input: Write a function to find the most efficient path for a robot to take from its current location to the destination using a breadth-first search algorithm. The function should return a list of positions representing the path from the start to the end, or None if no path is found within a maximum number of tries.
  
  def find_path(start, end):
      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 position not in visited and max_tries > 0:
              visited.add(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((0, 0), (2, 2)) == [(0, 0), (1, 0), (2, 0), (2, 1), (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((1, 1), (1, 1)) == [(1, 1)]
  assert find_path((0, 0), (4, 4)) == None
output: def find_path(start, end):
      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