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Details of Grant 

EPSRC Reference: EP/R026173/1
Title: UK Robotics and Artificial Intelligence Hub for Offshore Energy Asset Integrity Management
Principal Investigator: Petillot, Professor Y
Other Investigators:
Mistry, Professor M Kiprakis, Professor A Hastie, Professor HF
Ramamoorthy, Professor S Flynn, Professor D Patchett, Dr C
Cawley, Professor P Ingram, Professor DM Williams, Professor C
Vijayakumar, Professor S Erden, Dr M Dragone, Dr M
Havoutis, Professor I Kovac, Professor M Hospedales, Professor T
Petrick, Professor R Cegla, Dr F Stokes, Professor A
Jump, Dr M Chantler, Professor M Fisher, Professor M
Robu, Dr V Fallon, Professor M Lohan, Dr K S
Wang, Dr S
Researcher Co-Investigators:
Project Partners:
ABB Group Autonomous Surface Vehicles Ltd (ASV) Baker Hughes (Europe) Ltd
Guided Ultrasonics Ltd Hydrason Solutions Limited Itf, The Industry Technology
Kawasaki Heavy Industries Ltd (Global) KUKA Robotics UK Limited Lloyd's Register Foundation
Lloyd's Register Group Offshore Renewable Energy Catapult OGIC (Oil and Gas Innovation Centre)
OGTC (formerly Oil and Gas Tech Centre) Permasense Limited Schlumberger
SCHUNK Intec Limited (UK) Scottish Enterprise Seebyte Ltd
SgurrEnergy Ltd Sprint Robotics Subsea 7 Limited
Subsea UK TechnipFMC (International) Tenaris (International)
Tharsus The Data Lab The Underwater Centre (UK)
Total E&P UK PLC
Department: Sch of Engineering and Physical Science
Organisation: Heriot-Watt University
Scheme: Standard Research
Starts: 02 October 2017 Ends: 31 March 2022 Value (£): 15,223,235
EPSRC Research Topic Classifications:
Artificial Intelligence Fundamentals of Computing
Human-Computer Interactions Image & Vision Computing
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Environment
Energy Information Technologies
Water R&D
Related Grants:
Panel History:
Panel DatePanel NameOutcome
18 Sep 2017 ISCF - Robotics and Artificial Intelligence Hub Full Bids Panel Meeting Announced
Summary on Grant Application Form
The international offshore energy industry currently faces the triple challenges of an oil price expected to remain less than $50 a barrel, significant expensive decommissioning commitments of old infrastructure (especially North Sea) and small margins on the traded commodity price per KWh of offshore renewable energy. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal.

The long-term industry vision is thus for a completely autonomous offshore energy field, operated, inspected and maintained from the shore. The time is now right to further develop, integrate and de-risk these into certifiable evaluation prototypes because there is a pressing need to keep UK offshore oil and renewable energy fields economic, and to develop more productive and agile products and services that UK startups, SMEs and the supply chain can export internationally. This will maintain a key economic sector currently worth £40 billion and 440,000 jobs to the UK economy, and a supply chain adding a further £6 billion in exports of goods and services.

The ORCA Hub is an ambitious initiative that brings together internationally leading experts from 5 UK universities with over 30 industry partners (>£17.5M investment). Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV).

The Hub will provide game-changing, remote solutions using robotics and AI that are readily integratable with existing and future assets and sensors, and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping of, navigation around and interaction with offshore assets that support the deployment of sensors networks for asset monitoring. Human-machine systems will be able to co-operate with remotely located human operators through an intelligent interface that manages the cognitive load of users in these complex, high-risk situations. Robots and sensors will be integrated into a broad asset integrity information and planning platform that supports self-certification of the assets and robots.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Project URL:  
Further Information:  
Organisation Website: http://www.hw.ac.uk