Improving Control Performance of Tilt-Rotor VTOL UAV with Model-Based Reward and Multi-Agent Reinforcement Learning

Tilt-rotor Vertical Takeoff and Landing Unmanned Aerial Vehicles (TR-VTOL UAVs) combine fixed-wing and rotary-wing configurations, offering optimized flight planning but presenting challenges due to their complex dynamics and uncertainties. This study investigates a multi-agent reinforcement learnin...

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Bibliographic Details

Published in:	Aerospace
Main Authors:	Muammer Ugur, Aydin Yesildirek
Format:	Article
Language:	English
Published:	MDPI AG 2025-09-01
Subjects:	tilt-rotor UAV reinforcement learning soft actor-critic algorithm multi-agent RL dynamic reference-based reward mechanism
Online Access:	https://www.mdpi.com/2226-4310/12/9/814