In this project, we study multiple optimisation techniques to tackle the task assignment and path planning problem for multi Unmanned Aerial Vehicles (UAVs).
This problem, abbreviated as MUTAPP problem, is considered an NP-hard problem and can be described as a Multi Travelling Salesman Problem (MTSP).
We encounter solutions such as Simulated Annealing (SA), Genetic Algorithm (GA), Hybrid Ant Colony Optimisation and Whale Optimisation Algorithm (H-ACO-WOA), and Hybrid ACO and Dragonfly Algorithm (H-ACO-DA).
More information and visualisations here.
The path planning part was a simple changing of placement of a mid point in the path just for proofing the concept. An intended future work was to add obstacles for the path planning to avoid.
The codes were written in Python with some OOP concepts. The visualisation was done using Matplotlib.
This project was part of the Metaheuristic Optimization Techniques for Multi-Cooperative Systems course at the German University in Cairo, which is taught by Assist. Prof. Omar Shehata.
This project was developed by: