1. Using Python, create a script to find the shortest path from point S (start) to point G (goal) through a discretized workspace (6 rows by 12 columns) such as this ("." designates a cell of free space, "X" represents a cell fully occupied by an obstacle). Use 4-connectivity (research the subject of connectivity, e.g., here): X X X X X X X X X X X X 2. Find a way to visualize the calculated path, including the path length, with the final state of the wave expansion. 3. Change to 8-connectivity, recalculate, visualize, and interpret the results. 4. Modify the code so that the coordinates of "S" and "G" are randomly generated (obviously, the locations of those cannot be in the obstacle area). Run this simulation in a loop. At the end of each simulation, display the path. For the sake of the exercise, repeat the loop just three times. Either connectivity (4 or 8) is acceptable. For simplicity, you can restrict randomly generated "S"s to the left half and "G"s to the right half.