UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Intelligent Multi-Task Allocation and Planning for Multiple Unmanned Surface Vehicles (USVs) Using Self-Organising Maps and Fast Marching Method

Liu, Y; Song, R; Bucknall, R; Xinyu, Z; (2019) Intelligent Multi-Task Allocation and Planning for Multiple Unmanned Surface Vehicles (USVs) Using Self-Organising Maps and Fast Marching Method. Information Sciences , 496 pp. 180-197. 10.1016/j.ins.2019.05.029. Green open access

[thumbnail of Intelligent Multi-Task Allocation and Planning for Multiple Unmanned Surface Vehicles (USVs) Using Self-Organising Maps and Fast Marching Method.pdf]
Preview
Text
Intelligent Multi-Task Allocation and Planning for Multiple Unmanned Surface Vehicles (USVs) Using Self-Organising Maps and Fast Marching Method.pdf - Accepted Version

Download (1MB) | Preview

Abstract

As a result of the advances in autonomous navigation technology, ocean based operations with increasing levels of complexity can be undertaken using unmanned surface vehicles (USVs). Presently, the trend of developing USVs is to use multiple USVs as a fleet to carry out single or multiple tasks in a cooperative and coordinated manner. To further support such a deployment, a new intelligent multi-task allocation and path planning algorithm has been proposed in this paper based upon the self-organising map (SOM) and the fast marching method (FMM). To specifically address the two critical issues of energy consumption and communication range, a novel energy coordination scheme as well as a task prioritising method have been proposed to efficiently assign tasks to a multi-USV system. The algorithm has been verified and validated through a number of computer-based simulations and has been proven to work effectively in both simulated and practical maritime environments.

Type: Article
Title: Intelligent Multi-Task Allocation and Planning for Multiple Unmanned Surface Vehicles (USVs) Using Self-Organising Maps and Fast Marching Method
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.ins.2019.05.029
Publisher version: https://doi.org/10.1016/j.ins.2019.05.029
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Unmanned surface vehicle (USV)Task allocationPath planningMulti-vehicle system
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10073676
Downloads since deposit
541Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item