Development of a Landing Period Indicator and the Use of Signal Prediction to Improve Landing Methodologies of Autonomous Unmanned Aerial Vehicles on Maritime Vessels

The scope of this thesis is the creation and evaluation of a methodology for improving the overall landing performance for UAVs using signal prediction and a developed Landing Period Indicator (LPI). The research is conducted in a synthetic environment, where the test vehicle is a quad-rotor UAV that is equipped with a light detection and ranging system to aerially detect ship motion. The observed ship motion is forecasted using signal prediction which identifies and notifies the UAV of potential landing opportunities. The Signal Prediction Algorithm (SPA) is also used for Active Heave Compensation (AHC) to facilitate the UAV in maintaining a safe low hover position above the ship deck. Further, an algorithm is developed to use the AHC system to plan trajectories that land the UAV with a specified impact velocity. The results in this thesis indicate that the developed landing methodologies can improve the landing performance of ocean-going helicopters.

Name thesis:degree_name

Master of Applied Science (M.App.Sc.)

Level thesis:degree_level

Master's

Discipline thesis:degree_discipline

Engineering, Mechanical

Grantor dc:publisher

Carleton University

Year dc:date.issued

2019

Author dc:creator

• Abujoub, Shadi

Statement dc:rights

• Copyright © 2019 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2019-13764

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/40319