Agent ROS Bridge 🔒
The Safety-First Production Gateway for AI-to-Robot Integration
When robots matter, safety comes first.
Why Us? • Quick Start • Safety First • Comparison • Docs
Why Agent ROS Bridge?
Unlike diagnostic tools (NASA ROSA) or research platforms (ROS-LLM), Agent ROS Bridge is the only production-ready gateway with built-in safety validation.
The Safety Problem
Deploying LLM-controlled robots in production is dangerous:
- AI hallucinations can damage equipment
- Wrong commands can injure humans
- No validation of AI decisions
- No learning from operator corrections
Our Solution
🛡️ Safety-First Architecture:
├── Human-in-the-Loop (enforced by default)
├── Shadow Mode Validation (200+ hours required)
├── Simulation Testing (10K scenarios, 95.93% success)
├── Gradual Rollout (0% → 100% autonomy)
└── Emergency Stop (always available)
Comparison
| Feature | Agent ROS Bridge | NASA ROSA | ROS-LLM |
|---|---|---|---|
| Safety Validation | ✅ Shadow mode | ❌ None | ❌ None |
| Human-in-the-Loop | ✅ Enforced | ⚠️ Optional | ❌ No |
| Production Tests | ✅ 2,021 tests | ❓ Unknown | ❓ Unknown |
| Simulation | ✅ 10K scenarios | ⚠️ Basic | ❌ No |
| Multi-Protocol | ✅ 4 protocols | ❌ CLI only | ❌ ROS2 only |
| Fleet Support | ✅ Multi-robot | ❌ Single | ❌ Single |
| Published Research | 📝 Whitepaper in progress | ✅ arXiv | ✅ Nature |
Quick Start
Installation
pip install agent-ros-bridge
Basic Usage
from agent_ros_bridge import RobotAgent
# Create agent with SAFETY enforced
agent = RobotAgent(
device_id='bot1',
llm_provider='moonshot',
require_confirmation=True, # Human approval required
)
# AI proposes, human approves, robot executes
result = agent.execute("Go to the kitchen")
print(f"Success: {result.success}")
print(f"AI confidence: {result.ai_confidence:.2f}")
print(f"Human approvals: {result.human_approvals}")
Output:
============================================================
🛡️ SAFETY STATUS
============================================================
Device: bot1 (mobile_robot)
Autonomous Mode: False ✅
Human-in-the-Loop: True ✅
Shadow Mode: True ✅
Validation Status: simulation_only
============================================================
🤖 AI Proposal: navigate_to(kitchen)
👤 Human: Approve? (y/n): y
✅ Executed successfully
Safety First
Safe-by-Default Configuration
# config/global_config.yaml
safety:
autonomous_mode: false # Human approval required
human_in_the_loop: true # All AI proposals need approval
shadow_mode_enabled: true # Collect validation data
min_confidence_for_auto: 0.95 # High confidence threshold
gradual_rollout_stage: 0 # Start at 0% autonomy
safety_validation_status: "simulation_only"
required_shadow_hours: 200.0 # Target for validation
min_agreement_rate: 0.95 # Required agreement %
Deployment Stages
Stage 0: Simulation-Only (Current)
├── ✅ 10K scenarios tested
├── ✅ 95.93% success rate
└── ⚠️ No real-world validation yet
Stage 1: Supervised Operation
├── Human approves all actions
├── Shadow mode collects data
└── Target: 200+ hours, >95% agreement
Stage 2: Gradual Rollout
├── 10% → 25% → 50% → 75% → 100%
├── High confidence only
└── Monitor at each stage
Stage 3: Full Autonomy
├── After validation complete
├── Emergency stop always available
└── Continuous monitoring
Architecture
AI Agents ─┬─ WebSocket ─┐
├─ gRPC ──────┼──► ┌─────────────┐
├─ MQTT ──────┤ │ Gateway │
└─ TCP ───────┘ └──────┬──────┘
│
┌────────────────┼────────────────┐
▼ ▼ ▼
┌──────────────┐ ┌──────────────┐ ┌──────────┐
│Safety Layer │ │ Shadow Mode │ │ ROS1/ │
│(Validation) │ │ (Data Coll.) │ │ ROS2 │
└──────────────┘ └──────────────┘ └──────────┘
Key Components
| Component | Purpose | Status |
|---|---|---|
| Gateway | Multi-protocol support | ✅ Stable |
| Safety Layer | Validation & enforcement | ✅ Implemented |
| Shadow Mode | AI-human decision logging | ✅ Active |
| Simulation | 10K scenario testing | ✅ Complete |
| Fleet | Multi-robot orchestration | ✅ Beta |
Features
🛡️ Safety & Validation
- Shadow Mode - Log AI proposals vs human decisions
- Human-in-the-Loop - Enforced by default
- Simulation Testing - 10K scenarios before deployment
- Gradual Rollout - Increase autonomy slowly
- Emergency Stop - Always available
🌐 Multi-Protocol
- WebSocket - Real-time bidirectional
- gRPC - High-performance RPC
- MQTT - IoT messaging
- TCP - Raw socket support
🤖 Universal Support
- Mobile Robots - Navigation, mapping
- Drones - Flight control, aerial missions
- Robot Arms - Manipulation, grasping
- Humanoids - Walking, balancing
- Sensors - Data collection, monitoring
🧠 AI Integration
- Multi-LLM - OpenAI, Moonshot, Anthropic
- Intent Parsing - Natural language understanding
- Context Awareness - Scene understanding
- Multi-Language - English, Chinese, +4 more
Documentation
- Safety Guide - Deployment safety requirements
- Architecture - System design
- API Reference - Complete API docs
- Comparison - vs NASA ROSA vs ROS-LLM
- Changelog - Version history
Web Dashboard
Agent ROS Bridge includes a modern web dashboard for robot control and monitoring.
Features
- 🎮 Robot Control - D-pad interface, natural language commands
- 📊 Real-time Telemetry - Position, velocity, battery, sensors
- 🧠 Shadow Mode Metrics - AI-human agreement tracking
- 🛡️ Safety Status - Validation gates, deployment readiness
- 🚁 Fleet Management - Multi-robot coordination
Quick Start
Option 1: Docker (Recommended)
# Start bridge + web dashboard
docker-compose --profile web up -d
# Access dashboard
open http://localhost:8081
Option 2: Host (Development)
# Start bridge
agent-ros-bridge --websocket-port 8765
# In another terminal, serve dashboard
cd agent_ros_bridge/web
python3 -m http.server 8081
# Access dashboard
open http://localhost:8081
Dashboard URLs
| Dashboard | URL | Purpose |
|---|---|---|
| Control Dashboard | http://localhost:8081 | Robot control + shadow metrics |
| 3D Visualization | http://localhost:8080 | Gazebo/3D view (in ros2_jazzy) |
| Grafana | http://localhost:3000 | System monitoring |
WebSocket Connection
The dashboard connects to the bridge via WebSocket:
- URL:
ws://localhost:8765 - Protocol: JSON messages
- Auth: JWT token (if enabled)
Installation
Prerequisites
- Python 3.11+
- ROS1 (Noetic) or ROS2 (Humble/Jazzy)
- Docker (optional, for simulation)
PyPI Install
pip install agent-ros-bridge
Docker Install
docker pull agent-ros-bridge:jazzy-with-nav2
docker run -it agent-ros-bridge:jazzy-with-nav2
Development Install
git clone https://github.com/webthree549-bot/agent-ros-bridge.git
cd agent-ros-bridge
pip install -e ".[dev]"
Testing
# Run all tests
pytest tests/ -v
# Run with coverage
pytest tests/ --cov=agent_ros_bridge --cov-report=html
# Run safety-critical tests only
pytest tests/unit/safety/ -v
# Run simulation tests (requires Docker)
pytest tests/e2e/ -v
Current Status:
- 2,021 tests passing
- 65% code coverage
- Gate 2 validation: PASSED (95.93% success)
Safety Certification Roadmap
| Milestone | Target | Status |
|---|---|---|
| Shadow Mode Data | 200 hours | 🟡 In Progress (0 hrs) |
| Agreement Rate | >95% | 🟡 In Progress (0%) |
| Simulation Validation | 10K scenarios | ✅ PASSED (95.93%) |
| ISO 10218 Review | Q3 2026 | ⏳ Planned |
| Insurance Review | Q4 2026 | ⏳ Planned |
Community
- ROS Discourse: Announcement Thread
- GitHub Issues: Report Issues
- Documentation: Full Docs
Citation
If you use Agent ROS Bridge in research, please cite:
@software{agent_ros_bridge,
title = {Agent ROS Bridge: Safety-First Production Gateway for AI-to-Robot Integration},
author = {Agent ROS Bridge Contributors},
year = {2026},
url = {https://github.com/webthree549-bot/agent-ros-bridge}
}
License
MIT License - See LICENSE for details.
Built with safety in mind for production robotics deployments.
When robots matter, safety comes first.
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