请写一段AirSim无人机在三维空间中实现A*+DWA算法的代码。

在AirSim（Microsoft的开源飞行模拟平台）中，要实现A* + DWA（动态窗口避障路径规划算法）算法，你需要首先安装AirSim库并了解其Python API。这里是一个简化的示例代码片段，展示了如何在一个基本框架内集成这两个导航算法：

import numpy as np
from airsim.types import Pose, Vector3r
from airsim.utils import distance

class AstarDwaPlanner:
    def __init__(self, start_pose, goal_pose):
        self.start_pose = start_pose
        self.goal_pose = goal_pose
        self.map_data = load_map_data()  # 假设已加载地图数据
        self.astar_graph = build_astar_graph(map_data)  # 构建A*图
        self.dwa_params = DWAParams()  # 设置DWA参数

    def plan_path(self):
        astar_path = self.astar_search(start_pose, goal_pose)
        if astar_path is not None:
            dwa_path = self.execute_dwa(astar_path)
            return dwa_path
        else:
            print("No path found from start to goal")
            return []

    def astar_search(self, start, goal):
        # 使用A*搜索算法找到最短路径
        pass  # 实现细节取决于AirSim的API和自定义的A*算法

    def execute_dwa(self, path):
        current_pose = start_pose
        waypoints = [pose.position for pose in path]
        while current_pose != goal_pose:
            next_waypoint = self.select_next_waypoint(waypoints, current_pose)
            current_pose = self.move_robot_to_next_waypoint(current_pose, next_waypoint)
        return path

    def select_next_waypoint(self, waypoints, current_pose):
        # 根据DWA参数计算下一个安全目标点
        # 这里需要考虑速度、障碍物避免等
        pass

    def move_robot_to_next_waypoint(self, current_pose, next_waypoint):
        # 发送移动命令到AirSim控制飞机到下一目标点
        client = MultirotorClient()
        client.move_by_local_position_async(Vector3r(next_waypoint.x_val, next_waypoint.y_val, current_pose.z_val), True)
        return client.get_current_position().position

# ... 定义DWAParams类和其他必要的辅助函数

注意，这只是一个基础的模板，并未包含完整的A*搜索和DWA路径跟踪的所有细节，例如代价函数的选择、启发式函数的实现、局部路径调整以及处理AirSim实时反馈等。实际应用中，你还需要根据AirSim的具体文档和功能进行相应的修改。