Optimal Strategies of Autonomous Reconnaissance Missions

Optimal Strategies of Autonomous Reconnaissance Missions

Verlinde, Lander (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Discrete Mathematics and Optimization)

Jurrius, R.P.M.J. (mentor)
de Laat, D. (graduation committee)

Delft University of Technology

Applied Mathematics

2024-01-22

The role of Unmanned Aerial Vehicles (UAVs), more commonly known as drones, in society continues to become more significant every day, both in everyday life and in military operations. The extent to which unmanned vehicles are used for both offensive as well as reconnaissance missions is at an all-time high. To expand the number of operational systems while managing costs, it is desirable to deploy systems that can operate fully independently. For a survey mission, this requires a planning of the complete mission before the drone leaves for enemy territory. The setting of such a mission can be stated as follows: starting from a secure base, multiple surveillance locations need to be safely reached and the acquired information has to be transmitted back to the base. There are many possible strategies for gathering this information. This report investigates how to find the strategy that maximises the expected amount of retrieved information. Specifically, such an optimal strategy tells us which route the UAV should take in enemy territory and at what moments in the mission transmissions should be made. We present a mathematical framework for formulating the problem, as well as a genetic algorithm capable of finding the optimal strategy in different scenarios.

Mission Planning
Genetic programming
Vehicle Routing

http://resolver.tudelft.nl/uuid:c9819e3b-0c02-437f-9c63-8ed84e978032

This report is the result of my three month long internship at the Netherlands Defense Academy as part of the Master Program in Applied Mathematics.

Student theses

student report

© 2024 Lander Verlinde