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Cooperative and Decentralized Decision-Making for Loyal Wingman UAVs

With the application of decision-making techniques, it is possible to automate many of the intelligent decisions of UAVs, leaving human commanders to focus on higher-level decisions in modern warfare scenarios, providing a crucial tactical advantage. This paper applies key methods to enable decentralized decision-making for autonomous combat UAVs, also known as loyal wingman (LW) drones. A simulator was developed to simulate to implement and analyze the behaviors of the so-called LW. We used as the main decision-making technique the construction of a behavior tree (BT) capable of providing decisions in a decentralized manner, and for parameters optimization, the PSO optimization algorithm was used. Our approach shows a promising result of threat elimination efficiency of approximately 93%.