diff --git a/electives/amr/autonomous-mobile-robots-cheatsheet.pdf b/electives/amr/autonomous-mobile-robots-cheatsheet.pdf
index a783087..4cf0710 100644
Binary files a/electives/amr/autonomous-mobile-robots-cheatsheet.pdf and b/electives/amr/autonomous-mobile-robots-cheatsheet.pdf differ
diff --git a/electives/amr/parts/04_vision/03_mapping.tex b/electives/amr/parts/04_vision/03_mapping.tex
index 7fe3969..33d6931 100644
--- a/electives/amr/parts/04_vision/03_mapping.tex
+++ b/electives/amr/parts/04_vision/03_mapping.tex
@@ -33,7 +33,7 @@ $\displaystyle s_k = \frac{w_{k - 1} s_{k - 1} + \tilde{s}_k}{w_{k - 1} + 1}$ wi
 \bi{Implementation} Using Hash maps or octree (dense grid inefficient)
 
 
-\subsubsection{Iterative Closest Point}
+\subsubsection{Iterative Closest Point (ICP)}
 Build \textit{correspondences}: associate all live scan points $l_i$ to closest map points $m_i$. Error term:
 $\vec{e} = \vec{T}_{W L_l} {_{L_l}}m_i - {_W}\vec{l}_i$.
 Minimize this via Gauss-Newton, then re-associate, iterate.