ros2-web-integration
Patterns and best practices for integrating ROS2 systems with web technologies including REST APIs, WebSocket bridges, and browser-based robot interfaces.
Install / Use
npx skills add arpitg1304/robotics-agent-skills --skill ros2-web-integrationInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of ros2-web-integration
ros2-web-integration scores 83/100 on our quality scale, 3020th of 4,604 Development & Engineering skills we index.
Its SKILL.md is 49 KB long, well organised into 96 sections with 34 code examples: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.
It has 368 GitHub stars, a meaningful sign that others use it.
Maintenance, license and trust
- The repository was last updated about 2 months ago, so ros2-web-integration is actively maintained.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
ros2-web-integration compared with similar skills
All 4 of these similar skills score higher than ros2-web-integration; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| ros2-web-integration (this skill)by arpitg1304 | 83 | 368 | 56d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 92.6k | 21d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.5k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 45.1k | 1d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.8k | 6d ago | CLAUDE.md |
Frequently asked questions
- How do I install ros2-web-integration?
- Run
npx skills add arpitg1304/robotics-agent-skills --skill ros2-web-integration. The install tabs above show the steps for each supported agent. - Which AI agents does ros2-web-integration work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is ros2-web-integration safe to use?
- It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is ros2-web-integration still maintained?
- The repository was last updated about 2 months ago, so ros2-web-integration is actively maintained.
Skill content
View source on GitHubname: ros2-web-integration description: > Patterns and best practices for integrating ROS2 systems with web technologies including REST APIs, WebSocket bridges, and browser-based robot interfaces. Use this skill when building web dashboards for robots, streaming camera feeds to browsers, exposing ROS2 services as REST endpoints, or implementing bidirectional WebSocket communication between web UIs and ROS2 nodes. Trigger whenever the user mentions rosbridge, rosbridge_suite, roslibjs, FastAPI with ROS2, Flask with rclpy, WebSocket for robot telemetry, MJPEG streaming, WebRTC for robots, REST API wrapping ROS2 services, web-based robot control, browser robot interface, robot dashboard, CORS configuration for robots, or any web-to-ROS2 bridge pattern. Also trigger for authentication on robot web interfaces, rate limiting sensor streams, video streaming from robot cameras to browsers, or running async web frameworks alongside the ROS2 executor. Covers rosbridge_suite, FastAPI, Flask, WebSocket, and WebRTC approaches.
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 | rosbridge_suite | 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 web_video_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[byt
Truncated for display — read the full file on GitHub.
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From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
