Artificial Intelligence Planning for AUV Mission Control

Michael Cashmore; Maria Fox; Derek Long; Daniele Magazzeni; Bram Ridder

doi:10.1016/j.ifacol.2015.06.043

Artificial Intelligence Planning for AUV Mission Control

Michael Cashmore, Maria Fox, Derek Long, Daniele Magazzeni, Bram Ridder

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

5 Citations (Scopus)

Abstract

Autonomous intelligent robotic systems are becoming increasingly important in a wide range of applications. Many of these application contexts are in physical situations out of human reach, so that a robot, or team of robots, must be capable of operating for long periods without human intervention. This requires a strategic planning capability as well as an ability to interpret and adapt to unexpected events. In this paper we describe progress towards developing such a capability in the context of underwater oilfield operations.

Original language	English
Title of host publication	IFAC Proceedings Volumes (IFAC-PapersOnline)
Publisher	IFAC Secretariat
Pages	262-267
Number of pages	6
Volume	48
Edition	2
DOIs	https://doi.org/10.1016/j.ifacol.2015.06.043
Publication status	E-pub ahead of print - 2 Sept 2015
Event	4th IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2015 - Girona, Spain Duration: 28 Apr 2015 → 30 Apr 2015

Conference

Conference	4th IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2015
Country/Territory	Spain
City	Girona
Period	28/04/2015 → 30/04/2015

Keywords

Artificial intelligence
Automatic control systems
Autonomous vehicles
Intelligent knowledge-based systems
Persistent autonomy
Planning
Time schedule control

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10.1016/j.ifacol.2015.06.043

Cite this

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title = "Artificial Intelligence Planning for AUV Mission Control",

abstract = "Autonomous intelligent robotic systems are becoming increasingly important in a wide range of applications. Many of these application contexts are in physical situations out of human reach, so that a robot, or team of robots, must be capable of operating for long periods without human intervention. This requires a strategic planning capability as well as an ability to interpret and adapt to unexpected events. In this paper we describe progress towards developing such a capability in the context of underwater oilfield operations.",

keywords = "Artificial intelligence, Automatic control systems, Autonomous vehicles, Intelligent knowledge-based systems, Persistent autonomy, Planning, Time schedule control",

author = "Michael Cashmore and Maria Fox and Derek Long and Daniele Magazzeni and Bram Ridder",

year = "2015",

month = sep,

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doi = "10.1016/j.ifacol.2015.06.043",

language = "English",

volume = "48",

pages = "262--267",

booktitle = "IFAC Proceedings Volumes (IFAC-PapersOnline)",

publisher = "IFAC Secretariat",

edition = "2",

note = "4th IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2015 ; Conference date: 28-04-2015 Through 30-04-2015",

}

Cashmore, M , Fox, M , Long, D , Magazzeni, D & Ridder, B 2015, Artificial Intelligence Planning for AUV Mission Control. in IFAC Proceedings Volumes (IFAC-PapersOnline). 2 edn, vol. 48, IFAC Secretariat, pp. 262-267, 4th IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2015, Girona, Spain, 28/04/2015. https://doi.org/10.1016/j.ifacol.2015.06.043

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AU - Cashmore, Michael

AU - Fox, Maria

AU - Long, Derek

AU - Magazzeni, Daniele

AU - Ridder, Bram

PY - 2015/9/2

Y1 - 2015/9/2

N2 - Autonomous intelligent robotic systems are becoming increasingly important in a wide range of applications. Many of these application contexts are in physical situations out of human reach, so that a robot, or team of robots, must be capable of operating for long periods without human intervention. This requires a strategic planning capability as well as an ability to interpret and adapt to unexpected events. In this paper we describe progress towards developing such a capability in the context of underwater oilfield operations.

AB - Autonomous intelligent robotic systems are becoming increasingly important in a wide range of applications. Many of these application contexts are in physical situations out of human reach, so that a robot, or team of robots, must be capable of operating for long periods without human intervention. This requires a strategic planning capability as well as an ability to interpret and adapt to unexpected events. In this paper we describe progress towards developing such a capability in the context of underwater oilfield operations.

KW - Artificial intelligence

KW - Automatic control systems

KW - Autonomous vehicles

KW - Intelligent knowledge-based systems

KW - Persistent autonomy

KW - Planning

KW - Time schedule control

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U2 - 10.1016/j.ifacol.2015.06.043

DO - 10.1016/j.ifacol.2015.06.043

M3 - Conference paper

VL - 48

SP - 262

EP - 267

BT - IFAC Proceedings Volumes (IFAC-PapersOnline)

PB - IFAC Secretariat

T2 - 4th IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2015

Y2 - 28 April 2015 through 30 April 2015

ER -

Artificial Intelligence Planning for AUV Mission Control

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