docs on ro-slam

doc/source/range_only_localization_mapping.rst

@@ -6,7 +6,8 @@ Range-only Localization and Mapping Solutions
 
 .. contents:: :local:
 
-Range-only SLAM
+
+1. Range-only SLAM
 ====================
 
 MRPT at present offers one SLAM solution for RO-SLAM, integrated into the
@@ -17,7 +18,10 @@ Users can employ 2D or 3D poses in RBPF-SLAM, but notice that RO-SLAM with a RBP
 requires a decent odometry as input, which can comprise 2D or 3D robot motion
 actions.
 
-Range-only Localization
+.. image:: images/demo_ROSLAM_symmetry1.jpg
+   :alt: Range-Only SLAM with symmetry example
+
+2. Range-only Localization
 ==========================
 
 There are two implementations:
@@ -26,23 +30,30 @@ pf-localization
 ---------------------
 
 The `pf-localization application <https://www.mrpt.org/list-of-mrpt-apps/application-pf-localization/>`_
-is a CLI to the underlying C++ class from the library: \ref mrpt_apps_grp.
+is a CLI to the underlying C++ class from the library `mrpt::apps <group_mrpt_apps_grp.html>`_.
 
 Users can employ 2D or 3D odometry as input for 2D or 3D motion estimation. If
 no odometry is available, using a no-motion mean value with a large uncertainty
 should work.
 
 The CLI application works with offline data only, for online use, please refer
-to the underlying class in \ref mrpt_apps_grp or use the even most low-level classes:
-- mrpt::slam::CMonteCarloLocalization2D: For robots moving in 2D; pose=(x,y,phi)
-- mrpt::slam::CMonteCarloLocalization3D: For robots moving in 3D space; pose=(x,y,z,yaw,pitch,roll)
+to the underlying class in `mrpt::apps <group_mrpt_apps_grp.html>`_ 
+or use the even most low-level classes:
+
+- `mrpt::slam::CMonteCarloLocalization2D <class_mrpt_slam_CMonteCarloLocalization2D.html>`_: For robots
+  moving in 2D, with SE(2) poses (x,y,phi)
+
+- `mrpt::slam::CMonteCarloLocalization3D <class_mrpt_slam_CMonteCarloLocalization3D.html>`_: For robots
+  moving in 3D space, with SE(3) poses (x,y,z,yaw,pitch,roll)
 
 ro-localization
 ---------------------
 
 The `ro-localization application <https://www.mrpt.org/list-of-mrpt-apps/application-ro-localization/>`_
 is exactly like pf-localization above, but with two differences:
+
 - It's available for 2D only (at present).
+
 - It defines an extended state vector (at each particle) with an estimate of the current bias of each beacon/anchor.
 
 If your sensors do NOT suffer of bias with often, abrupt large changes, the regular