AI-Drone-Routing 🚁

🤖 This Prolog project was created as part of an AI course assignment.
It solves delivery drone routing problems using uninformed and informed search strategies.

📁 Files

• drone_routing.pl: The Prolog solution for both problems (uninformed and informed search).
• AI - Assignment 2 [Spring 2025].pdf: The official assignment description provided by the course.

📄 View Assignment Description

🧠 Problems Solved

Problem 1: Uninformed Search (DFS / BFS)

• A drone starts at the top-left corner of a grid.
• It needs to visit as many delivery points (P) as possible while avoiding obstacles (O).
• Implemented using DFS or BFS.

Bonus: Visual representation of the grid before and after pathfinding.

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Problem 2: Informed Search (A*)

• The drone must visit all delivery points while minimizing total cost.
• Implemented using A* with a heuristic function.
• Path must be the shortest possible to complete all deliveries.

Bonus:

• Energy constraint (e.g., 6 moves max before recharging).
• Recharge station (R) refills the battery.
• Modified A* includes energy logic.

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🚀 How to Run

1. Open SWI-Prolog or any compatible Prolog interpreter.
2. Load the file:

?- consult('drone_routing').

👥 Team Members

• Israa Mohamed
• Amany Mohamed
• Salma Mohamed
• Rana Ibrahim