Re-architecture document structure (#669)

* Rearchitecture document structure

* Rearchitecture document structure

* Rearchitecture document structure

* Rearchitecture document structure

* Rearchitecture document structure

* Rearchitecture document structure

* Rearchitecture document structure

docs/modules/slam/graph_slam/graphSLAM_SE2_example.rst

@@ -44,7 +44,7 @@ The Dataset
 
 
 
-.. image:: graph_slam/graphSLAM_SE2_example_files/graphSLAM_SE2_example_4_0.png
+.. image:: graphSLAM_SE2_example_files/graphSLAM_SE2_example_4_0.png
 
 
 Each edge in this dataset is a constraint that compares the measured
@@ -122,7 +122,7 @@ dataset and plot them.
 
 
 
-.. image:: graph_slam/graphSLAM_SE2_example_files/graphSLAM_SE2_example_8_0.png
+.. image:: graphSLAM_SE2_example_files/graphSLAM_SE2_example_8_0.png
 
 
 .. code:: ipython3
@@ -131,7 +131,7 @@ dataset and plot them.
 
 
 
-.. image:: graph_slam/graphSLAM_SE2_example_files/graphSLAM_SE2_example_9_0.png
+.. image:: graphSLAM_SE2_example_files/graphSLAM_SE2_example_9_0.png
 
 
 Optimization
@@ -165,7 +165,7 @@ different data sources into a single optimization problem.
             6             215.8405          -0.000000
 
 
-.. figure:: graph_slam/graphSLAM_SE2_example_files/Graph_SLAM_optimization.gif
+.. figure:: graphSLAM_SE2_example_files/Graph_SLAM_optimization.gif
 
 .. code:: ipython3
 
@@ -173,7 +173,7 @@ different data sources into a single optimization problem.
 
 
 
-.. image:: graph_slam/graphSLAM_SE2_example_files/graphSLAM_SE2_example_13_0.png
+.. image:: graphSLAM_SE2_example_files/graphSLAM_SE2_example_13_0.png
 
 
 .. code:: ipython3
@@ -195,7 +195,7 @@ different data sources into a single optimization problem.
 
 
 
-.. image:: graph_slam/graphSLAM_SE2_example_files/graphSLAM_SE2_example_15_0.png
+.. image:: graphSLAM_SE2_example_files/graphSLAM_SE2_example_15_0.png
 
 
 .. code:: ipython3
@@ -204,5 +204,5 @@ different data sources into a single optimization problem.
 
 
 
-.. image:: graph_slam/graphSLAM_SE2_example_files/graphSLAM_SE2_example_16_0.png
+.. image:: graphSLAM_SE2_example_files/graphSLAM_SE2_example_16_0.png
 

docs/modules/slam/graph_slam/graphSLAM_doc.rst

@@ -142,7 +142,7 @@ created based on the information of the motion and the observation.
 
 
 
-.. image:: graph_slam/graphSLAM_doc_files/graphSLAM_doc_2_0.png
+.. image:: graphSLAM_doc_files/graphSLAM_doc_2_0.png
 
 
 .. parsed-literal::
@@ -157,7 +157,7 @@ created based on the information of the motion and the observation.
 
 
 
-.. image:: graph_slam/graphSLAM_doc_files/graphSLAM_doc_2_2.png
+.. image:: graphSLAM_doc_files/graphSLAM_doc_2_2.png
 
 
 In particular, the tasks are split into 2 parts, graph construction, and
@@ -289,7 +289,7 @@ robot with 3DoF, namely, :math:`[x, y, \theta]^T`
 
 
 
-.. image:: graph_slam/graphSLAM_doc_files/graphSLAM_doc_4_0.png
+.. image:: graphSLAM_doc_files/graphSLAM_doc_4_0.png
 
 
 .. code:: ipython3
@@ -420,7 +420,7 @@ zero since :math:`x_j + d_j cos(\psi_j + \theta_j)` should equal
 
 
 
-.. image:: graph_slam/graphSLAM_doc_files/graphSLAM_doc_9_1.png
+.. image:: graphSLAM_doc_files/graphSLAM_doc_9_1.png
 
 
 Since the constraints equations derived before are non-linear,
@@ -494,9 +494,9 @@ Similarly, :math:`B = \frac{\partial e_{ij}}{\partial \boldsymbol{x}_j}`
 
 
 
-.. image:: graph_slam/graphSLAM_doc_files/graphSLAM_doc_11_1.png
+.. image:: graphSLAM_doc_files/graphSLAM_doc_11_1.png
 
-.. image:: graph_slam/graphSLAM_doc_files/graphSLAM_doc_11_2.png
+.. image:: graphSLAM_doc_files/graphSLAM_doc_11_2.png
 
 .. code:: ipython3
 

docs/modules/slam/graph_slam/graphSLAM_formulation.rst

@@ -70,7 +70,7 @@ Using Bayes’ rule, we can write this probability as
 
 since :math:`p(\mathcal{Z})` is a constant (albeit, an unknown constant)
 and we assume that :math:`p(\mathbf{p}_1, \ldots, \mathbf{p}_N)` is
-uniformly distributed `PROBABILISTIC ROBOTICS`_. Therefore, we
+uniformly distributed. Therefore, we
 can use Eq. :eq:`infomat` and and Eq. :eq:`bayes` to simplify the Graph SLAM
 optimization as follows:
 

docs/modules/slam/graph_slam/graph_slam_main.rst

@@ -13,9 +13,9 @@ The black stars are landmarks for graph edge generation.
 
 .. image:: https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/SLAM/GraphBasedSLAM/animation.gif
 
-.. include:: graph_slam/graphSLAM_doc.rst
-.. include:: graph_slam/graphSLAM_formulation.rst
-.. include:: graph_slam/graphSLAM_SE2_example.rst
+.. include:: graphSLAM_doc.rst
+.. include:: graphSLAM_formulation.rst
+.. include:: graphSLAM_SE2_example.rst
 
 References:
 ~~~~~~~~~~~