Prompt to Gazebo Sandbox

Live Demo: https://ptg-forge.netlify.app

An AI-powered prompt-to-Gazebo tool that lets users generate complete ROS2/Gazebo simulation environments—including .world, .urdf, and .launch.py files—using natural language prompts. Perfect for rapid robot cell prototyping in manufacturing and robotics engineering.

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Features

• Natural Language Scene Generation: Describe your simulation in plain English
• Prompt-based URDF Creation: Generate URDFs for Fanuc and other robots
• Auto-generation of ROS2 Launch Files: Instantly create .launch.py files
• One-click Export: Download all config files in a ZIP bundle
• Modern Web UI: Real-time generation and preview

Tech Stack

• Frontend: Next.js 15, TypeScript, Tailwind CSS, shadcn/ui
• Backend / Logic: Gemini/genkit for prompt interpretation, file generation templates
• Simulation: ROS2, Gazebo, URDF, RViz (optional)
• Hosting/Deployment: Netlify, Firebase, HuggingFace Spaces

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Setup Instructions

Prerequisites

• Node.js 18+
• npm 9+
• (Optional) ROS2/Gazebo for local simulation

Frontend Setup

git clone https://github.com/cronenberg64/PTG-Forge.git
cd PTG-Forge
npm install
cp env.example .env.local
npm run dev

Environment Variables

Set your environment variables in .env.local:

GOOGLE_AI_API_KEY=your_google_ai_api_key_here
NEXT_PUBLIC_APP_URL=http://localhost:9002

For deployment (e.g., Netlify), set these in your site environment variables.

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Usage

1. Open the web interface at https://ptg-forge.netlify.app or http://localhost:9002
2. Describe your simulation using natural language:

   Simulate two Fanuc LR Mate robots welding on either side of a car chassis inside a 6x6m cell.
   

3. Review the generated files: .world, .urdf, .launch.py, and more
4. Export all files as a ZIP bundle

Example Prompts

• "A factory floor with a Fanuc M-10iA robot arm that picks up a small red cube and places it on a conveyor belt. The simulation should run for 5 cycles."
• "Create a scene with a single robot arm and a conveyor belt."
• "Generate a URDF for a Fanuc M-20iA robot with a gripper."

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Project Structure

PTG-Forge/
├── src/
│   ├── ai/                 # AI integration with Genkit
│   │   ├── flows/         # AI generation flows
│   │   ├── dev.ts         # Development server
│   │   └── genkit.ts      # Genkit configuration
│   ├── app/               # Next.js App Router
│   │   ├── globals.css    # Global styles
│   │   ├── layout.tsx     # Root layout
│   │   └── page.tsx       # Home page
│   ├── components/        # React components
│   │   ├── ptgverse/      # Simulation-specific components
│   │   └── ui/            # shadcn/ui components
│   ├── hooks/             # Custom React hooks
│   └── lib/               # Utility functions
├── docs/                  # Documentation
└── public/                # Static assets

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Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Follow TypeScript best practices
• Write comprehensive tests
• Update documentation for new features
• Ensure ROS2/Gazebo compatibility

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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Acknowledgements

• ROS - Robot Operating System foundation
• Gazebo - Robot simulation environment
• MoveIt - Motion planning framework
• Google Gemini - Natural language processing
• Firebase - Backend infrastructure
• Next.js - React framework
• shadcn/ui - UI component library

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Deploying to Netlify

This project supports static export for easy deployment on Netlify.

Steps:

1. Push your code to GitHub (or GitLab/Bitbucket).
2. Create a new site on Netlify.
3. Connect your repository.
4. Set the build command:

   npm run build && npm run export
   

5. Set the publish directory:

   out
   

6. Add your environment variables (from .env.example) in the Netlify dashboard under Site settings > Environment variables.
7. Deploy!

For advanced SSR/ISR support, see the Netlify Next.js docs.