(I need help with these problems; an explanation would be appreciated. In Python, please, thank you.)

Perseverance is able to perform some science thanks to you. It now spots a sector that has obstacles represented by 1s. Keeping the assumptions same as Q3, return the length of the shortest path avoiding obstacles. Return -1 if no such path exists.

Hints:

Dont explore neighboring cells that dont exist (are beyond the grids boundary)

Dont explore neighboring cells that are obstacles.

Dont revisit a cell.

Your search ends when there is nothing to explore.

You will have to propagate the information of the explored length so far.

Here are some examples.

grid = [[0,0,0],

[1,1,0],

[1,1,0]]

start, goal = (1,2), (0,0)

Solution = 4

grid = [[0,1],

[1,0]]

start, goal = (0, 0), (1,1)

Solution = -1 ---> Perseverance cant travel diagonally and thus there doesnt exist any feasible path.

####CODE

def shortest_path_grid(grid, start, goal):

'''

Function that returns the length of the shortest path in a grid

that HAS obstacles represented by 1s. The length is simply the number

of cells on the path including the 'start' and the 'goal'

:param grid: list of lists (represents a square grid where 0 represents free space and 1s obstacles)

:param start: tuple of start index

:param goal: tuple of goal index

:return: length of path

'''

n = len(grid)

if __name__ == "__main__":

grid = [[0,0,0],

[1,1,0],

[1,1,0]]

start, goal = (1,2), (0,0)

print(shortest_path_grid(grid, start, goal))

assert shortest_path_grid(grid, start, goal) == 4

grid = [[0,1],

[1,0]]

start, goal = (0, 0), (1,1)

print(shortest_path_grid(grid, start, goal))

assert shortest_path_grid(grid, start, goal) == -1