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
Harris, Catherine A.
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Phillips, Alexander B.
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Dopico Gonzalez, Carolina
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Brito, Mario P.
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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.
.
(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
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
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Date deposited: 28 Sep 2016 08:45
Last modified: 15 Mar 2024 05:55
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Contributors
Author:
Catherine A. Harris
Author:
Alexander B. Phillips
Author:
Carolina Dopico Gonzalez
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