AMR-SIM is an AI-powered simulation tool for planning and testing Autonomous Mobile Robot (AMR) systems in warehouse environments. It helps pre-sales engineers and warehouse planners simulate different scenarios to meet specific throughput goals, robot types, and layout configurations.
🚧 This project is still in progress — currently focused on building core features like throughput configuration, dynamic map layout, and algorithm selection.
- Frontend: React.js, TypeScript, Tailwind CSS
- Backend: Python, FastAPI
- Database & Tools: Google Sheets API, PostgreSQL (planned), Docker
- AI & Analysis (Upcoming): NumPy, pandas, scikit-learn, HuggingFace, LangChain
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Google Sheets Integration
- Users can input desired throughput, number of robots, and other warehouse configurations.
- Data is synced with the front-end UI for real-time updates.
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Custom Map Creation
- Define robot positions, stations, shelves, chargers, and high-traffic zones.
- Interactive grid-based layout using data from the spreadsheet.
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Algorithm Selection Interface
- Choose from multiple planning algorithms like A*, Dijkstra, Genetic, ACO, DWA.
- Hover tooltips explain advantages and drawbacks of each method.
- Order simulation using Geek+ Picking System API standard (v3.4.2)
- AI-powered chatbot assistant for system guidance and Q&A
- Visualization dashboard with heatmaps and performance insights
- Full simulation environment with robot coordination logic
- Web app login & spreadsheet sync for multiple users
# Clone the repo
git clone https://github.com/Jung028/AMR-SIM.git
cd AMR-SIM
# Install backend dependencies
cd backend
pip install -r requirements.txt
# Install frontend dependencies
cd ../frontend
npm install
npm run dev