The University of Southampton
University of Southampton Institutional Repository

Risk and reliability modelling for multi-vehicle marine domains

Risk and reliability modelling for multi-vehicle marine domains
Risk and reliability modelling for multi-vehicle marine domains
It is well-known that autonomous underwater vehicle (AUV) missions are a challenging, high-risk robotics application. With many parallels to Mars rovers, AUV missions involve operating a vehicle in an inherently uncertain environment of which our prior knowledge is often sparse or low-resolution. The lack of an accurate prior, coupled with poor situational awareness and potentially significant sensor noise, presents substantial engineering challenges in navigation, localisation, state estimation and control. When constructing missions and operating AUVs, it is important to consider the risks involved. Stakeholders need to be reassured that risks of vehicle loss or damage have been minimised where possible, and scientists need to be confident that the mission is likely to produce sufficient high-quality data to meet the aims of the deployment. In this paper, we consider the challenges associated with risk analysis methods and representations for multi-vehicle missions, reviewing the relevant literature and proposing a methodology.
286-293
IEEE
Harris, Catherine A.
cceaafa6-e4ea-406e-bece-b4e51513249c
Phillips, Alexander B.
f565b1da-6881-4e2a-8729-c082b869028f
Dopico Gonzalez, Carolina
c6dab806-46fb-4b37-84d6-1232edef3c9d
Brito, Mario P.
82e798e7-e032-4841-992e-81c6f13a9e6c
Harris, Catherine A.
cceaafa6-e4ea-406e-bece-b4e51513249c
Phillips, Alexander B.
f565b1da-6881-4e2a-8729-c082b869028f
Dopico Gonzalez, Carolina
c6dab806-46fb-4b37-84d6-1232edef3c9d
Brito, Mario P.
82e798e7-e032-4841-992e-81c6f13a9e6c

Harris, Catherine A., Phillips, Alexander B., Dopico Gonzalez, Carolina and Brito, Mario P. (2016) Risk and reliability modelling for multi-vehicle marine domains. In 2016 IEEE/OES Autonomous Underwater Vehicles: AUV 2016. IEEE. pp. 286-293 . (doi:10.1109/AUV.2016.7778685).

Record type: Conference or Workshop Item (Paper)

Abstract

It is well-known that autonomous underwater vehicle (AUV) missions are a challenging, high-risk robotics application. With many parallels to Mars rovers, AUV missions involve operating a vehicle in an inherently uncertain environment of which our prior knowledge is often sparse or low-resolution. The lack of an accurate prior, coupled with poor situational awareness and potentially significant sensor noise, presents substantial engineering challenges in navigation, localisation, state estimation and control. When constructing missions and operating AUVs, it is important to consider the risks involved. Stakeholders need to be reassured that risks of vehicle loss or damage have been minimised where possible, and scientists need to be confident that the mission is likely to produce sufficient high-quality data to meet the aims of the deployment. In this paper, we consider the challenges associated with risk analysis methods and representations for multi-vehicle missions, reviewing the relevant literature and proposing a methodology.

Text
PID4441071.pdf - Accepted Manuscript
Download (3MB)

More information

Accepted/In Press date: 6 September 2016
e-pub ahead of print date: 12 December 2016
Venue - Dates: 2016 IEEE/OES Autonomous Underwater Vehicles: AUV 2016, Japan, Japan, 2016-11-06 - 2016-11-09
Organisations: Ocean Technology and Engineering, Southampton Business School

Identifiers

Local EPrints ID: 400831
URI: http://eprints.soton.ac.uk/id/eprint/400831
PURE UUID: 2be20b98-495d-4ecb-87a2-d5fe828b7474
ORCID for Alexander B. Phillips: ORCID iD orcid.org/0000-0003-3234-8506
ORCID for Mario P. Brito: ORCID iD orcid.org/0000-0002-1779-4535

Catalogue record

Date deposited: 28 Sep 2016 08:45
Last modified: 15 Mar 2024 05:55

Export record

Altmetrics

Contributors

Author: Catherine A. Harris
Author: Alexander B. Phillips ORCID iD
Author: Carolina Dopico Gonzalez
Author: Mario P. Brito 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.

×