JavaScript で自動運転とドローン技術について学ぶ

// 导入Tensorflow.js和预训练模型
const tf = require('@tensorflow/tfjs-node');
const cocoSsd = require('@tensorflow-models/coco-ssd');

// 加载预训练模型
async function loadModel() {
  const model = await cocoSsd.load();
  return model;
}

// 对图像进行对象检测
async function detectObjects(imagePath) {
  // 加载图像
  const image = await tf.node.decodeImage(imagePath);
  const model = await loadModel();

  // 对图像进行对象检测
  const predictions = await model.detect(image);

  // 打印检测结果
  predictions.forEach(prediction => {
    console.log(`对象: ${prediction.class}, 置信度: ${prediction.score}`);
  });
}

// 测试
detectObjects('image.jpg');

// 定义A-星算法类
class AStar {
  constructor(grid) {
    this.grid = grid;
  }

  // 寻找最优路径
  findPath(startNode, endNode) {
    // TODO: 实现A-星算法
  }
}

// 定义节点类
class Node {
  constructor(x, y) {
    this.x = x;
    this.y = y;
    this.gCost = Infinity;
    this.hCost = 0;
    this.fCost = 0;
    this.parent = null;
  }
}

// 测试
const grid = [
  [1, 0, 0],
  [1, 1, 1],
  [0, 0, 1]
];

const startNode = new Node(0, 0);
const endNode = new Node(2, 2);

const astar = new AStar(grid);
const path = astar.findPath(startNode, endNode);

console.log(path);

// 导入Drone.js和相关库
const {Drone, Mission} = require('drone-js');

// 创建无人机实例
const drone = new Drone('192.168.1.1');

// 起飞
drone.takeoff();

// 飞行到指定位置
drone.goTo(40.7128, -74.0060, 100);

// 降落
drone.land();

// 导入OpenCV.js和相关库
const cv = require('opencv.js');

// 加载图像
const image = cv.imread('image.jpg');

// 转换为灰度图像
cv.cvtColor(image, image, cv.COLOR_RGB2GRAY);

// 进行目标追踪
const kernel = new cv.Mat();
cv.Canny(image, image, 50, 150, 3);

// 显示结果
cv.imshow('image', image);
cv.waitKey();