Ming Start Robotics Skills Ros2 Web Integration

When to Use This Skill

• Building a web dashboard to monitor or control a robot running ROS2
• Streaming camera feeds (MJPEG, WebRTC, compressed WebSocket) from a robot to a browser
• Exposing ROS2 services and actions as REST API endpoints
• Implementing bidirectional WebSocket communication between a web UI and ROS2 nodes
• Setting up rosbridge_suite for quick prototyping or foxglove integration
• Writing a custom FastAPI or Flask bridge to ROS2 for production deployments
• Adding authentication, rate limiting, or CORS to robot web interfaces
• Running an async web server (uvicorn) alongside the rclpy executor without deadlocks
• Publishing teleop commands from a browser joystick to cmd_vel
• Serving ROS2 parameter configuration pages or diagnostic dashboards over HTTP

Architecture Overview

Comparison Table

When to Use rosbridge vs Custom Bridge

Use rosbridge_suite when:

• You need a working bridge in under 10 minutes
• The client is foxglove, webviz, or another rosbridge-aware tool
• Security is not a concern (local network, demo environment)
• You do not need custom business logic between web and ROS2

Use a custom bridge (FastAPI/Flask) when:

• You need authentication, authorization, or rate limiting
• You want to expose only specific topics/services (not the entire ROS2 graph)
• You need to transform or aggregate data before sending to the client
• You need REST endpoints for integration with non-WebSocket clients
• You are streaming video and need control over encoding and quality
• The system is deployed in production or on a public network

Pattern 1: rosbridge_suite

Installation and Launch

# 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 Client (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
}

Limitations and Performance

• JSON serialization overhead: All messages are serialized to JSON, including binary data (base64-encoded). A 640x480 JPEG compressed image becomes ~30% larger over the wire.
• No topic filtering: By default rosbridge exposes every topic, service, and action on the ROS2 graph. Any connected client can publish to /cmd_vel.
• Single-threaded event loop: rosbridge_server uses a single Tornado event loop. High-frequency subscriptions from multiple clients can starve the loop.
• No built-in rate limiting: Clients can subscribe at any rate. A misbehaving client subscribing to a 30Hz point cloud will consume the server.
• Authentication is minimal: rosauth uses MAC-based tokens with shared secrets. It does not support JWT, OAuth2, or role-based access.

Pattern 2: Custom FastAPI Bridge

Project Structure

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

ROS2 Node with Async Executor

# 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)

FastAPI App with ROS2 Integration

# 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

WebSocket Endpoint for Streaming

# 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

REST Endpoints Wrapping ROS2 Services

# 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}

Running FastAPI + rclpy Together

This is the critical integration point. Uvicorn runs in the main thread, rclpy spins in a background thread, and shutdown is coordinated via signals.

# 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()

Pattern 3: Flask Bridge

Flask with rclpy Threading

Flask is synchronous. Running rclpy.spin() on the same thread as Flask will block one or the other. The correct approach uses a background thread for the ROS2 executor.

# 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()

When Flask Is Enough vs When You Need FastAPI

Use Flask when:

• You only need simple REST endpoints (no WebSocket)
• The web bridge is an internal tool with few concurrent users
• Your team is already familiar with Flask and not ready to adopt async
• You do not need OpenAPI/Swagger documentation auto-generation

Use FastAPI when:

• You need WebSocket endpoints for real-time streaming
• You need high concurrency (async handlers, many simultaneous clients)
• You want automatic request validation via Pydantic models
• You want auto-generated OpenAPI docs for the robot API
• You are streaming video or sensor data to multiple clients

Video Streaming Patterns

MJPEG Streaming

MJPEG streams work in <img> tags natively with no JavaScript needed. Useful for simple dashboards.

# 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"
    )

Browser usage — no JavaScript required:

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

WebRTC via webrtc_ros

For low-latency, high-quality video streaming, use the webrtc_ros package.

# 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'),
            ],
        ),
    ])

Compressed Topic Streaming via WebSocket

For a balance between simplicity and performance, stream compressed image topics over a binary WebSocket.

# 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

Client-side 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;
};

Bidirectional Communication

Web UI to Robot Commands

# 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)

Robot Status to 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)

Command Acknowledgment Pattern

For reliable command execution, use a request-response pattern over WebSocket with correlation IDs.

# 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

Rate Limiting and Backpressure

Server-Side Rate Limiting

# 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()

Client-Driven Backpressure

Let clients request their own rate to match their processing capability.

@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

Adaptive Quality Reduction

Reduce image quality when bandwidth or client processing cannot keep up.

# 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)

Security

TLS/HTTPS with Nginx Reverse Proxy

Never expose the robot web bridge directly to untrusted networks. Use nginx as a TLS-terminating reverse proxy.

# /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;
    }
}

Token-Based Auth (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 Configuration

# 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"],
)

Network Segmentation

Robots should run on isolated networks. The web bridge is the only component with interfaces on both the robot network and the user-facing network.

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

• The web bridge has two network interfaces: one facing users (nginx TLS), one facing the robot DDS network.
• ROS2 DDS discovery is confined to the robot VLAN via ROS_DOMAIN_ID and DDS network interface configuration.
• The web bridge translates and filters — never forwards raw DDS traffic.

ROS2 Parameter Management via REST

# 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 Integration Anti-Patterns

1. Blocking the ROS2 Executor from HTTP Handlers

Problem: Calling rclpy.spin_once() or rclpy.spin_until_future_complete() inside an HTTP handler blocks the web server thread and can deadlock if the ROS2 executor is already spinning in another thread.

Fix: Spin the ROS2 executor in a dedicated background thread. Access data via thread-safe shared state (lock-protected attributes). Never call spin functions from request handlers.

# 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. Streaming Raw Image Messages Over WebSocket

Problem: Sending raw sensor_msgs/Image data (uncompressed BGR8, 6

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