ROS & LLM Integration Bridge
Enables large language models to interact with ROS robots seamlessly, allowing natural language control, real-time sensor monitoring, and autonomous task execution without modifying existing robot code.
README
<h1 align="center">🤖 ROS & LLM Integration Bridge 🧠</h1>
<div align="center">
Empowering robots with Large Language Models for seamless, bidirectional communication.[cite: 1]
</div>
<p align="center"> <img src="https://github.com/Ankit-Paliwal/MCP-SERVER-FOR-ROS/blob/main/docs/images/framework.png" alt="Framework Overview"/> </p>
✨ Why Choose This Bridge?
- 🚫 Zero Modifications Required: Easily integrate the
rosbridgenode without altering your existing robot source code.[cite: 1] - 🔄 True Bidirectional Interaction: LLMs can both control the robot's actions and monitor its environment in real-time.[cite: 1]
- 🧠 Comprehensive Context Awareness: Gain full access to publish/subscribe topics, service calls, action executions, sensor readings, and parameter tuning.[cite: 1]
- 🔍 Intelligent Discovery: The system automatically guides the AI to understand available ROS topics, custom types, and services, ensuring flawless syntax execution.[cite: 1]
- 🌐 Universal Client Support: Built on the open MCP standard, making it fully compatible with Claude, Gemini, ChatGPT, Cursor, and Codex CLI.[cite: 1]
- ⚡ Cross-Version Compatibility: Works flawlessly across ROS 1 and ROS 2 distributions (including Jazzy and Humble).[cite: 1]
🎥 Action Showcases
<p align="center"> <a href="https://youtu.be/Yy1loJAn9sA"> <img src="https://github.com/Ankit-Paliwal/MCP-SERVER-FOR-ROS/blob/main/docs/images/MCP%20Demos%20Slide%20-%207to12s.gif" alt="Demos" width="80%"/> </a> </p>
🏭 1. Industrial Robot Diagnostics
Connects AI agents to production robots using only technical manuals as a reference. The AI autonomously discovers custom topic syntaxes, executes diagnostic tests (like vacuum/gripper tests), identifies anomalies, and reports the root cause.[cite: 1]
<p align="center"> <a href="https://youtu.be/EhZNFULz9P4"> <img src="https://github.com/Ankit-Paliwal/MCP-SERVER-FOR-ROS/blob/main/docs/images/ROS%20MCP%20Gripper%20vacuum%20test.jpg" width="400" alt="Industrial Robot Test" /> </a> </p>
🗣️ 2. Natural Language Mobile Navigation
Command your mobile robots with simple phrases like, "Grab a Coke from the fridge & go to the living room." The AI utilizes Nav2 (SLAM) for mapping/navigation and MoveIt for manipulation, operating entirely autonomously.[cite: 1]
<p align="center"> <img src="https://github.com/Ankit-Paliwal/MCP-SERVER-FOR-ROS/blob/main/docs/images/Wilson%20thumbnail.jpg" width="400" alt="Mobile Robot Control" /> </p>
🐕 3. Simulated Quadruped Control (NVIDIA Isaac Sim)
Interpret natural language commands to navigate and control quadruped robots directly within the NVIDIA Isaac Sim environment.[cite: 1]
<p align="center"> <a href="https://www.youtube.com/watch?v=9StFx4lnvmc"> <img src="https://img.youtube.com/vi/9StFx4lnvmc/maxresdefault.jpg" width="400" alt="Quadruped Simulation" /> </a> </p>
🚀 Getting Started
To start integrating LLMs with your ROS setup, please refer to our Installation Guide.[cite: 1]
This tool is ready to be paired with any MCP-compatible client, including Claude Desktop, Gemini CLI, ChatGPT, and Cursor.[cite: 1]
<p align="center"> <img src="https://github.com/Ankit-Paliwal/MCP-SERVER-FOR-ROS/blob/main/docs/images/MCP_topology.png" alt="Topology Overview"/> </p>
🤝 How to Contribute
We encourage community contributions to make this project even better:
- 🐛 Bug fixes and documentation improvements
- ✨ New features (e.g., advanced permissions, action support)
- 📖 Additional tutorials and real-world examples
Please review our Contributing Guidelines to get started.[cite: 1]
📜 Licensing
This software is released under the Apache License 2.0.[cite: 1]
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