diff --git a/doc/rcfs.pdf b/doc/rcfs.pdf
index 504320302976aca92562959b4982e70dd28cc079..0103c220c8070f0a22935d03adf128895f82f1b7 100644
Binary files a/doc/rcfs.pdf and b/doc/rcfs.pdf differ
diff --git a/doc/rcfs.tex b/doc/rcfs.tex
index 079368484aa266b851212a2145757ca5db1bc3ce..a87f986420d75ca537f188fc9424c2473310e7f9 100644
--- a/doc/rcfs.tex
+++ b/doc/rcfs.tex
@@ -70,8 +70,6 @@
 \newcommand{\tmax}{{\scriptscriptstyle\max}}
 %\newcommand{\filename}[1]{{\raggedleft\colorbox{rr2}{{\color{white}\texttt{#1}}}\\[2mm]}}
 \newcommand{\filename}[1]{\colorbox{rr2}{\color{white}\texttt{#1}}}
-%\newcommand{\filename}[1]{\texttt{#1}}
-
 
 %\usepackage{hyperref}
 %\hypersetup{
@@ -107,7 +105,7 @@
 
 This technical report presents several learning and optimal control techniques in robotics in the form of simple toy problems that can be easily coded. It comes with a set of standalone examples gathered as a git repository \textbf{Robotics Codes From Scratch (RCFS)}, accessed at:
 \begin{center}
-\texttt{https://gitlab.idiap.ch/rli/robotics-codes-from-scratch}
+\url{https://gitlab.idiap.ch/rli/robotics-codes-from-scratch}
 \end{center}%\\
 
 Each section in this report lists the corresponding source codes in Python and Matlab (ensuring full compatibility with GNU Octave), as well as in C++ and Julia for some of the principal examples. 
@@ -1794,7 +1792,7 @@ see also Fig.~\ref{fig:iLQR_manipulator}.
 Reaching task with a humanoid (side view) by keeping the center of mass in an area defined by the feet location. 
 }
 \label{fig:iLQR_CoM}
-%\vspace{-20pt}
+\vspace{-20pt}
 \end{wrapfigure}
 
 If we assume an equal mass for each link concentrated at the joint (i.e., assuming that the motors and gripper are heavier than the link structures), the forward kinematics function to determine the center of a mass of an articulated chain can simply be computed with
@@ -1908,7 +1906,7 @@ with the corresponding Jacobian matrix $\bm{J}^\tp{CoM}\in\mathbb{R}^{2\times 5}
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\subsubsection{Ellipsoidal obstacle avoidance} %(1-e'*e)'*(1-e'*e) version
+\subsubsection{Obstacle avoidance with ellipsoid shapes} %(1-e'*e)'*(1-e'*e) version, where 1-e'*e is a scalar
 \begin{flushright}
 \filename{iLQR\_obstacle.*}
 \end{flushright}
@@ -1927,7 +1925,7 @@ with the corresponding Jacobian matrix $\bm{J}^\tp{CoM}\in\mathbb{R}^{2\times 5}
 \centering
 \includegraphics[width=.30\textwidth]{images/iLQR_ellipsoidObstacle01.png}
 \caption{\footnotesize
-Reaching task with obstacle avoidance.
+Reaching task with obstacle avoidance, by starting from $\bm{x}_1$ and reaching $\bm{\mu}_T$ while avoiding the two obstacles in red.
 }
 \label{fig:iLQR_obstacle}
 \vspace{-80pt}