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A Fuzzy-Based System for Autonomous Unmanned Aerial Vehicle Ship Deck Landing.

Ioannis Tsitses¹, Paraskevi Zacharia¹, Elias Xidias²

¹Department of Industrial Design and Production Engineering, University of West Attica, 12241 Egaleo, Greece.

Sensors (Basel, Switzerland)

|January 26, 2024

Summary

This study presents a fuzzy logic system for autonomous ship deck landings of fixed-wing unmanned aerial vehicles (UAVs). The intelligent system simplifies challenging maritime landings, enhancing operational safety and efficiency.

Keywords:

autonomous ship deck landing fuzzy logic control system unmanned aerial vehicles

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Area of Science:

Aerospace Engineering
Robotics
Artificial Intelligence

Background:

Autonomous ship deck landing for fixed-wing UAVs presents significant challenges in maritime environments.
Current methods require intensive operator control, increasing risk and workload.

Purpose of the Study:

To develop and evaluate a fuzzy logic-based autonomous system for UAV ship deck landings.
To simplify the complex task of landing unmanned aerial vehicles on moving vessels under adverse conditions.

Main Methods:

A fuzzy logic system (FLS) was designed with three interconnected subsystems: speed, lateral motion, and altitude.
The FLS utilizes five inputs (range, relative wind, airspeed, altitude) and outputs UAV velocity, bank angle, and angle of descent.
The system's performance was assessed using MATLAB Fuzzy Toolbox.

Main Results:

The fuzzy logic landing model effectively processes multiple environmental and flight parameters.
The system provides control outputs for speed, bank angle, and angle of descent.
Simulations demonstrated the potential for autonomous landing in challenging maritime scenarios.

Conclusions:

The developed fuzzy logic system offers a viable solution for autonomous UAV ship deck landings.
This intelligent system can reduce operator burden and improve landing safety in complex maritime operations.
Further research can explore real-world implementation and adaptive capabilities for dynamic conditions.