[AMR] Many learnings from exercises

electives/amr/parts/05_planning-control/01_motion-planning-exploration/01_a-star-algorithm.tex

@@ -3,6 +3,7 @@ Function \texttt{h(\dots)} is a lower bound of optimal cost.
 % TODO: If space constrained, move to below
 % Init vert. with \texttt{dist}, \texttt{totDistEst} to $\8$, \texttt{prev} \texttt{undef}, \texttt{start}
 \begin{algorithm}
+    \small
     \begin{algorithmic}[1]
         \Procedure{Astar}{\texttt{Graph, start, goal}}
             \For{each \texttt{v} in \texttt{Graph.Verticies}}

electives/amr/parts/05_planning-control/01_motion-planning-exploration/02_rrt.tex

@@ -1,5 +1,7 @@
+\newpage
 \subsubsection{Rapidly-Exploring Random Tree (RRT)}
 \begin{algorithm}
+    \small
     \begin{algorithmic}[1]
         \Procedure{RRT}{\texttt{start, goal}}
             \State \Call{insertVertex}{\texttt{start, Graph}}
@@ -28,6 +30,7 @@
 Returns a collision-free path as graph. Need nearest neighbour search.
 Extension to RRT* to make path better:
 \begin{algorithm}
+    \small
     \begin{algorithmic}[1]
         \State $X_{\text{near}} \gets$ \Call{neighbours}{Graph, $x_f$, $R$}
         \State $x_{\min} \gets$ \Call{neighbours}{Graph, $x_f$, $R$}