input: Write a function to find the most efficient path for a robot to take from its current location to the destination. The function should return a list of positions representing the path from the start to the end, or None if no path is found. If the given start and end are the same, the function should return a list with just the start position.
  
  def find_path(start, end):
      if start == end:
          return [start]
      x = start[0]
      y = start[1] 
      goal_x = end[0] 
      goal_y = end[1] 
      visited = set() 
      queue = [([x, y], [])] 
      neighbor = [[1, 0], [0, 1], [-1, 0], [0, -1]] 
      max_tries = 100 
      while queue:
          position, path = queue.pop(0) 
          if position[0] == goal_x and position[1] == goal_y:
              return path + [position]
          if tuple(position) not in visited and max_tries > 0:
              visited.add(tuple(position))
              max_tries = max_tries - 1 
              for neighbor_x, neighbor_y in neighbor:
                  next_x = position[0] + neighbor_x
                  next_y = position[1] + neighbor_y
                  queue.append(([next_x, next_y], path + [position]))
      return None
  
  assert find_path((4, 2), (9, 9)) == [(4, 2), (5, 2), (6, 2), (7, 2), (8, 2), (9, 2), (9, 3), (9, 4), (9, 5), (9, 6), (9, 7), (9, 8), (9, 9)]
  assert find_path((2, 2), (2, 2)) == [(2, 2)]
  assert find_path((0, 0), (3, 3)) == [(0, 0), (1, 0), (2, 0), (3, 0), (3, 1), (3, 2), (3, 3)]
  assert find_path((5, 5), (6, 6)) == [(5, 5), (6, 5), (6, 6)]
  assert find_path((1, 1), (10, 10)) == None
output: def find_path(start, end):
      if start == end:
          return [start]
      x = start[0]
      y = start[1] 
      goal_x = end[0] 
      goal_y = end[1] 
      visited = set() 
      queue = [([x, y], [])] 
      neighbor = [[1, 0], [0, 1], [-1, 0], [0, -1]] 
      max_tries = 100 
      while queue:
          position, path = queue.pop(0) 
          if position[0] == goal_x and position[1] == goal_y:
              return path + [position]
          if tuple(position) not in visited and max_tries > 0:
              visited.add(tuple(position))
              max_tries = max_tries - 1 
              for neighbor_x, neighbor_y in neighbor:
                  next_x = position[0] + neighbor_x
                  next_y = position[1] + neighbor_y
                  queue.append(([next_x, next_y], path + [position]))
      return None