Python使用A*算法实现路径规划，可自主设置起点终点和路径障碍，并用pugame输出

好的，让我来解答你的问题。首先，A*算法是一种启发式搜索算法，可用于求解最短路径问题。其基本思想是：在搜索过程中，通过启发式函数估计每个节点到目标节点的距离，从而选择最优的节点进行扩展，直到达到目标节点。 下面是一个Python实现A*算法的示例代码： ```python import heapq def heuristic(a, b): # 计算启发式函数，这里使用曼哈顿距离 return abs(a[0] - b[0]) + abs(a[1] - b[1]) def astar(array, start, goal): # 初始化起点和终点 neighbors = [(0,1),(0,-1),(1,0),(-1,0),(1,1),(1,-1),(-1,1),(-1,-1)] close_set = set() came_from = {} gscore = {start:0} fscore = {start:heuristic(start, goal)} oheap = [] heapq.heappush(oheap, (fscore[start], start)) while oheap: current = heapq.heappop(oheap)[1] if current == goal: data = [] while current in came_from: data.append(current) current = came_from[current] return data[::-1] close_set.add(current) for i, j in neighbors: neighbor = current[0] + i, current[1] + j tentative_g_score = gscore[current] + heuristic(current, neighbor) if 0 <= neighbor[0] < array.shape[0]: if 0 <= neighbor[1] < array.shape[1]: if array[neighbor[0]][neighbor[1]] == 1: continue else: # 超出边界 continue else: # 超出边界 continue if neighbor in close_set and tentative_g_score >= gscore.get(neighbor, 0): continue if tentative_g_score < gscore.get(neighbor, 0) or neighbor not in [i[1]for i in oheap]: came_from[neighbor] = current gscore[neighbor] = tentative_g_score fscore[neighbor] = tentative_g_score + heuristic(neighbor, goal) heapq.heappush(oheap, (fscore[neighbor], neighbor)) return None # 主程序 import pygame as pg import numpy as np # 设置常量 WIDTH, HEIGHT = 640, 480 TILESIZE = 20 FPS = 30 # 初始化pygame pg.init() screen = pg.display.set_mode((WIDTH, HEIGHT)) clock = pg.time.Clock() # 设置颜色 BLACK = (0, 0, 0) WHITE = (255, 255, 255) GREEN = (0, 255, 0) RED = (255, 0, 0) BLUE = (0, 0, 255) # 设置地图 maze = np.zeros((int(HEIGHT/TILESIZE), int(WIDTH/TILESIZE))) # 设置起点和终点 start = (int(np.random.randint(0, int(WIDTH/TILESIZE)-1)), int(np.random.randint(0, int(HEIGHT/TILESIZE)-1))) goal = (int(np.random.randint(0, int(WIDTH/TILESIZE)-1)), int(np.random.randint(0, int(HEIGHT/TILESIZE)-1))) # 设置障碍 for i in range(np.random.randint(50, 100)): x = int(np.random.randint(0, int(WIDTH/TILESIZE)-1)) y = int(np.random.randint(0, int(HEIGHT/TILESIZE)-1)) if (x, y) != start and (x, y) != goal: maze[y][x] = 1 # 运行A*算法 path = astar(maze, start, goal) print(path) # 绘制地图 def draw_grid(): for x in range(0, WIDTH, TILESIZE): pg.draw.line(screen, WHITE, (x, 0), (x, HEIGHT)) for y in range(0, HEIGHT, TILESIZE): pg.draw.line(screen, WHITE, (0, y), (WIDTH, y)) def draw_maze(): for i in range(maze.shape[0]): for j in range(maze.shape[1]): if maze[i][j] == 1: pg.draw.rect(screen, RED, (j*TILESIZE, i*TILESIZE, TILESIZE, TILESIZE)) def draw_path(): for i in range(len(path)-1): pg.draw.line(screen, BLUE, (path[i][0]*TILESIZE+TILESIZE/2, path[i][1]*TILESIZE+TILESIZE/2), (path[i+1][0]*TILESIZE+TILESIZE/2, path[i+1][1]*TILESIZE+TILESIZE/2), 5) def draw_start_end(): pg.draw.rect(screen, GREEN, (start[0]*TILESIZE, start[1]*TILESIZE, TILESIZE, TILESIZE)) pg.draw.rect(screen, GREEN, (goal[0]*TILESIZE, goal[1]*TILESIZE, TILESIZE, TILESIZE)) # 主循环 running = True while running: # 事件处理 for event in pg.event.get(): if event.type == pg.QUIT: running = False # 绘制地图 screen.fill(BLACK) draw_grid() draw_maze() draw_path() draw_start_end() # 刷新屏幕 pg.display.flip() clock.tick(FPS) # 退出pygame pg.quit() ``` 这段代码实现了以下功能： 1. 生成一个随机的地图，包括起点、终点和障碍； 2. 使用A*算法求解起点到终点的最短路径； 3. 使用Pygame绘制地图和路径。 你可以将这段代码保存为一个Python文件并运行它，然后就可以看到A*算法求解的最短路径了。注意，这段代码中使用了NumPy和Pygame库，你需要先安装这两个库才能运行代码。 希望我的回答能够帮到你！