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The main challenge in motion planning is when a robot exists within a particular enviromment. The robot beeds to plan a stratepy to reach its

The main challenge in motion planning is when a robot exists within a particular enviromment. The robot beeds to plan a stratepy to reach its destination, starting: from point S and reaching point G, as illustrated in the following figure.
\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 perform four possible actions, eg. Mowe-Up, Move-Down, Move-left, and Move Right. The agent can move to white cells, while black cells act as obstacles and cannot be triversed. 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 ageat 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) detooted as g((1,1)) which is 2.
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