请写一段用openmv和Dstar算法对数组迷宫进行路径规划1为墙壁，0为道路，2为起点与重点要求输出的路径用3表示数组如下Mi[21][21] = {(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1), (1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,2,1), (1,0,1,0,1,1,1,0,1,0,1,0,1,1,1,0,1,0,1,1,1), (1,0,1,0,1,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1), (1,0,1,1,1,0,1,1,1,0,1,1,1,0,1,0,1,1,1,0,1), (1,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1), (1,1,1,0,1,0,1,0,1,1,1,1,1,0,1,1,1,0,1,1,1), (1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1), (1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1), (1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1), (1,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,0,1), (1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,1), (1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1), (1,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1), (1,1,1,0,1,1,1,0,1,1,1,1,1,0,1,0,1,0,1,1,1), (1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1), (1,0,1,1,1,0,1,0,1,1,1,0,1,1,1,0,1,1,1,0,1), (1,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1), (1,1,1,0,1,0,1,1,1,0,1,0,1,0,1,1,1,0,1,0,1), (1,2,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1), (1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1)}

请注意，由于我是一个文本AI模型，我无法直接操作OpenMV或编写代码。然而，我可以为您提供一个基于OpenMV和D*算法的路径规划示例代码，您可以将其运行在OpenMV上。

# 导入所需库
import sensor
import image
import time

# 定义迷宫数组
maze = [[1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1],
        [1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,2,1],
        [1,0,1,0,1,1,1,0,1,0,1,0,1,1,1,0,1,0,1,1,1],
        [1,0,1,0,1,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1],
        [1,0,1,1,1,0,1,1,1,0,1,1,1,0,1,0,1,

# 初始化OpenMV摄像头
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.skip_frames(time = 200)

# 定义迷宫的宽度和高度
maze_width = len(maze[0])
maze_height = len(maze)

# 定义起点和终点的坐标
start = (0, 1)
end = (maze_height - 1, maze_width - 2)

# 定义D*算法的节点类
class Node:
    def __init__(self, x, y):
        self.x = x
        self.y = y
        self.g = float("inf")
        self.rhs = float("inf")
        self.parent = None
    
    def __lt__(self, other):
        return (self.g + self.h) < (other.g + other.h)

# 定义D*算法的路径规划函数
def DStar(maze, start, end):
    # 初始化节点列表
    nodes = [[Node(i, j) for j in range(maze_width)] for i in range(maze_height)]
    
    # 设置起点和终点的代价值
    nodes[start[0]][start[1]].g = 0
    nodes[start[0]][start[1]].rhs = 0
    
    # 定义启发式函数（欧几里得距离）
    def heuristic(node):
        return ((node.x - end[0]) ** 2 + (node.y - end[1]) ** 2) ** 0.5
    
    # 更新节点的代价值
    def updateNode(node):
        if node != start:
            g_values = [nodes[node.x-1][node.y].g + 1,
                        nodes[node.x+1][node.y].g + 1,
                        nodes[node.x][node.y-1].g + 1,
                        nodes[node.x][node.y+1].g + 1]
            node.rhs = min(g_values)
        
        if node in open_list:
            open_list.remove(node)
        
        if node.g != node.rhs:
            open_list.append(node)
    
    # 更新节点的父节点
    def updateParent(node):
        min_g = float("inf")
        parent = None
        
        neighbors = [(node.x-1, node.y),
                     (node.x+1, node.y),
                     (node.x, node.y-1),
                     (node.x, node.y+1)]
        
        for neighbor in neighbors:
            if 0 <= neighbor[0] < maze_height and 0 <= neighbor[1] < maze_width:
                if nodes[neighbor[0]][neighbor[1]].g + 1 < min_g:
                    min_g = nodes[neighbor[0]][neighbor[1]].g + 1
                    parent = (neighbor[0], neighbor[1])
        
        node.g = min_g
        node.parent = parent
    
    # 初始化开放列表和关闭列表
    open_list = [nodes[end[0]][end[1]]]
    closed_list = []
    
    # 开始路径规划
    while open_list:
        current = min(open_list)
        
        if current == nodes[start[0]][start[1]]:
            break
        
        open_list.remove(current)
        closed_list.append(current)
        
        neighbors = [(current.x-1, current.y),
                     (current.x+1, current.y),
                     (current.x, current.y-1),
                     (current.x, current.y+1)]
        
        for neighbor in neighbors:
            if 0 <= neighbor[0] < maze_height and 0 <= neighbor[1] < maze_width:
                if maze[neighbor[0]][neighbor[1]] == 1:
                    continue
                
                if nodes[neighbor[0]][neighbor[1]] not in closed_list:
                    updateParent(nodes[neighbor[0]][neighbor[1]])
                    
                    if nodes[neighbor[0]][neighbor[1]] not in open_list:
                        open_list.append(nodes[neighbor[0]][neighbor[1]])
                
                updateNode(nodes[neighbor[0]][neighbor[1]])
    
    # 输出路径
    path = []
    current = nodes[start[0]][start[1]]
    
    while current != nodes[end[0]][end[1]]:
        path.append((current.x, current.y))
        current = nodes[current.parent[0]][current.parent[1]]
    
    path.append(end)
    
    return path

# 进行路径规划
path = DStar(maze, start, end)
print(path)

请将以上代码复制到OpenMV IDE中，并根据您的具体需求进行修改和调试。运行代码后，您将获得一条路径，路径上的坐标用于找到在迷宫数组中对应的位置，并将其值设置为3以表示路径。

请注意，以上代码仅是一个示例，可能需要根据实际情况进行调整和优化。希望对您有所帮助！如有任何问题，请随时向我提问。