Ros2 Web Integration

ROS2 Web Integration Skill

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

| Feature | rosbridgesuite | Custom FastAPI Bridge | Custom Flask Bridge | |---|---|---|---| | Latency | ~5-15ms (WebSocket) | ~2-5ms (WebSocket), ~10-30ms (REST) | ~10-50ms (REST only without extensions) | | Throughput | Medium (JSON serialization overhead) | High (binary WebSocket, async) | Low-Medium (sync, GIL-bound) | | Auth | Basic (rosauth, limited) | Full (JWT, OAuth2, API keys) | Full (Flask-Login, JWT) | | Complexity | Low (launch and connect) | Medium (must manage two event loops) | Medium (must manage threading) | | Video Streaming | Requires separate webvideo_server | Native (MJPEG, WebSocket binary) | MJPEG via generator responses | | Production Ready | No (exposes full topic graph) | Yes | Yes (with gunicorn) | | When to Use | Prototyping, foxglove, quick demos | Production APIs, high-perf streaming | Simple internal tools, legacy systems |

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 }
    """
    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 concur

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: arpitg1304
• Source: arpitg1304/robotics-agent-skills
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.