集群控制的超大规模无人机表演系统原型代码(附详细的python源码)

以下是一个以下是一个基于分布式集群控制的超大规模无人机表演系统原型代码，整合了路径规划、灯光同步、动态编队等核心技术模块。该系统采用分形算法生成龙珠形态，通过时空同步协议确保万架无人机精准协作：

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from scipy.spatial import KDTree
from datetime import datetime
import asyncio
from dronekit import connect, VehicleMode, LocationGlobalRelative

class DragonSphere:
    def __init__(self, num_drones=10000):
        self.num_drones = num_drones
        self.fractal_level = 6  # 分形迭代次数
        self.base_radius = 300  # 基准半径（米）
        self.color_cycle = np.linspace(0, 1, 100)
        
        # 初始化分布式集群
        self.swarm = [DroneNode(i) for i in range(num_drones)]
        
        # 生成龙珠基础拓扑
        self.positions = self.generate_fractal_sphere()
        self.kdtree = KDTree(self.positions)
        
    def generate_fractal_sphere(self):
        """生成分形球体点云"""
        phi = np.pi * (3 - np.sqrt(5))  # 黄金角分布
        points = []
        for i in range(self.num_drones):
            y = 1 - (i / (self.num_drones - 1)) * 2
            radius = np.sqrt(1 - y*y)
            theta = phi * i
            x = np.cos(theta) * radius
            z = np.sin(theta) * radius
            
            # 添加分形扰动
            for _ in range(self.fractal_level):
                x += np.random.normal(0, 0.02)
                y += np.random.normal(0, 0.02) 
                z += np.random.normal(0, 0.02)
            
            points.append([x, y, z])
        
        # 标准化到实际尺寸
        points = np.array(points) * self.base_radius
        return points

    async def dynamic_animation(self, duration=600):
        """动态水波效果"""
        start_time = datetime.now()
        frame_interval = 0.1  # 100ms同步周期
        
        while (datetime.now() - start_time).seconds < duration:
            t = (datetime.now() - start_time).total_seconds()
            
            # 计算动态形变
            wave1 = 0.5 * np.sin(t/2) * np.sin(self.positions[:,0]/50 + t)
            wave2 = 0.3 * np.cos(t/3) * np.cos(self.positions[:,1]/30 + t*1.2)
            
            # 生成