Add base doc files

docs/Makefile

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+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line.
+SPHINXOPTS    =
+SPHINXBUILD   = sphinx-build
+SPHINXPROJ    = PythonRobotics
+SOURCEDIR     = .
+BUILDDIR      = _build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/README.md

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+## Python Robotics Documentation
+
+This folder contains documentation for the Python Robotics project.
+
+
+### Build the Documentation
+
+#### Install Sphinx and Theme
+
+```
+pip install sphinx sphinx-autobuild sphinx-rtd-theme
+```
+
+#### Building the Docs
+
+In the `docs/` folder:
+```
+make html
+```
+
+if you want to building each time a file is changed:
+
+```
+sphinx-autobuild . _build/html
+```

docs/conf.py

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+# -*- coding: utf-8 -*-
+#
+# Configuration file for the Sphinx documentation builder.
+#
+# This file does only contain a selection of the most common options. For a
+# full list see the documentation:
+# http://www.sphinx-doc.org/en/master/config
+
+# -- Path setup --------------------------------------------------------------
+
+# If extensions (or modules to document with autodoc) are in another directory,
+# add these directories to sys.path here. If the directory is relative to the
+# documentation root, use os.path.abspath to make it absolute, like shown here.
+#
+import os
+# import sys
+# sys.path.insert(0, os.path.abspath('.'))
+
+
+# -- Project information -----------------------------------------------------
+
+project = 'PythonRobotics'
+copyright = '2018, Atsushi Sakai'
+author = 'Atsushi Sakai'
+
+# The short X.Y version
+version = ''
+# The full version, including alpha/beta/rc tags
+release = ''
+
+
+# -- General configuration ---------------------------------------------------
+
+# If your documentation needs a minimal Sphinx version, state it here.
+#
+# needs_sphinx = '1.0'
+
+# Add any Sphinx extension module names here, as strings. They can be
+# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
+# ones.
+extensions = [
+    'sphinx.ext.autodoc',
+    'sphinx.ext.mathjax',
+    'sphinx.ext.viewcode',
+]
+
+# Add any paths that contain templates here, relative to this directory.
+templates_path = ['_templates']
+
+# The suffix(es) of source filenames.
+# You can specify multiple suffix as a list of string:
+#
+# source_suffix = ['.rst', '.md']
+source_suffix = '.rst'
+
+# The master toctree document.
+master_doc = 'index'
+
+# The language for content autogenerated by Sphinx. Refer to documentation
+# for a list of supported languages.
+#
+# This is also used if you do content translation via gettext catalogs.
+# Usually you set "language" from the command line for these cases.
+language = None
+
+# List of patterns, relative to source directory, that match files and
+# directories to ignore when looking for source files.
+# This pattern also affects html_static_path and html_extra_path .
+exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+
+# The name of the Pygments (syntax highlighting) style to use.
+pygments_style = 'sphinx'
+
+
+# -- Options for HTML output -------------------------------------------------
+
+# The theme to use for HTML and HTML Help pages.  See the documentation for
+# a list of builtin themes.
+#
+# Fix for read the docs
+on_rtd = os.environ.get('READTHEDOCS') == 'True'
+if on_rtd:
+    html_theme = 'default'
+else:
+    html_theme = 'sphinx_rtd_theme'
+
+# Theme options are theme-specific and customize the look and feel of a theme
+# further.  For a list of options available for each theme, see the
+# documentation.
+#
+html_logo = '../icon.png'
+html_theme_options = {
+    'display_version': False,
+}
+
+# Add any paths that contain custom static files (such as style sheets) here,
+# relative to this directory. They are copied after the builtin static files,
+# so a file named "default.css" will overwrite the builtin "default.css".
+html_static_path = ['_static']
+
+# Custom sidebar templates, must be a dictionary that maps document names
+# to template names.
+#
+# The default sidebars (for documents that don't match any pattern) are
+# defined by theme itself.  Builtin themes are using these templates by
+# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
+# 'searchbox.html']``.
+#
+# html_sidebars = {}
+
+
+# -- Options for HTMLHelp output ---------------------------------------------
+
+# Output file base name for HTML help builder.
+htmlhelp_basename = 'PythonRoboticsdoc'
+
+
+# -- Options for LaTeX output ------------------------------------------------
+
+latex_elements = {
+    # The paper size ('letterpaper' or 'a4paper').
+    #
+    # 'papersize': 'letterpaper',
+
+    # The font size ('10pt', '11pt' or '12pt').
+    #
+    # 'pointsize': '10pt',
+
+    # Additional stuff for the LaTeX preamble.
+    #
+    # 'preamble': '',
+
+    # Latex figure (float) alignment
+    #
+    # 'figure_align': 'htbp',
+}
+
+# Grouping the document tree into LaTeX files. List of tuples
+# (source start file, target name, title,
+#  author, documentclass [howto, manual, or own class]).
+latex_documents = [
+    (master_doc, 'PythonRobotics.tex', 'PythonRobotics Documentation',
+     'Atsushi Sakai', 'manual'),
+]
+
+
+# -- Options for manual page output ------------------------------------------
+
+# One entry per manual page. List of tuples
+# (source start file, name, description, authors, manual section).
+man_pages = [
+    (master_doc, 'pythonrobotics', 'PythonRobotics Documentation',
+     [author], 1)
+]
+
+
+# -- Options for Texinfo output ----------------------------------------------
+
+# Grouping the document tree into Texinfo files. List of tuples
+# (source start file, target name, title, author,
+#  dir menu entry, description, category)
+texinfo_documents = [
+    (master_doc, 'PythonRobotics', 'PythonRobotics Documentation',
+     author, 'PythonRobotics', 'One line description of project.',
+     'Miscellaneous'),
+]
+
+
+# -- Extension configuration -------------------------------------------------

docs/getting_started.rst

@@ -0,0 +1,29 @@
+.. _getting_started:
+
+Getting Started
+===============
+
+Requirements
+-------------
+
+-  Python 3.6.x
+-  numpy
+-  scipy
+-  matplotlib
+-  pandas
+-  `cvxpy`_
+
+.. _cvxpy: http://www.cvxpy.org/en/latest/
+
+
+How to use
+----------
+
+1. Install the required libraries. You can use environment.yml with
+   conda command.
+
+2. Clone this repo.
+
+3. Execute python script in each directory.
+
+4. Add star to this repo if you like it 😃.

docs/index.rst

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+.. PythonRobotics documentation master file, created by
+   sphinx-quickstart on Sat Sep 15 13:15:55 2018.
+   You can adapt this file completely to your liking, but it should at least
+   contain the root `toctree` directive.
+
+Welcome to PythonRobotics's documentation!
+==========================================
+
+Python codes for robotics algorithm.
+
+This is a Python code collection of robotics algorithms, especially for autonomous navigation.
+
+Features:
+
+1. Easy to read for understanding each algorithm's basic idea.
+
+2. Widely used and practical algorithms are selected.
+
+3. Minimum dependency.
+
+See this paper for more details:
+
+-  `[1808.10703] PythonRobotics: a Python code collection of robotics
+   algorithms`_ (`BibTeX`_)
+
+.. _`[1808.10703] PythonRobotics: a Python code collection of robotics algorithms`: https://arxiv.org/abs/1808.10703
+.. _BibTeX: https://github.com/AtsushiSakai/PythonRoboticsPaper/blob/master/python_robotics.bib
+
+
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Guide
+
+   getting_started
+   modules/localization
+   modules/mapping
+   modules/slam
+
+
+
+Indices and tables
+==================
+
+* :ref:`genindex`
+* :ref:`modindex`
+* :ref:`search`

docs/make.bat

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+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=.
+set BUILDDIR=_build
+set SPHINXPROJ=PythonRobotics
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.http://sphinx-doc.org/
+	exit /b 1
+)
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
+
+:end
+popd

docs/modules/localization.rst

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+.. _localization:
+
+Localization
+============
+
+Extended Kalman Filter localization
+-----------------------------------
+
+.. raw:: html
+
+   <img src="https://github.com/AtsushiSakai/PythonRobotics/raw/master/Localization/extended_kalman_filter/animation.gif" width="640">
+
+This is a sensor fusion localization with Extended Kalman Filter(EKF).
+
+The blue line is true trajectory, the black line is dead reckoning
+trajectory,
+
+the green point is positioning observation (ex. GPS), and the red line
+is estimated trajectory with EKF.
+
+The red ellipse is estimated covariance ellipse with EKF.
+
+Ref:
+
+-  `PROBABILISTIC ROBOTICS`_
+
+Unscented Kalman Filter localization
+------------------------------------
+
+|2|
+
+This is a sensor fusion localization with Unscented Kalman Filter(UKF).
+
+The lines and points are same meaning of the EKF simulation.
+
+Ref:
+
+-  `Discriminatively Trained Unscented Kalman Filter for Mobile Robot
+   Localization`_
+
+Particle filter localization
+----------------------------
+
+|3|
+
+This is a sensor fusion localization with Particle Filter(PF).
+
+The blue line is true trajectory, the black line is dead reckoning
+trajectory,
+
+and the red line is estimated trajectory with PF.
+
+It is assumed that the robot can measure a distance from landmarks
+(RFID).
+
+This measurements are used for PF localization.
+
+Ref:
+
+-  `PROBABILISTIC ROBOTICS`_
+
+Histogram filter localization
+-----------------------------
+
+|4|
+
+This is a 2D localization example with Histogram filter.
+
+The red cross is true position, black points are RFID positions.
+
+The blue grid shows a position probability of histogram filter.
+
+In this simulation, x,y are unknown, yaw is known.
+
+The filter integrates speed input and range observations from RFID for
+localization.
+
+Initial position is not needed.
+
+Ref:
+
+-  `PROBABILISTIC ROBOTICS`_
+
+.. _PROBABILISTIC ROBOTICS: http://www.probabilistic-robotics.org/
+.. _Discriminatively Trained Unscented Kalman Filter for Mobile Robot Localization: https://www.researchgate.net/publication/267963417_Discriminatively_Trained_Unscented_Kalman_Filter_for_Mobile_Robot_Localization
+
+.. |2| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Localization/unscented_kalman_filter/animation.gif
+.. |3| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Localization/particle_filter/animation.gif
+.. |4| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Localization/histogram_filter/animation.gif

docs/modules/mapping.rst

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+.. _mapping:
+
+Mapping
+=======
+
+Gaussian grid map
+-----------------
+
+This is a 2D Gaussian grid mapping example.
+
+|2|
+
+Ray casting grid map
+--------------------
+
+This is a 2D ray casting grid mapping example.
+
+|3|
+
+k-means object clustering
+-------------------------
+
+This is a 2D object clustering with k-means algorithm.
+
+|4|
+
+Object shape recognition using circle fitting
+---------------------------------------------
+
+This is an object shape recognition using circle fitting.
+
+|5|
+
+The blue circle is the true object shape.
+
+The red crosses are observations from a ranging sensor.
+
+The red circle is the estimated object shape using circle fitting.
+
+.. |2| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Mapping/gaussian_grid_map/animation.gif
+.. |3| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Mapping/raycasting_grid_map/animation.gif
+.. |4| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Mapping/kmeans_clustering/animation.gif
+.. |5| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/Mapping/circle_fitting/animation.gif

docs/modules/slam.rst

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+.. _slam:
+
+SLAM
+====
+
+Simultaneous Localization and Mapping(SLAM) examples
+
+.. _iterative-closest-point-(icp)-matching:
+
+Iterative Closest Point (ICP) Matching
+--------------------------------------
+
+This is a 2D ICP matching example with singular value decomposition.
+
+It can calculate a rotation matrix and a translation vector between
+points to points.
+
+|3|
+
+Ref:
+
+-  `Introduction to Mobile Robotics: Iterative Closest Point Algorithm`_
+
+EKF SLAM
+--------
+
+This is an Extended Kalman Filter based SLAM example.
+
+The blue line is ground truth, the black line is dead reckoning, the red
+line is the estimated trajectory with EKF SLAM.
+
+The green crosses are estimated landmarks.
+
+|4|
+
+Ref:
+
+-  `PROBABILISTIC ROBOTICS`_
+
+FastSLAM 1.0
+------------
+
+This is a feature based SLAM example using FastSLAM 1.0.
+
+The blue line is ground truth, the black line is dead reckoning, the red
+line is the estimated trajectory with FastSLAM.
+
+The red points are particles of FastSLAM.
+
+Black points are landmarks, blue crosses are estimated landmark
+positions by FastSLAM.
+
+|5|
+
+Ref:
+
+-  `PROBABILISTIC ROBOTICS`_
+
+-  `SLAM simulations by Tim Bailey`_
+
+FastSLAM 2.0
+------------
+
+This is a feature based SLAM example using FastSLAM 2.0.
+
+The animation has the same meanings as one of FastSLAM 1.0.
+
+|6|
+
+Ref:
+
+-  `PROBABILISTIC ROBOTICS`_
+
+-  `SLAM simulations by Tim Bailey`_
+
+Graph based SLAM
+----------------
+
+This is a graph based SLAM example.
+
+The blue line is ground truth.
+
+The black line is dead reckoning.
+
+The red line is the estimated trajectory with Graph based SLAM.
+
+The black stars are landmarks for graph edge generation.
+
+|7|
+
+Ref:
+
+-  `A Tutorial on Graph-Based SLAM`_
+
+.. _`Introduction to Mobile Robotics: Iterative Closest Point Algorithm`: https://cs.gmu.edu/~kosecka/cs685/cs685-icp.pdf
+.. _PROBABILISTIC ROBOTICS: http://www.probabilistic-robotics.org/
+.. _SLAM simulations by Tim Bailey: http://www-personal.acfr.usyd.edu.au/tbailey/software/slam_simulations.htm
+.. _A Tutorial on Graph-Based SLAM: http://www2.informatik.uni-freiburg.de/~stachnis/pdf/grisetti10titsmag.pdf
+
+.. |3| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/SLAM/iterative_closest_point/animation.gif
+.. |4| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/SLAM/EKFSLAM/animation.gif
+.. |5| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/SLAM/FastSLAM1/animation.gif
+.. |6| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/SLAM/FastSLAM2/animation.gif
+.. |7| image:: https://github.com/AtsushiSakai/PythonRobotics/raw/master/SLAM/GraphBasedSLAM/animation.gif