The University of Southampton
University of Southampton Institutional Repository

ASVLite: a high-performance simulator for autonomous surface vehicles

ASVLite: a high-performance simulator for autonomous surface vehicles
ASVLite: a high-performance simulator for autonomous surface vehicles
The energy of ocean waves is the key distinguishing factor of marine environments compared to other aquatic environments such as lakes and rivers. Waves significantly affect the dynamics of marine vehicles; hence it is imperative to consider the dynamics of vehicles in waves when developing efficient control strategies for autonomous surface vehicles (ASVs). However, most marine simulators available open-source either exclude dynamics of vehicles in waves or use methods with high computational overhead. This paper presents ASVLite, a computationally efficient ASV simulator that uses frequency domain analysis for wave force computation. ASVLite is suitable for applications requiring low computational overhead and high run-time performance. Our tests on a Raspberry Pi 2 and a mid-range desktop computer show that the simulator has a high run-time performance to efficiently simulate irregular waves with a component wave count of up to 260 and large-scale swarms of up to 500 ASVs.
2249-2255
Thomas, Toby
74a1d49e-8c13-43ed-afe5-406e92c94f8e
Bossens, David
633a4d28-2e59-4343-98fe-283082ba1873
Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4
Thomas, Toby
74a1d49e-8c13-43ed-afe5-406e92c94f8e
Bossens, David
633a4d28-2e59-4343-98fe-283082ba1873
Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4

Thomas, Toby, Bossens, David and Tarapore, Danesh (2021) ASVLite: a high-performance simulator for autonomous surface vehicles. In 2021 IEEE International Conference on Robotics and Automation (ICRA). pp. 2249-2255 . (doi:10.1109/ICRA48506.2021.9561815).

Record type: Conference or Workshop Item (Paper)

Abstract

The energy of ocean waves is the key distinguishing factor of marine environments compared to other aquatic environments such as lakes and rivers. Waves significantly affect the dynamics of marine vehicles; hence it is imperative to consider the dynamics of vehicles in waves when developing efficient control strategies for autonomous surface vehicles (ASVs). However, most marine simulators available open-source either exclude dynamics of vehicles in waves or use methods with high computational overhead. This paper presents ASVLite, a computationally efficient ASV simulator that uses frequency domain analysis for wave force computation. ASVLite is suitable for applications requiring low computational overhead and high run-time performance. Our tests on a Raspberry Pi 2 and a mid-range desktop computer show that the simulator has a high run-time performance to efficiently simulate irregular waves with a component wave count of up to 260 and large-scale swarms of up to 500 ASVs.

This record has no associated files available for download.

More information

Published date: 2021

Identifiers

Local EPrints ID: 452620
URI: http://eprints.soton.ac.uk/id/eprint/452620
PURE UUID: 2c71b44d-f265-4912-bb62-d7d3b5b02375
ORCID for David Bossens: ORCID iD orcid.org/0000-0003-1924-5756
ORCID for Danesh Tarapore: ORCID iD orcid.org/0000-0002-3226-6861

Catalogue record

Date deposited: 11 Dec 2021 11:29
Last modified: 17 Mar 2024 03:46

Export record

Altmetrics

Contributors

Author: Toby Thomas
Author: David Bossens ORCID iD
Author: Danesh Tarapore ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×