The main challenge in motion planning is when a robot exists within a particular environment. The robot needs to plan a strategy to reach its destination, starting, from point $S$ and reaching point $G,$ as illustrated in the following figure.

$\backslash$table$[[,0,1,2,3,4,5],[0,5,,,,,],[1,,,,,,],[2,,,,,,],[3,,,,,,],[4,,,,,,]]$

The start state in this problem can be represented as $(0,0)$ and the goal state is represented as $(4,5).$ The agent can perforn four possible actions, eg$.$ Mave$-$Up$,$ Move$-$Down, Move$-$Left, and Move Right. The agent can move to white cells, while black cells act as obstacles and cannot be traversed. For example, the agent from the start state $(0,0)$ can perform Move$-$Right or Move$-$Down actions to get into $(0,1)$ or $(1,0)$ states, respectively. The cost of each action is $1,$ representing the actual cost $"g"$ to go from one state to another state For instance, as the agest moves from state $(0,0)$ to $0,1$ with a cost of $1,$ and then from $(0,1)$ to $(1,1)$ with an additional cost of $1,$ the total cost from the start state $[0,0)$ to $(1,1)$ denoted as $g((1,1])$ which is $2.$