ros2-web-integration

ROS2 Web 集成技能

何时使用此技能

• 构建 Web 仪表板，以监控或控制运行 ROS2 的机器人
• 将机器人上的摄像头画面（MJPEG、WebRTC、压缩 WebSocket）流式传输到浏览器
• 将 ROS2 服务和操作公开为 REST API 端点
• 实现 Web UI 与 ROS2 节点之间的双向 WebSocket 通信
• 设置 rosbridge_suite，以便快速原型开发或集成 foxglove
• 编写自定义 FastAPI 或 Flask 桥接程序，将 ROS2 用于生产部署
• 为机器人 Web 界面添加身份验证、速率限制或 CORS
• 在运行 rclpy 执行器的同时运行异步 Web 服务（uvicorn），避免死锁
• 从浏览器操纵杆向 cmd_vel 发布远程操控命令
• 通过 HTTP 提供 ROS2 参数配置页面或诊断仪表板

架构概述

对比表

特性	rosbridge_suite	自定义 FastAPI 桥接程序	自定义 Flask 桥接程序
延迟	~5-15ms（WebSocket）	~2-5ms（WebSocket），~10-30ms（REST）	~10-50ms（仅 REST，不含扩展）
吞吐量	中（JSON 序列化开销）	高（二进制 WebSocket、异步）	低-中（同步、受 GIL 限制）
身份验证	基本（rosauth，功能有限）	完整（JWT、OAuth2、API 密钥）	完整（Flask-Login、JWT）
复杂度	低（启动并连接）	中（必须管理两个事件循环）	中（必须管理线程）
视频流	需要单独的 web_video_server	原生支持（MJPEG、WebSocket 二进制）	通过生成器响应提供 MJPEG
适用于生产环境	否（会暴露完整的主题图）	是	是（搭配 gunicorn）
适用场景	原型开发、foxglove、快速演示	生产 API、高性能流传输	简单的内部工具、旧版系统

何时使用 rosbridge，何时使用自定义桥接程序

在以下情况下使用 rosbridge_suite：

• 你需要在 10 分钟内搭建可用的桥接程序
• 客户端是 foxglove、webviz 或其他支持 rosbridge 的工具
• 无需考虑安全性（本地网络、演示环境）
• Web 与 ROS2 之间不需要自定义业务逻辑

在以下情况下使用自定义桥接程序（FastAPI/Flask）：

• 你需要身份验证、授权或速率限制
• 你只想公开特定主题/服务，而非整个 ROS2 图
• 你需要在向客户端发送数据前对数据进行转换或聚合
• 你需要 REST 端点，以便与非 WebSocket 客户端集成
• 你正在传输视频流，需要控制编码和画质
• 系统部署在生产环境或公共网络上

模式 1：rosbridge_suite

安装和启动

# Install rosbridge_suite
sudo apt install ros-${ROS_DISTRO}-rosbridge-suite

# Launch with default settings (port 9090)
ros2 launch rosbridge_server rosbridge_websocket_launch.xml

# Launch with custom port and SSL
ros2 launch rosbridge_server rosbridge_websocket_launch.xml \
    port:=9091 \
    ssl:=true \
    certfile:=/etc/ssl/certs/robot.pem \
    keyfile:=/etc/ssl/private/robot.key

# Launch with authentication (rosauth)
ros2 launch rosbridge_server rosbridge_websocket_launch.xml \
    authenticate:=true

JavaScript 客户端（roslibjs）

// Connect to rosbridge WebSocket
const ros = new ROSLIB.Ros({ url: 'ws://robot-host:9090' });

ros.on('connection', () => console.log('Connected to rosbridge'));
ros.on('error', (err) => console.error('Connection error:', err));
ros.on('close', () => console.log('Connection closed'));

// Subscribe to compressed camera images
const imageTopic = new ROSLIB.Topic({
  ros: ros,
  name: '/camera/image/compressed',
  messageType: 'sensor_msgs/msg/CompressedImage',
  // Throttle to 10 Hz to avoid flooding the browser
  throttle_rate: 100,
  // Queue size of 1 — drop stale frames
  queue_size: 1
});

imageTopic.subscribe((msg) => {
  // msg.data is base64-encoded JPEG
  const imgElement = document.getElementById('camera-feed');
  imgElement.src = 'data:image/jpeg;base64,' + msg.data;
});

// Call a ROS2 service
const getMapSrv = new ROSLIB.Service({
  ros: ros,
  name: '/map_server/map',
  serviceType: 'nav_msgs/srv/GetMap'
});

getMapSrv.callService(new ROSLIB.ServiceRequest({}), (result) => {
  console.log('Map received:', result.map.info.width, 'x', result.map.info.height);
}, (error) => {
  console.error('Service call failed:', error);
});

// Publish velocity commands from a virtual joystick
const cmdVelTopic = new ROSLIB.Topic({
  ros: ros,
  name: '/cmd_vel',
  messageType: 'geometry_msgs/msg/Twist'
});

function sendVelocity(linearX, angularZ) {
  const twist = new ROSLIB.Message({
    linear: { x: linearX, y: 0.0, z: 0.0 },
    angular: { x: 0.0, y: 0.0, z: angularZ }
  });
  cmdVelTopic.publish(twist);
}

// Publish at 10 Hz while joystick is active; stop on release
let joystickInterval = null;
function onJoystickMove(lx, az) {
  if (!joystickInterval) {
    joystickInterval = setInterval(() => sendVelocity(lx, az), 100);
  }
}
function onJoystickRelease() {
  clearInterval(joystickInterval);
  joystickInterval = null;
  sendVelocity(0.0, 0.0);  // Always send zero on release
}

局限性和性能

• JSON 序列化开销：所有消息都会序列化为 JSON，包括二进制数据（以 base64 编码）。一张 640x480 的 JPEG 压缩图像通过网络传输时会增大约 30%。
• 无法筛选主题：默认情况下，rosbridge 会公开 ROS2 图中的所有主题、服务和操作。任何已连接的客户端都可以向 /cmd_vel 发布消息。
• 单线程事件循环：rosbridge_server 使用单个 Tornado 事件循环。多个客户端的高频订阅可能会导致该循环无法处理其他任务。
• 没有内置速率限制：客户端可以按任意频率订阅。行为异常的客户端若以 30Hz 订阅点云，将耗尽服务端资源。
• 身份验证功能有限：rosauth 使用基于 MAC 的令牌和共享密钥，不支持 JWT、OAuth2 或基于角色的访问控制。

模式 2：自定义 FastAPI 桥接程序

项目结构

robot_web_bridge/
├── robot_web_bridge/
│   ├── __init__.py
│   ├── ros_node.py          # ROS2 node with shared state
│   ├── web_app.py           # FastAPI application
│   ├── main.py              # Entry point: starts both rclpy and uvicorn
│   ├── auth.py              # JWT authentication middleware
│   └── rate_limiter.py      # Token bucket rate limiter
├── config/
│   └── bridge_config.yaml   # Allowed topics, rate limits, auth keys
├── launch/
│   └── web_bridge.launch.py
├── package.xml
├── setup.py
└── setup.cfg

使用异步执行器的 ROS2 节点

# ros_node.py
import threading
import time
from typing import Optional

import rclpy
from rclpy.node import Node
from rclpy.executors import MultiThreadedExecutor
from rclpy.qos import QoSProfile, ReliabilityPolicy, HistoryPolicy
from sensor_msgs.msg import CompressedImage
from geometry_msgs.msg import Twist
from nav_msgs.msg import Odometry
from std_srvs.srv import Trigger


class RobotBridgeNode(Node):
    """ROS2 node that exposes topic data via thread-safe shared state."""

    def __init__(self):
        super().__init__('web_bridge_node')

        # Thread-safe shared state for latest messages
        self._lock = threading.Lock()
        self._latest_image: Optional[bytes] = None
        self._latest_odom: Optional[dict] = None
        self._image_timestamp: float = 0.0

        # QoS for sensor data — best effort, keep last 1
        sensor_qos = QoSProfile(
            reliability=ReliabilityPolicy.BEST_EFFORT,
            history=HistoryPolicy.KEEP_LAST,
            depth=1
        )

        # Subscribers
        self.create_subscription(
            CompressedImage, '/camera/image/compressed',
            self._image_cb, sensor_qos)
        self.create_subscription(
            Odometry, '/odom', self._odom_cb, sensor_qos)

        # Publisher for velocity commands
        self.cmd_vel_pub = self.create_publisher(Twist, '/cmd_vel', 10)

        # Service client for emergency stop
        self.estop_client = self.create_client(Trigger, '/emergency_stop')

        self.get_logger().info('Web bridge node initialized')

    def _image_cb(self, msg: CompressedImage):
        with self._lock:
            self._latest_image = bytes(msg.data)
            self._image_timestamp = time.monotonic()

    def _odom_cb(self, msg: Odometry):
        with self._lock:
            self._latest_odom = {
                'x': msg.pose.pose.position.x,
                'y': msg.pose.pose.position.y,
                'theta': 2.0 * __import__('math').atan2(
                    msg.pose.pose.orientation.z,
                    msg.pose.pose.orientation.w),
                'linear_vel': msg.twist.twist.linear.x,
                'angular_vel': msg.twist.twist.angular.z,
            }

    def get_latest_image(self) -> Optional[bytes]:
        with self._lock:
            return self._latest_image

    def get_latest_odom(self) -> Optional[dict]:
        with self._lock:
            return self._latest_odom.copy() if self._latest_odom else None

    def publish_cmd_vel(self, linear_x: float, angular_z: float):
        msg = Twist()
        msg.linear.x = float(linear_x)
        msg.angular.z = float(angular_z)
        self.cmd_vel_pub.publish(msg)

集成 ROS2 的 FastAPI 应用

# web_app.py
import base64
import asyncio
import time
from typing import Optional

from fastapi import FastAPI, WebSocket, WebSocketDisconnect, HTTPException, Depends
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel, Field

from .ros_node import RobotBridgeNode


class CmdVelRequest(BaseModel):
    linear_x: float = Field(ge=-1.0, le=1.0, description="Linear velocity m/s")
    angular_z: float = Field(ge=-2.0, le=2.0, description="Angular velocity rad/s")


def create_app(ros_node: RobotBridgeNode) -> FastAPI:
    app = FastAPI(title="Robot Web Bridge", version="1.0.0")

    # CORS — restrict to known origins in production
    app.add_middleware(
        CORSMiddleware,
        allow_origins=["https://dashboard.example.com"],
        allow_credentials=True,
        allow_methods=["GET", "POST", "PUT"],
        allow_headers=["Authorization", "Content-Type"],
    )

    # Store ros_node in app state so endpoints can access it
    app.state.ros_node = ros_node

    return app

用于流传输的 WebSocket 端点

# Add to web_app.py — WebSocket camera streaming endpoint

@app.websocket("/ws/camera")
async def camera_stream(websocket: WebSocket):
    """Stream compressed camera images as base64 over WebSocket.

    Supports per-client rate limiting via query parameter:
        ws://host/ws/camera?max_fps=10
    """
    await websocket.accept()
    ros_node: RobotBridgeNode = websocket.app.state.ros_node

    # Per-client rate limiting
    max_fps = int(websocket.query_params.get("max_fps", "15"))
    min_interval = 1.0 / max(1, min(max_fps, 30))  # Clamp 1-30 FPS
    last_send_time = 0.0
    last_image_bytes: Optional[bytes] = None

    try:
        while True:
            now = time.monotonic()
            elapsed = now - last_send_time

            if elapsed < min_interval:
                await asyncio.sleep(min_interval - elapsed)
                continue

            image_bytes = ros_node.get_latest_image()
            if image_bytes is None or image_bytes is last_image_bytes:
                # No new image available — avoid sending duplicates
                await asyncio.sleep(0.01)
                continue

            last_image_bytes = image_bytes
            last_send_time = time.monotonic()

            # Send as base64 JSON for browser compatibility
            b64_data = base64.b64encode(image_bytes).decode('ascii')
            await websocket.send_json({
                "type": "image",
                "format": "jpeg",
                "data": b64_data,
                "timestamp": last_send_time,
            })
    except WebSocketDisconnect:
        pass  # Client disconnected — clean exit
    except Exception as e:
        ros_node.get_logger().warn(f'WebSocket error: {e}')
    finally:
        # Graceful disconnect — no cleanup needed for read-only stream
        try:
            await websocket.close()
        except RuntimeError:
            pass  # Already closed

封装 ROS2 服务的 REST 端点

# Add to web_app.py — REST endpoints

@app.get("/api/robot/status")
async def get_robot_status():
    """Return current robot odometry and system status."""
    ros_node: RobotBridgeNode = app.state.ros_node
    odom = ros_node.get_latest_odom()
    if odom is None:
        raise HTTPException(status_code=503, detail="No odometry data available yet")
    return {
        "status": "active",
        "odometry": odom,
        "timestamp": time.time(),
    }


@app.post("/api/robot/cmd_vel")
async def post_cmd_vel(cmd: CmdVelRequest):
    """Send a velocity command to the robot."""
    ros_node: RobotBridgeNode = app.state.ros_node
    ros_node.publish_cmd_vel(cmd.linear_x, cmd.angular_z)
    return {"status": "ok", "linear_x": cmd.linear_x, "angular_z": cmd.angular_z}


@app.get("/api/robot/params/{param_name}")
async def get_parameter(param_name: str):
    """Read a ROS2 parameter from the bridge node."""
    ros_node: RobotBridgeNode = app.state.ros_node
    try:
        param = ros_node.get_parameter(param_name)
        return {"name": param_name, "value": param.value}
    except rclpy.exceptions.ParameterNotDeclaredException:
        raise HTTPException(status_code=404, detail=f"Parameter '{param_name}' not declared")


@app.put("/api/robot/params/{param_name}")
async def set_parameter(param_name: str, value: dict):
    """Set a ROS2 parameter on the bridge node.

    Body: {"value": <new_value>}
    """
    ros_node: RobotBridgeNode = app.state.ros_node
    try:
        param_value = value.get("value")
        if param_value is None:
            raise HTTPException(status_code=400, detail="Missing 'value' field")
        ros_node.set_parameters([rclpy.Parameter(param_name, value=param_value)])
        return {"name": param_name, "value": param_value, "status": "updated"}
    except rclpy.exceptions.ParameterNotDeclaredException:
        raise HTTPException(status_code=404, detail=f"Parameter '{param_name}' not declared")


@app.post("/api/robot/emergency_stop")
async def emergency_stop():
    """Call the emergency stop service."""
    ros_node: RobotBridgeNode = app.state.ros_node
    if not ros_node.estop_client.service_is_ready():
        raise HTTPException(status_code=503, detail="Emergency stop service not available")
    future = ros_node.estop_client.call_async(Trigger.Request())
    # Wait for result with timeout — run in executor to avoid blocking
    result = await asyncio.get_event_loop().run_in_executor(
        None, lambda: future.result(timeout=5.0)
    )
    return {"success": result.success, "message": result.message}

同时运行 FastAPI 和 rclpy

这是关键的集成环节。Uvicorn 在主线程中运行，rclpy 在后台线程中执行 spin 操作，并通过信号协调关闭。

# main.py
import signal
import sys
import threading

import rclpy
from rclpy.executors import MultiThreadedExecutor
import uvicorn

from .ros_node import RobotBridgeNode
from .web_app import create_app


def main():
    rclpy.init()
    ros_node = RobotBridgeNode()
    app = create_app(ros_node)

    # Spin rclpy in a background thread with a multi-threaded executor
    executor = MultiThreadedExecutor(num_threads=2)
    executor.add_node(ros_node)
    spin_thread = threading.Thread(target=executor.spin, daemon=True)
    spin_thread.start()

    # Shutdown coordination
    shutdown_event = threading.Event()

    def shutdown_handler(signum, frame):
        ros_node.get_logger().info('Shutdown signal received')
        shutdown_event.set()
        # Stop uvicorn by raising KeyboardInterrupt in main thread
        raise KeyboardInterrupt

    signal.signal(signal.SIGINT, shutdown_handler)
    signal.signal(signal.SIGTERM, shutdown_handler)

    try:
        # Run uvicorn in the main thread
        uvicorn.run(
            app,
            host="0.0.0.0",
            port=8080,
            log_level="info",
            # Do NOT use reload in production with rclpy
            reload=False,
        )
    except KeyboardInterrupt:
        pass
    finally:
        ros_node.get_logger().info('Shutting down web bridge...')
        executor.shutdown()
        ros_node.destroy_node()
        rclpy.shutdown()
        spin_thread.join(timeout=5.0)


if __name__ == '__main__':
    main()

模式 3：Flask 桥接程序

使用 rclpy 线程运行 Flask

Flask 是同步的。在与 Flask 相同的线程中运行 rclpy.spin() 会阻塞其中一个。正确做法是使用后台线程运行 ROS2 执行器。

# BAD: Blocking — rclpy.spin() never returns, Flask never starts
import rclpy
from flask import Flask, jsonify

app = Flask(__name__)

def bad_main():
    rclpy.init()
    node = rclpy.create_node('flask_bridge')
    rclpy.spin(node)  # Blocks forever — Flask never starts
    app.run(host='0.0.0.0', port=8080)

# GOOD: Threaded executor — rclpy spins in background, Flask serves in main thread
import threading
import rclpy
from rclpy.executors import MultiThreadedExecutor
from flask import Flask, jsonify

app = Flask(__name__)
ros_node = None

class SimpleRosNode(rclpy.node.Node):
    def __init__(self):
        super().__init__('flask_bridge')
        self._lock = threading.Lock()
        self._data = {}
        self.create_subscription(
            Odometry, '/odom', self._odom_cb,
            QoSProfile(reliability=ReliabilityPolicy.BEST_EFFORT, depth=1))

    def _odom_cb(self, msg):
        with self._lock:
            self._data['x'] = msg.pose.pose.position.x
            self._data['y'] = msg.pose.pose.position.y

    def get_data(self):
        with self._lock:
            return self._data.copy()

@app.route('/api/status')
def status():
    return jsonify(ros_node.get_data())

def main():
    global ros_node
    rclpy.init()
    ros_node = SimpleRosNode()

    executor = MultiThreadedExecutor()
    executor.add_node(ros_node)
    spin_thread = threading.Thread(target=executor.spin, daemon=True)
    spin_thread.start()

    try:
        app.run(host='0.0.0.0', port=8080, threaded=True)
    finally:
        executor.shutdown()
        ros_node.destroy_node()
        rclpy.shutdown()

何时使用 Flask，何时需要 FastAPI

在以下情况下使用 Flask：

• 只需要简单的 REST 端点（不需要 WebSocket）
• Web 桥接是仅供内部使用、并发用户较少的工具
• 团队已经熟悉 Flask，还没准备好采用异步方式
• 不需要自动生成 OpenAPI/Swagger 文档

在以下情况下使用 FastAPI：

• 需要用于实时流传输的 WebSocket 端点
• 需要高并发（异步处理程序、多个客户端同时连接）
• 希望通过 Pydantic 模型自动验证请求
• 希望为机器人 API 自动生成 OpenAPI 文档
• 需要向多个客户端传输视频或传感器数据

视频流传输模式

MJPEG 流传输

MJPEG 流可直接在 <img> 标签中使用，无需 JavaScript。适用于简单的仪表板。

# mjpeg_stream.py — MJPEG streaming endpoint for FastAPI
import cv2
import time
from fastapi import FastAPI
from fastapi.responses import StreamingResponse
from .ros_node import RobotBridgeNode


def generate_mjpeg(ros_node: RobotBridgeNode, max_fps: int = 15):
    """Generator that yields MJPEG frames as multipart HTTP response chunks."""
    min_interval = 1.0 / max_fps
    last_send = 0.0

    while True:
        now = time.monotonic()
        if now - last_send < min_interval:
            time.sleep(min_interval - (now - last_send))
            continue

        image_bytes = ros_node.get_latest_image()
        if image_bytes is None:
            time.sleep(0.05)
            continue

        last_send = time.monotonic()
        # Yield as multipart MJPEG frame
        yield (
            b'--frame\r\n'
            b'Content-Type: image/jpeg\r\n'
            b'Content-Length: ' + str(len(image_bytes)).encode() + b'\r\n'
            b'\r\n' + image_bytes + b'\r\n'
        )


@app.get("/video/mjpeg")
async def mjpeg_feed():
    ros_node: RobotBridgeNode = app.state.ros_node
    return StreamingResponse(
        generate_mjpeg(ros_node, max_fps=15),
        media_type="multipart/x-mixed-replace; boundary=frame"
    )

浏览器用法——无需 JavaScript：

<img src="http://robot-host:8080/video/mjpeg" alt="Robot Camera" />

通过 webrtc_ros 使用 WebRTC

如需低延迟、高质量的视频流传输，请使用 webrtc_ros 软件包。

# webrtc_ros launch config
# webrtc_bridge.launch.py
from launch import LaunchDescription
from launch_ros.actions import Node

def generate_launch_description():
    return LaunchDescription([
        Node(
            package='webrtc_ros',
            executable='webrtc_ros_server_node',
            name='webrtc_server',
            parameters=[{
                'port': 8443,
                'image_transport': 'compressed',
                # Bind to all interfaces for remote access
                'address': '0.0.0.0',
            }],
            remappings=[
                ('image', '/camera/image_raw'),
            ],
        ),
    ])

通过 WebSocket 传输压缩话题

为兼顾简洁性与性能，可通过二进制 WebSocket 传输压缩图像话题。

# Binary WebSocket streaming — more efficient than base64 JSON
@app.websocket("/ws/camera/binary")
async def camera_stream_binary(websocket: WebSocket):
    """Stream JPEG frames as binary WebSocket messages.

    ~30% more bandwidth-efficient than base64 JSON encoding.
    Client must handle raw binary blobs.
    """
    await websocket.accept()
    ros_node: RobotBridgeNode = websocket.app.state.ros_node
    min_interval = 1.0 / 15  # 15 FPS max

    try:
        last_bytes = None
        while True:
            image_bytes = ros_node.get_latest_image()
            if image_bytes is not None and image_bytes is not last_bytes:
                last_bytes = image_bytes
                await websocket.send_bytes(image_bytes)
            await asyncio.sleep(min_interval)
    except WebSocketDisconnect:
        pass

客户端 JavaScript：

const ws = new WebSocket('ws://robot-host:8080/ws/camera/binary');
ws.binaryType = 'arraybuffer';

ws.onmessage = (event) => {
  const blob = new Blob([event.data], { type: 'image/jpeg' });
  const url = URL.createObjectURL(blob);
  const img = document.getElementById('camera-feed');
  // Revoke previous URL to prevent memory leaks
  if (img.src.startsWith('blob:')) URL.revokeObjectURL(img.src);
  img.src = url;
};

双向通信

从 Web UI 向机器人发送命令

# teleop_handler.py — WebSocket teleop with command timeout watchdog
import asyncio
import time
from fastapi import WebSocket, WebSocketDisconnect

from .ros_node import RobotBridgeNode


class TeleopHandler:
    """Handles joystick input from browser with safety watchdog.

    If no command is received for 500ms, publishes zero velocity
    to prevent the robot from running away on disconnect.
    """

    COMMAND_TIMEOUT_S = 0.5  # Zero velocity after 500ms silence

    def __init__(self, ros_node: RobotBridgeNode):
        self.ros_node = ros_node
        self.last_command_time = 0.0

    async def handle(self, websocket: WebSocket):
        await websocket.accept()
        self.last_command_time = time.monotonic()

        # Start watchdog task
        watchdog_task = asyncio.create_task(self._watchdog())

        try:
            while True:
                data = await websocket.receive_json()
                # Expected: {"linear_x": 0.5, "angular_z": -0.3}
                linear_x = float(data.get("linear_x", 0.0))
                angular_z = float(data.get("angular_z", 0.0))

                # Clamp values for safety
                linear_x = max(-1.0, min(1.0, linear_x))
                angular_z = max(-2.0, min(2.0, angular_z))

                self.ros_node.publish_cmd_vel(linear_x, angular_z)
                self.last_command_time = time.monotonic()

                # Acknowledge to client
                await websocket.send_json({"ack": True, "t": self.last_command_time})
        except WebSocketDisconnect:
            pass
        finally:
            watchdog_task.cancel()
            # Always send zero on disconnect
            self.ros_node.publish_cmd_vel(0.0, 0.0)

    async def _watchdog(self):
        """Publish zero velocity if no command received within timeout."""
        while True:
            await asyncio.sleep(0.1)
            if time.monotonic() - self.last_command_time > self.COMMAND_TIMEOUT_S:
                self.ros_node.publish_cmd_vel(0.0, 0.0)

将机器人状态发送到 Web UI

# Status broadcast — push robot state to all connected WebSocket clients
class StatusBroadcaster:
    """Broadcasts robot status to all connected WebSocket clients."""

    def __init__(self, ros_node: RobotBridgeNode):
        self.ros_node = ros_node
        self.clients: set[WebSocket] = set()

    async def register(self, websocket: WebSocket):
        await websocket.accept()
        self.clients.add(websocket)
        try:
            # Keep connection alive — client sends pings
            while True:
                await websocket.receive_text()
        except WebSocketDisconnect:
            self.clients.discard(websocket)

    async def broadcast_loop(self, interval: float = 0.1):
        """Call this as a background task on app startup."""
        while True:
            odom = self.ros_node.get_latest_odom()
            if odom and self.clients:
                dead_clients = set()
                for client in self.clients.copy():
                    try:
                        await client.send_json({"type": "status", "odom": odom})
                    except Exception:
                        dead_clients.add(client)
                self.clients -= dead_clients
            await asyncio.sleep(interval)

命令确认模式

为确保命令可靠执行，可通过 WebSocket 使用带关联 ID 的请求-响应模式。

# Client sends:  {"id": "cmd-001", "action": "navigate_to", "x": 1.0, "y": 2.0}
# Server responds: {"id": "cmd-001", "status": "accepted", "estimated_time": 12.5}
# Server updates: {"id": "cmd-001", "status": "in_progress", "progress": 0.45}
# Server completes: {"id": "cmd-001", "status": "completed", "result": "success"}

@app.websocket("/ws/commands")
async def command_channel(websocket: WebSocket):
    await websocket.accept()
    ros_node: RobotBridgeNode = websocket.app.state.ros_node

    while True:
        try:
            data = await websocket.receive_json()
            cmd_id = data.get("id", "unknown")
            action = data.get("action")

            if action == "navigate_to":
                await websocket.send_json({
                    "id": cmd_id, "status": "accepted"
                })
                # Dispatch to ROS2 action client (non-blocking)
                asyncio.create_task(
                    execute_navigation(ros_node, websocket, cmd_id,
                                       data["x"], data["y"])
                )
            else:
                await websocket.send_json({
                    "id": cmd_id, "status": "error",
                    "message": f"Unknown action: {action}"
                })
        except WebSocketDisconnect:
            break

速率限制与背压

服务端速率限制

# rate_limiter.py — Token bucket rate limiter
import time
import threading


class TokenBucketRateLimiter:
    """Token bucket rate limiter for controlling message throughput.

    Usage:
        limiter = TokenBucketRateLimiter(tokens_per_second=10, burst_size=15)
        if limiter.acquire():
            send_message()
        else:
            drop_or_queue()
    """

    def __init__(self, tokens_per_second: float, burst_size: int = 0):
        self.rate = tokens_per_second
        self.burst_size = burst_size or int(tokens_per_second)
        self._tokens = float(self.burst_size)
        self._last_refill = time.monotonic()
        self._lock = threading.Lock()

    def acquire(self) -> bool:
        """Try to acquire a token. Returns True if allowed, False if rate limited."""
        with self._lock:
            now = time.monotonic()
            elapsed = now - self._last_refill
            self._tokens = min(
                self.burst_size,
                self._tokens + elapsed * self.rate
            )
            self._last_refill = now

            if self._tokens >= 1.0:
                self._tokens -= 1.0
                return True
            return False

    def reset(self):
        """Reset to full burst capacity."""
        with self._lock:
            self._tokens = float(self.burst_size)
            self._last_refill = time.monotonic()

客户端驱动的背压

允许客户端自行请求速率，以匹配其处理能力。

@app.websocket("/ws/sensor/{topic_name}")
async def sensor_stream(websocket: WebSocket, topic_name: str):
    await websocket.accept()

    # Client sends desired rate on connect
    config = await websocket.receive_json()
    requested_hz = config.get("hz", 10)
    requested_hz = max(1, min(requested_hz, 30))  # Clamp to 1-30 Hz
    interval = 1.0 / requested_hz

    ros_node: RobotBridgeNode = websocket.app.state.ros_node

    try:
        while True:
            data = ros_node.get_latest_odom()
            if data:
                await websocket.send_json({"topic": topic_name, "data": data})
            await asyncio.sleep(interval)
    except WebSocketDisconnect:
        pass

自适应降低画质

当带宽不足或客户端处理能力跟不上时，降低图像质量。

# Adaptive quality — reduce JPEG quality when send buffer backs up
import cv2
import numpy as np


async def adaptive_camera_stream(websocket: WebSocket, ros_node: RobotBridgeNode):
    quality = 80  # Start at 80% JPEG quality
    send_times = []

    while True:
        image_bytes = ros_node.get_latest_image()
        if image_bytes is None:
            await asyncio.sleep(0.05)
            continue

        # Re-encode with adaptive quality if needed
        if quality < 80:
            np_arr = np.frombuffer(image_bytes, np.uint8)
            img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
            _, image_bytes = cv2.imencode(
                '.jpg', img, [cv2.IMWRITE_JPEG_QUALITY, quality])
            image_bytes = image_bytes.tobytes()

        t0 = time.monotonic()
        await websocket.send_bytes(image_bytes)
        send_duration = time.monotonic() - t0

        # Track send times to detect backpressure
        send_times.append(send_duration)
        if len(send_times) > 30:
            send_times.pop(0)

        avg_send = sum(send_times) / len(send_times)
        # If average send time > 50ms, reduce quality
        if avg_send > 0.05 and quality > 20:
            quality -= 5
        elif avg_send < 0.02 and quality < 80:
            quality += 5

        await asyncio.sleep(1.0 / 15)

安全性

使用 Nginx 反向代理配置 TLS/HTTPS

切勿将机器人 Web 桥接直接暴露在不受信任的网络中。使用 nginx 作为终止 TLS 的反向代理。

# /etc/nginx/sites-available/robot-bridge
server {
    listen 443 ssl;
    server_name robot.example.com;

    ssl_certificate /etc/ssl/certs/robot.pem;
    ssl_certificate_key /etc/ssl/private/robot.key;
    ssl_protocols TLSv1.2 TLSv1.3;

    # REST API
    location /api/ {
        proxy_pass http://127.0.0.1:8080;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }

    # WebSocket endpoints
    location /ws/ {
        proxy_pass http://127.0.0.1:8080;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection "upgrade";
        proxy_read_timeout 86400;  # Keep WebSocket alive for 24h
    }

    # MJPEG video stream
    location /video/ {
        proxy_pass http://127.0.0.1:8080;
        proxy_buffering off;  # Critical for streaming
        proxy_cache off;
    }
}

基于令牌的身份验证（JWT）

# auth.py — JWT authentication for FastAPI robot bridge
import time
from typing import Optional

from fastapi import Request, HTTPException, WebSocket
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
import jwt

SECRET_KEY = "load-from-environment-variable"  # Use os.environ in production
ALGORITHM = "HS256"
TOKEN_EXPIRY_S = 3600  # 1 hour


class RobotAPIAuth(HTTPBearer):
    """JWT bearer token authentication for robot API endpoints."""

    def __init__(self, auto_error: bool = True):
        super().__init__(auto_error=auto_error)

    async def __call__(self, request: Request) -> dict:
        credentials: HTTPAuthorizationCredentials = await super().__call__(request)
        if not credentials:
            raise HTTPException(status_code=403, detail="No credentials provided")
        return self._verify_token(credentials.credentials)

    @staticmethod
    def _verify_token(token: str) -> dict:
        try:
            payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
            if payload.get("exp", 0) < time.time():
                raise HTTPException(status_code=401, detail="Token expired")
            return payload
        except jwt.InvalidTokenError:
            raise HTTPException(status_code=401, detail="Invalid token")


auth_scheme = RobotAPIAuth()


# Protect REST endpoints
@app.get("/api/robot/status", dependencies=[Depends(auth_scheme)])
async def protected_status():
    return {"status": "active"}


# Protect WebSocket endpoints — check token from query parameter
async def verify_ws_token(websocket: WebSocket) -> Optional[dict]:
    """WebSocket cannot use Authorization header — use query param."""
    token = websocket.query_params.get("token")
    if not token:
        await websocket.close(code=4001, reason="Missing token")
        return None
    try:
        return RobotAPIAuth._verify_token(token)
    except HTTPException:
        await websocket.close(code=4003, reason="Invalid token")
        return None

CORS 配置

# BAD: Allow all origins — any website can control your robot
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],        # Any website can send requests
    allow_methods=["*"],        # Including DELETE, PATCH
    allow_headers=["*"],
)

# GOOD: Explicit origins — only your dashboard can access the API
app.add_middleware(
    CORSMiddleware,
    allow_origins=[
        "https://dashboard.example.com",
        "https://monitor.internal.example.com",
    ],
    allow_credentials=True,
    allow_methods=["GET", "POST", "PUT"],
    allow_headers=["Authorization", "Content-Type"],
)

网络分段

机器人应运行在隔离网络中。Web 桥接是唯一一个同时连接机器人网络和面向用户网络的组件。

┌─────────────────┐     ┌──────────────────┐     ┌─────────────────┐
│   Browser /      │     │   Web Bridge      │     │   ROS2 Nodes    │
│   Dashboard      │◄───►│   (FastAPI)        │◄───►│   (DDS network) │
│   (user network) │:443 │   eth0: user net   │     │   (robot VLAN)  │
│                  │     │   eth1: robot net  │     │                 │
└─────────────────┘     └──────────────────┘     └─────────────────┘

• Web 桥接有两个网络接口：一个面向用户（nginx TLS），另一个面向机器人 DDS 网络。
• ROS2 DDS 发现通过 ROS_DOMAIN_ID 和 DDS 网络接口配置限制在机器人 VLAN 内。
• Web 桥接负责转换和过滤，绝不转发原始 DDS 流量。

通过 REST 管理 ROS2 参数

# parameter_api.py — Full CRUD for ROS2 parameters via HTTP

from fastapi import APIRouter, HTTPException, WebSocket, WebSocketDisconnect
from pydantic import BaseModel
from typing import Any
import asyncio

router = APIRouter(prefix="/api/params", tags=["parameters"])


class ParamUpdate(BaseModel):
    value: Any


@router.get("/")
async def list_parameters():
    """List all declared parameters on the bridge node."""
    ros_node = app.state.ros_node
    param_names = ros_node.get_parameters_by_prefix("")
    return {
        "parameters": [
            {"name": name, "value": param.value}
            for name, param in param_names.items()
        ]
    }


@router.get("/{name}")
async def get_param(name: str):
    """Get a single parameter value."""
    ros_node = app.state.ros_node
    try:
        param = ros_node.get_parameter(name)
        return {"name": name, "value": param.value, "type": str(param.type_)}
    except Exception:
        raise HTTPException(404, f"Parameter '{name}' not found")


@router.put("/{name}")
async def set_param(name: str, body: ParamUpdate):
    """Set a parameter value. Notifies WebSocket subscribers."""
    ros_node = app.state.ros_node
    try:
        old_value = ros_node.get_parameter(name).value
        ros_node.set_parameters([
            rclpy.parameter.Parameter(name, value=body.value)
        ])
        # Notify WebSocket subscribers of the change
        await param_broadcaster.notify(name, old_value, body.value)
        return {"name": name, "old_value": old_value, "new_value": body.value}
    except Exception as e:
        raise HTTPException(400, str(e))


# Parameter change notifications via WebSocket
class ParamBroadcaster:
    def __init__(self):
        self.subscribers: set[WebSocket] = set()

    async def notify(self, name: str, old_value: Any, new_value: Any):
        dead = set()
        for ws in self.subscribers.copy():
            try:
                await ws.send_json({
                    "type": "param_change",
                    "name": name,
                    "old_value": old_value,
                    "new_value": new_value,
                })
            except Exception:
                dead.add(ws)
        self.subscribers -= dead

    async def handle_ws(self, websocket: WebSocket):
        await websocket.accept()
        self.subscribers.add(websocket)
        try:
            while True:
                await websocket.receive_text()  # Keep alive
        except WebSocketDisconnect:
            self.subscribers.discard(websocket)


param_broadcaster = ParamBroadcaster()


@router.websocket("/ws")
async def param_ws(websocket: WebSocket):
    """WebSocket endpoint for real-time parameter change notifications."""
    await param_broadcaster.handle_ws(websocket)

Web 集成反模式

1. 在 HTTP 处理程序中阻塞 ROS2 执行器

问题： 在 HTTP 处理程序中调用 rclpy.spin_once() 或 rclpy.spin_until_future_complete() 会阻塞 Web 服务线程；如果 ROS2 执行器已在另一个线程中运行，还可能导致死锁。

解决方法： 在专用后台线程中运行 ROS2 执行器。通过线程安全的共享状态（使用锁保护的属性）访问数据。切勿在请求处理程序中调用 spin 函数。

# BAD: Spinning inside a Flask route
@app.route('/api/scan')
def get_scan():
    rclpy.spin_once(node, timeout_sec=1.0)  # Blocks the web server thread
    return jsonify(node.latest_scan)

# GOOD: Executor spins in background, handler reads shared state
@app.route('/api/scan')
def get_scan():
    return jsonify(node.get_latest_scan())  # Lock-protected read, non-blocking

2. 通过 WebSocket 传输原始图像消息

问题： 通过 WebSocket 发送原始 sensor_msgs/Image 数据（未压缩的 BGR8 格式，640x480 = 每帧 921,600 字节）会浪费带宽，并增加客户端 CPU 负担。Base64 编码会将其膨胀到每帧 1.2MB。

解决方法： 订阅 CompressedImage 话题（JPEG/PNG），或在服务端压缩后再发送。使用二进制 WebSocket 帧，而不是 base64 JSON。

# BAD: Subscribing to raw image and base64-encoding it
self.create_subscription(Image, '/camera/image_raw', self._raw_cb, 10)
# Each frame: 921,600 bytes raw -> 1,228,800 bytes base64 -> JSON overhead

# GOOD: Subscribe to compressed topic, send as binary WebSocket frame
self.create_subscription(
    CompressedImage, '/camera/image/compressed', self._compressed_cb,
    QoSProfile(reliability=ReliabilityPolicy.BEST_EFFORT, depth=1))
# Each frame: ~30,000-80,000 bytes JPEG, sent as binary
await websocket.send_bytes(compressed_image_bytes)

3. 传感器订阅没有速率限制

问题： 以 20Hz 发布、每次扫描包含 100K 个点的 LiDAR 会产生约 8MB/s 的数据。将每条消息转发给每个 WebSocket 客户端会占满网络带宽，并使浏览器不堪重负。

解决方案： 在服务端按客户端进行速率限制。使用令牌桶或简单的基于时间的节流。允许客户端请求所需的速率。

# BAD: Forward every message to every client
def _scan_cb(self, msg):
    for client in self.clients:
        client.send(serialize(msg))  # 20 msgs/s * N clients

# GOOD: Rate-limit per client
def _scan_cb(self, msg):
    with self._lock:
        self._latest_scan = msg  # Just store latest

async def stream_to_client(self, ws, max_hz=5):
    interval = 1.0 / max_hz
    while True:
        scan = self.get_latest_scan()
        if scan:
            await ws.send_json(scan)
        await asyncio.sleep(interval)

4. 在生产环境中运行 rosbridge 却没有身份验证

问题： 使用默认设置的 rosbridge_suite 会向任何 WebSocket 客户端开放所有主题、服务和参数。网络中的任何浏览器都可以向 /cmd_vel 发布消息，或调用 /emergency_stop。

解决方案： 在生产环境中，使用带身份验证的自定义桥接服务。如果必须使用 rosbridge，请启用 rosauth，通过过滤器限制主题，并在经过身份验证的反向代理后运行。

# BAD: Default rosbridge launch — full access to everything
ros2 launch rosbridge_server rosbridge_websocket_launch.xml

# GOOD: At minimum, enable authentication and use a reverse proxy
ros2 launch rosbridge_server rosbridge_websocket_launch.xml \
    authenticate:=true \
    topics_glob:="['/camera/image/compressed', '/odom', '/cmd_vel']"

5. 在异步处理程序中进行同步服务调用

问题： 在 FastAPI 的 async def 处理程序中调用 service_client.call(request)（同步调用），会阻塞事件循环，直到服务返回之前，所有其他请求都会冻结。

解决方案： 使用 call_async()，并通过 asyncio.get_event_loop().run_in_executor() 等待 future，或使用专用线程池。

# BAD: Synchronous service call blocks the async event loop
@app.post("/api/navigate")
async def navigate(goal: NavGoal):
    response = nav_client.call(goal_request)  # Blocks entire event loop
    return {"result": response.result}

# GOOD: Async service call with executor bridge
@app.post("/api/navigate")
async def navigate(goal: NavGoal):
    future = nav_client.call_async(goal_request)
    response = await asyncio.get_event_loop().run_in_executor(
        None, lambda: future.result(timeout=30.0)
    )
    return {"result": response.result}

6. Web 服务器与 ROS2 Spinner 之间的 GIL 争用

问题： 使用多个工作线程运行 uvicorn，并在另一个线程中运行 rclpy.spin，会导致 GIL 争用。在高负载下，Web 服务器和 ROS2 回调会相互阻塞，导致消息丢失并增加延迟。

解决方案： 使用线程数较少（2-4）的 MultiThreadedExecutor。对于高吞吐量系统，在单独的进程中运行 ROS2 节点，并通过共享内存、Redis 或 Unix 套接字进行通信。

# BAD: SingleThreadedExecutor competing with uvicorn for the GIL
executor = SingleThreadedExecutor()
executor.add_node(node)
threading.Thread(target=executor.spin).start()
uvicorn.run(app, workers=4)  # 4 workers + 1 spinner = GIL contention

# GOOD: MultiThreadedExecutor with limited threads, single uvicorn worker
executor = MultiThreadedExecutor(num_threads=2)
executor.add_node(node)
threading.Thread(target=executor.spin, daemon=True).start()
uvicorn.run(app, workers=1, host="0.0.0.0", port=8080)

7. 未管理连接生命周期

问题： WebSocket 客户端可能在未发送关闭帧的情况下断开连接（例如关闭浏览器标签页或网络中断）。服务器仍会向失效连接发送数据，浪费 CPU 和内存。随着时间推移，失效客户端集合会无限增长。

解决方案： 使用集合跟踪已连接的客户端，在断开连接时将其移除，并定期通过心跳检查清理失效连接。

# BAD: No tracking of client lifecycle
clients = []

@app.websocket("/ws/data")
async def data_ws(ws: WebSocket):
    await ws.accept()
    clients.append(ws)
    while True:
        await ws.send_json(get_data())  # Throws on dead client, never removed

# GOOD: Proper lifecycle management with cleanup
clients: set[WebSocket] = set()

@app.websocket("/ws/data")
async def data_ws(ws: WebSocket):
    await ws.accept()
    clients.add(ws)
    try:
        while True:
            # Wait for client messages (ping/pong keepalive)
            await ws.receive_text()
    except WebSocketDisconnect:
        pass
    finally:
        clients.discard(ws)

async def broadcast(data: dict):
    dead = set()
    for client in clients.copy():
        try:
            await client.send_json(data)
        except Exception:
            dead.add(client)
    clients -= dead

8. 无条件公开所有主题

问题： Web 桥接服务会订阅 ROS2 图中的每个主题，并向 Web 客户端开放所有主题。这会泄露内部系统细节（诊断信息、调试主题），浪费带宽并造成安全风险。

解决方案： 明确维护需要公开的主题允许列表。从配置中加载该列表。拒绝对列表中不存在的主题的请求。

# BAD: Dynamically subscribe to whatever the client requests
@app.websocket("/ws/topic/{topic_name}")
async def any_topic(ws: WebSocket, topic_name: str):
    # Client can request /rosout, /parameter_events, /diagnostics, etc.
    sub = node.create_subscription(String, topic_name, callback, 10)

# GOOD: Allowlist of exposed topics from configuration
ALLOWED_TOPICS = {
    "/camera/image/compressed": CompressedImage,
    "/odom": Odometry,
    "/battery_state": BatteryState,
    "/cmd_vel": Twist,
}

@app.websocket("/ws/topic/{topic_name:path}")
async def allowed_topic(ws: WebSocket, topic_name: str):
    topic_path = "/" + topic_name
    if topic_path not in ALLOWED_TOPICS:
        await ws.close(code=4004, reason=f"Topic '{topic_path}' not in allowlist")
        return
    msg_type = ALLOWED_TOPICS[topic_path]
    # Proceed with subscription

Web 集成检查清单

1. 线程隔离：rclpy 执行器在专用后台线程中运行；Web 服务器在主线程或自己的线程中运行。它们绝不共用事件循环。
2. 共享状态受锁保护：HTTP 处理程序读取、ROS2 回调写入的每项数据都由 threading.Lock() 保护。跨线程访问时不得直接读取或写入属性。
3. 协调实现平稳关停：信号处理程序设置关停事件，在调用 rclpy.shutdown() 之前停止执行器，并在加入 spin 线程时设置超时。
4. 强制执行主题允许列表：仅向 Web 客户端公开明确列出的主题。允许列表从配置文件加载，不得硬编码。
5. 限制所有数据流的速率：每个 WebSocket 数据流都设有针对单个客户端的速率限制器（令牌桶或基于时间的限制器）。客户端可以请求更低的速率，但不能超过服务器的上限。
6. 命令超时监控：任何接受速度或运动命令的端点，如果在 500ms 内未收到命令，都会发布零速度，以防机器人在断开连接后失控。
7. 传输前压缩视频：摄像头画面使用 CompressedImage 主题或由服务器进行 JPEG 编码。绝不向 Web 客户端转发原始 Image 消息。
8. 在桥接服务前终止 TLS：使用 nginx 或 caddy 反向代理处理 TLS。桥接服务本身仅监听 localhost。正确代理 WebSocket 升级请求头。
9. 对所有变更端点进行身份验证：POST、PUT、DELETE 端点和遥操作 WebSocket 连接都需要有效的 JWT 或 API 密钥。在专用网络上，只读状态端点可以不进行身份验证。
10. CORS 限制来源：allow_origins 列出特定的仪表板 URL。生产环境中绝不使用通配符 *。
11. 管理连接生命周期：在一个集合中跟踪 WebSocket 客户端，断开连接时将其移除，并定期清理。绝不保留失效的客户端引用。
12. 高带宽数据使用二进制 WebSocket：图像帧、点云和其他二进制数据使用 send_bytes()，而非经过 base64 编码的 JSON。这样可以为两端节省约 33% 的带宽和 CPU。