} = f( \hat{x}_{k-1|k-1}, u_k ) $" src="form_87.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>
<p class="formulaDsp">
<img class="formulaDsp" alt="\[ \hat{x}_{k-1|k-1} \]" src="form_88.png"/>
</p>
<p> , at output must have <img class="formulaInl" alt="$ \hat{x}_{k|k-1} $" src="form_89.png"/> . </td></tr>
<tr><td class="paramname">out_skip</td><td>Set this to true if for some reason you want to skip the prediction step (to do not modify either the vector or the covariance). Default:false </td></tr>
</table>
</dd>
</dl>
<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a063802c52d3ba8e25f6f86441fd0025c">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<a class="anchor" id="a671e5190f4701458ae0a784c8d65ffa8"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::OnTransitionNoise" ref="a671e5190f4701458ae0a784c8d65ffa8" args="(KFMatrix_VxV &out_Q) const " -->
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<td>(</td>
<td class="paramtype"><a class="el" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html">KFMatrix_VxV</a> & </td>
<td class="paramname"> <em>out_Q</em> )</td>
<td> const<code> [protected, virtual]</code></td>
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<p>Implements the transition noise covariance <img class="formulaInl" alt="$ Q_k $" src="form_91.png"/>. </p>
<dl><dt><b>Parameters:</b></dt><dd>
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<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>
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<p>Implements <a class="el" href="classmrpt_1_1bayes_1_1_c_kalman_filter_capable.html#a262e44ea3d639a66a6fc09234039d8af">mrpt::bayes::CKalmanFilterCapable< VEH_SIZE, OBS_SIZE, FEAT_SIZE, ACT_SIZE, KFTYPE ></a>.</p>
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::processActionObservation </td>
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<td class="paramname"> <em>action</em>, </td>
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<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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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::reconsiderPartitionsNow </td>
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<p>The partitioning of the entire map is recomputed again. </p>
<p>Only when options.doPartitioningExperiment = true. This can be used after changing the parameters of the partitioning method. After this method, you can call getLastPartitionLandmarks. </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_m.html#af51ee48428140f4e9acba5681a1628c9" title="Return the partitioning of the landmarks in clusters accoring to the last partition.">getLastPartitionLandmarks</a> </dd></dl>
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<a class="anchor" id="af9059f0687f3232c0193df0d89109b3b"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::reset" ref="af9059f0687f3232c0193df0d89109b3b" args="()" -->
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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::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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<td class="memname">void mrpt::slam::CRangeBearingKFSLAM::saveMapAndPath2DRepresentationAsMATLABFile </td>
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<td class="paramname"> <em>fil</em>, </td>
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<td class="paramname"> <em>stdCount</em> = <code>3.0f</code>, </td>
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<td class="paramtype">const std::string & </td>
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<td class="paramtype">const std::string & </td>
<td class="paramname"> <em>stylePath</em> = <code>std::string("r")</code>, </td>
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<td class="paramtype">const std::string & </td>
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<td>)</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>Member Data Documentation</h2>
<a class="anchor" id="a325aa177708f2e1203f9a8b1ad060b3e"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::m_action" ref="a325aa177708f2e1203f9a8b1ad060b3e" 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_m.html#a325aa177708f2e1203f9a8b1ad060b3e">mrpt::slam::CRangeBearingKFSLAM::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_m_8h_source.html#l00434">434</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a63ce956a06ecc55a8e8c7de2b59244d8"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::m_IDs" ref="a63ce956a06ecc55a8e8c7de2b59244d8" 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_m.html#a63ce956a06ecc55a8e8c7de2b59244d8">mrpt::slam::CRangeBearingKFSLAM::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_m_8h_source.html#l00442">442</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a129a478e617bb6f5be7ded15fee98a7b"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::m_last_data_association" ref="a129a478e617bb6f5be7ded15fee98a7b" 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_m_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_m.html#a129a478e617bb6f5be7ded15fee98a7b">mrpt::slam::CRangeBearingKFSLAM::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_m_8h_source.html#l00455">455</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a099e1451f9addc6543c737f749deb60a"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::m_lastPartitionSet" ref="a099e1451f9addc6543c737f749deb60a" args="" -->
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<td class="memname">std::vector<<a class="el" href="namespacemrpt.html#aa4dc027dbc3804c847a78892a2982047">vector_uint</a>> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a099e1451f9addc6543c737f749deb60a">mrpt::slam::CRangeBearingKFSLAM::m_lastPartitionSet</a><code> [protected]</code></td>
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<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00453">453</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a9ceb909016d80c7c1f8ea9080eef89cb"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::m_SF" ref="a9ceb909016d80c7c1f8ea9080eef89cb" 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_m.html#a9ceb909016d80c7c1f8ea9080eef89cb">mrpt::slam::CRangeBearingKFSLAM::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_m_8h_source.html#l00438">438</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a7bce6dc04978cb42d426c00c476b9e77"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::m_SFs" ref="a7bce6dc04978cb42d426c00c476b9e77" 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_m.html#a7bce6dc04978cb42d426c00c476b9e77">mrpt::slam::CRangeBearingKFSLAM::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_m_8h_source.html#l00451">451</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a97aa37a9b59183096fe486544b1b4d87"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::mapPartitioner" ref="a97aa37a9b59183096fe486544b1b4d87" args="" -->
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<td class="memname"><a class="el" href="classmrpt_1_1slam_1_1_c_incremental_map_partitioner.html">CIncrementalMapPartitioner</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a97aa37a9b59183096fe486544b1b4d87">mrpt::slam::CRangeBearingKFSLAM::mapPartitioner</a><code> [protected]</code></td>
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<p>Used for map partitioning experiments. </p>
<p>Definition at line <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html#l00447">447</a> of file <a class="el" href="_c_range_bearing_k_f_s_l_a_m_8h_source.html">CRangeBearingKFSLAM.h</a>.</p>
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<a class="anchor" id="a267ffb78c2afd09a7f5b2b81acf31be1"></a><!-- doxytag: member="mrpt::slam::CRangeBearingKFSLAM::options" ref="a267ffb78c2afd09a7f5b2b81acf31be1" 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_m_1_1_t_options.html">mrpt::slam::CRangeBearingKFSLAM::TOptions</a> <a class="el" href="classmrpt_1_1slam_1_1_c_range_bearing_k_f_s_l_a_m.html#a267ffb78c2afd09a7f5b2b81acf31be1">mrpt::slam::CRangeBearingKFSLAM::options</a></td>
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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 1.7.2</a> for MRPT 0.9.4 SVN: at Mon Jan 10 22:30:30 UTC 2011</td><td></td> <td width="100"> </td> <td width="150"> </td></tr> </table> </body></html>
