Autonomous Warehouse Robot Simulator

A comprehensive warehouse robot simulation platform with both 2D and 3D visualization capabilities. This application simulates an autonomous robot navigating a warehouse environment, performing tasks such as picking and placing items, and managing its battery level through charging stations. The simulation provides real-time visualization options and detailed metrics of the robot's performance.

Features

• Warehouse Environment Simulation:

  • Dynamic warehouse setup with configurable dimensions
  • Placement of obstacles, storage racks, items, and charging stations
  • Realistic physical modeling of the environment

• Robot Simulation:

  • Path planning and navigation
  • Task scheduling and execution
  • Battery management
  • Picking and placing operations

• Visualization Options:

  • 2D top-down visualization for basic monitoring
  • 3D web-based visualization for detailed real-time monitoring
  • Performance metrics and statistics dashboard

• Task Management:

  • Automatic task generation
  • Priority-based task scheduling
  • Task completion tracking and metrics

Tech Stack

• Backend:

  • Python 3.x
  • Flask (for the web server and API)
  • Flask-SocketIO (for real-time WebSocket communication)
  • Eventlet (as WebSocket server)

• Frontend 3D Visualization:

  • HTML5/CSS3
  • JavaScript (ES6+)
  • Three.js (for 3D rendering)
  • Socket.IO client (for real-time updates)

• Core Simulation:

  • Custom Python modules for warehouse environment
  • Path planning algorithms
  • Task scheduling logic
  • Robot control logic

Project Structure

autonomous_robot_simulation/
├── config/                # Configuration files and classes
│   ├── default_robot.yaml     # Default robot configuration
│   ├── default_warehouse.yaml # Default warehouse configuration
│   ├── robot_config.py        # Robot configuration loader
│   └── warehouse_config.py    # Warehouse configuration loader
├── dashboard/            # Performance monitoring
│   ├── dashboard.py          # Main dashboard interface
│   └── metrics.py            # Performance metrics calculations
├── environment/          # Simulation environment
│   ├── obstacle.py           # Obstacle class definition
│   └── warehouse.py          # Warehouse environment class
├── planning/             # Planning algorithms
│   ├── path_planner.py       # Path planning algorithms
│   └── task_scheduler.py     # Task scheduling logic
├── robot/                # Robot implementation
│   ├── gripper.py            # Robot gripper mechanism
│   └── robot.py              # Main robot class
├── utils/                # Utility modules
│   └── visualization.py      # 2D visualization utilities
├── vision/               # Perception systems
│   ├── object_classification.py  # Object classification
│   └── object_detection.py       # Object detection
├── web/                  # Web-based 3D visualization
│   ├── static/               # Static web assets
│   │   ├── css/                  # Stylesheets
│   │   │   └── styles.css            # Main CSS file
│   │   └── js/                   # JavaScript files
│   │       ├── robot-model.js        # 3D robot model
│   │       ├── simulation.js         # Simulation controller
│   │       ├── three-setup.js        # Three.js setup
│   │       └── warehouse-model.js    # 3D warehouse model
│   └── templates/            # HTML templates
│       └── index.html            # Main visualization page
├── requirements.txt      # Python dependencies
├── run_simulation.py     # Main simulation runner
├── web_server.py         # Web server for 3D visualization
└── README.md             # This file

Setup and Installation

Prerequisites

• Python 3.7 or higher
• pip (Python package installer)
• A modern web browser (e.g., Chrome, Firefox, Edge)

Installation Steps

1. Download or Clone the Project: If you have this project in a Git repository, clone it:

   git clone <your-repository-url>
   cd warehouse_simulator

   Otherwise, ensure all project files are in a directory named warehouse_simulator.

2. Backend Setup: Navigate to the backend directory and install the required Python packages:

   cd backend
   pip install -r requirements.txt
   cd ..

3. Frontend Setup: No specific build or installation steps are required for the frontend as it uses vanilla HTML, CSS, and JavaScript.

How to Run

You need to run both the backend server and a server for the frontend files.

1. Start the Backend Server: Open a terminal, navigate to the backend directory, and run:

   python app.py

   The backend server will typically start on http://localhost:5000. Keep this terminal window open.

2. Start the Frontend Server: Open a new terminal window, navigate to the frontend directory, and use Python's built-in HTTP server (or any other simple HTTP server):

   python -m http.server 8000

   (You can use any available port instead of 8000).

3. Access the Application: Open your web browser and go to http://localhost:8000 (or the port you used for the frontend server).

API Endpoints (Backend)

The backend exposes the following main API endpoints:

• POST /initialize_warehouse: Initializes the warehouse with given dimensions.
  • Payload: {"width": int, "height": int}
• POST /obstacle: Adds an obstacle.
  • Payload: {"x": int, "y": int} (Note: type can be added if backend supports it)
• DELETE /obstacle: Removes an obstacle.
  • Payload: {"x": int, "y": int}
• POST /plan_path: Calculates the path from a start to an end point.
  • Payload: {"start": {"x": int, "y": int}, "end": {"x": int, "y": int}}

Future Enhancements (Ideas)

• Implement more advanced pathfinding algorithms (e.g., A*).
• Store obstacle types on the backend and allow types to affect pathfinding.
• Add animation for the robot's movement along the path.
• Save and load warehouse layouts.
• Introduce different robot types or capabilities.
• Display more detailed performance metrics (e.g., path length, calculation time).