🤖 DFA Controlled Robot Navigator v2

A visual simulation of a robot navigating a 5x5 grid based on a Deterministic Finite Automaton (DFA). The robot follows a sequence of directions (U, D, L, R) and uses a DFA transition table to determine whether it reaches an accept state (goal cell).

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Features

• Customizable start and accept states
• DFA logic implementation with transition loopbacks for invalid moves
• Reads DFA Transition Table from Excel (.xlsx)
• Graphical output of state transitions
• Built-in testing module (test_dfa.py)

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🗂 Project Structure

dfa_robot_navigatorv2/
├── dfa.py                  # Core DFA logic
├── dfa_graph.py            # Visualization of the DFA
├── main.py                 # Entry point and controller logic
├── test_dfa.py             # Unit tests
├── DFA_Transition_Table.xlsx  # Excel file for DFA transitions
├── requirements.txt        # Dependencies
├── Output Graph/           # Stores visualized output images
├── my_robot.jpg            # (Optional) Robot illustration
└── README.md               # This file

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Installation

1. Clone the repository:

git clone https://github.com/yourusername/dfa_robot_navigatorv2.git
cd dfa_robot_navigatorv2

2. Create a virtual environment (optional but recommended):

python -m venv venv
venv\Scripts\activate     # On Windows

3. Install dependencies:

pip install -r requirements.txt

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Running the Simulation

python main.py

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📸 Preview

Grid View	DFA Graph

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Future Enhancements

• Real-time robot animation
• GUI using Tkinter or PyQt
• Import/export DFA configurations
• DFA minimization options

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Author

Clay Mark Sarte
Passionate about AI, robotics, and software that makes machines think.

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📄 License

This project is licensed under the MIT License.