Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.673831
Title: An advanced obstacle avoidance system for autonomous maritime vehicles
Author: Oliveira Henrique, Sable Campbell de
ISNI:       0000 0004 5369 6582
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2014
Availability of Full Text:
Full text unavailable from EThOS.
Please contact the current institution’s library for further details.
Abstract:
Present-day levels of marine traffic pose a challenge to navigators to avoid vessels safely and efficiently. Unfortunately, despite technological advancements, maritime collisions still occur frequently due to human error. Likewise, deficiencies with unmanned surface vessels (USVs) involve their inability to automatically avoid traffic in a safe manner, complying with the international Regulations for Preventing Collisions at Sea 1972 (COLREGs). This thesis presents an USV obstacle avoidance framework, with holistic considerations of the navigation, guidance and control (NGC) system, as well as synthesis with an obstacle detection subsystem. The primary focus is a real-time path planning system, which incorporates COLREGs. Notable attempts on this topic to date adopt approaches such as evolutionary methods, artificial potential fields (APFs) and multi-objective optimisation strategies, for which prevalent limitations include lack of real-time capabilities, excessive computational effort, the compromise of safety in favour of optimality and failure to consider vessel dynamics.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.673831  DOI: Not available
Share: