连接无人机后,打开终端并telnet 192.168.1.1 - 这是直升机的IP。 对于 Linux,你可以使用 Linux 忙碌盒.
应用架构
我们的代码将分为以下几个模块:
具有用于语音检测的语音 API 的用户界面;
过滤命令并与标准进行比较;
向无人机发送命令;
现场视频直播。
只要有互联网连接,API 就可以工作。 为了确保这一点,我们添加了以太网连接。
是时候创建一个应用程序了!
代码
首先,让我们创建一个新文件夹并使用终端切换到它。
然后我们使用以下命令创建一个 Node 项目。
首先,我们安装所需的依赖项。
npm安装
我们将支持以下命令:
脱掉;
降落;
向上——无人机上升半米并悬停;
向下 - 坠落半米并冻结;
向左 - 向左移动半米;
向右 - 向右移动半米;
旋转——顺时针旋转90度;
向前-向前移动半米;
back - 向后退半米;
停止。
这是允许您接受命令、过滤命令并控制无人机的代码。
const express = require('express');
const bodyparser = require('body-parser');
var arDrone = require('ar-drone');
const router = express.Router();
const app = express();
const commands = ['takeoff', 'land','up','down','goleft','goright','turn','goforward','gobackward','stop'];
var drone = arDrone.createClient();
// disable emergency
drone.disableEmergency();
// express
app.use(bodyparser.json());
app.use(express.static(__dirname + '/public'));
router.get('/',(req,res) => {
res.sendFile('index.html');
});
router.post('/command',(req,res) => {
console.log('command recieved ', req.body);
console.log('existing commands', commands);
let command = req.body.command.replace(/ /g,'');
if(commands.indexOf(command) !== -1) {
switch(command.toUpperCase()) {
case "TAKEOFF":
console.log('taking off the drone');
drone.takeoff();
break;
case "LAND":
console.log('landing the drone');
drone.land();
break;
case "UP":
console.log('taking the drone up half meter');
drone.up(0.2);
setTimeout(() => {
drone.stop();
clearTimeout();
},2000);
break;
case "DOWN":
console.log('taking the drone down half meter');
drone.down(0.2);
setTimeout(() => {
drone.stop();
clearTimeout();
},2000);
break;
case "GOLEFT":
console.log('taking the drone left 1 meter');
drone.left(0.1);
setTimeout(() => {
drone.stop();
clearTimeout();
},1000);
break;
case "GORIGHT":
console.log('taking the drone right 1 meter');
drone.right(0.1);
setTimeout(() => {
drone.stop();
clearTimeout();
},1000);
break;
case "TURN":
console.log('turning the drone');
drone.clockwise(0.4);
setTimeout(() => {
drone.stop();
clearTimeout();
},2000);
break;
case "GOFORWARD":
console.log('moving the drone forward by 1 meter');
drone.front(0.1);
setTimeout(() => {
drone.stop();
clearTimeout();
},2000);
break;
case "GOBACKWARD":
console.log('moving the drone backward 1 meter');
drone.back(0.1);
setTimeout(() => {
drone.stop();
clearTimeout();
},2000);
break;
case "STOP":
drone.stop();
break;
default:
break;
}
}
res.send('OK');
});
app.use('/',router);
app.listen(process.env.port || 3000);
下面是监听用户并向 Node 服务器发送命令的 HTML 和 JavaScript 代码。
<!DOCTYPE html>
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<title>Voice Controlled Notes App</title>
<meta name="description" content="">
<meta name="viewport" content="width=device-width, initial-scale=1">
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/shoelace-css/1.0.0-beta16/shoelace.css">
<link rel="stylesheet" href="styles.css">
</head>
<body>
<div class="container">
<h1>Voice Controlled Drone</h1>
<p class="page-description">A tiny app that allows you to control AR drone using voice</p>
<h3 class="no-browser-support">Sorry, Your Browser Doesn't Support the Web Speech API. Try Opening This Demo In Google Chrome.</h3>
<div class="app">
<h3>Give the command</h3>
<div class="input-single">
<textarea id="note-textarea" placeholder="Create a new note by typing or using voice recognition." rows="6"></textarea>
</div>
<button id="start-record-btn" title="Start Recording">Start Recognition</button>
<button id="pause-record-btn" title="Pause Recording">Pause Recognition</button>
<p id="recording-instructions">Press the <strong>Start Recognition</strong> button and allow access.</p>
</div>
</div>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
<script src="script.js"></script>
</body>
</html>
还有用于处理语音命令的 JavaScript 代码,将它们发送到 Node 服务器。
try {
var SpeechRecognition = window.SpeechRecognition || window.webkitSpeechRecognition;
var recognition = new SpeechRecognition();
}
catch(e) {
console.error(e);
$('.no-browser-support').show();
$('.app').hide();
}
// other code, please refer GitHub source
recognition.onresult = function(event) {
// event is a SpeechRecognitionEvent object.
// It holds all the lines we have captured so far.
// We only need the current one.
var current = event.resultIndex;
// Get a transcript of what was said.
var transcript = event.results[current][0].transcript;
// send it to the backend
$.ajax({
type: 'POST',
url: '/command/',
data: JSON.stringify({command: transcript}),
success: function(data) { console.log(data) },
contentType: "application/json",
dataType: 'json'
});
};