Sprint Robotics
Sprint Robotics
2 Projects, page 1 of 1
assignment_turned_in Project2017 - 2022Partners:The Oil and Gas Technology Centre Ltd, OGIC (Oil and Gas Innovation Centre), SCHUNK Intec Limited (UK), KUKA Robotics UK Limited, TechnipFMC (France) +61 partnersThe Oil and Gas Technology Centre Ltd,OGIC (Oil and Gas Innovation Centre),SCHUNK Intec Limited (UK),KUKA Robotics UK Limited,TechnipFMC (France),Chevron (United Kingdom),Schunk (United Kingdom),KUKA Robotics UK Limited,Total E&P UK PLC,Tharsus,Lloyd's Register Foundation,Guided Ultrasonics Ltd,British Petroleum International Limited,SCR,Itf, The Industry Technology,SeeByte Ltd,Subsea 7 Limited,Subsea UK,Innovation Centre for Sensor and Imaging Systems,KUKA (United Kingdom),Baker Hughes Ltd,Offshore Renewable Energy Catapult,Autonomous Surface Vehicles Ltd (ASV),Kawasaki Heavy Industries Ltd (Global),Lloyd's Register Foundation,LR IMEA,CENSIS,Permasense Limited,Scottish Enterprise,The Underwater Centre (UK),Hydrason Solutions Limited,Sprint Robotics,The Data Lab,Subsea 7 Limited,The Underwater Centre (UK),CHEVRON NORTH SEA LIMITED,OFFSHORE RENEWABLE ENERGY CATAPULT,ABB (Switzerland),Itf, The Industry Technology,General Dynamics (United Kingdom),TechnipFMC (International),Kawasaki Heavy Industries (Japan),Oil & Gas Innovation Centre,Tharsus,Hydrason Solutions Limited,SgurrEnergy,ABB Group (International),Tenaris,Scottish Enterprise,Heriot-Watt University,Schlumberger (United Kingdom),Lloyd's Register Foundation,Guided Ultrasonics Ltd,Tenaris (United States),The Data Lab,Subsea UK,Offshore Renewable Energy Catapult,SgurrEnergy Ltd,British Petroleum International Limited,Baker Hughes (United Kingdom),SBT,Sprint Robotics,PERMASTORE LIMITED,Total E&P UK PLC,Heriot-Watt University,ASV (United Kingdom)Funder: UK Research and Innovation Project Code: EP/R026173/1Funder Contribution: 15,223,200 GBPThe 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.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2017 - 2022Partners:OC Robotics, EDF Energy (United Kingdom), UK Trade and Investment, NUVIA LIMITED, BP (United States) +74 partnersOC Robotics,EDF Energy (United Kingdom),UK Trade and Investment,NUVIA LIMITED,BP (United States),Longenecker and Associates (United States),Nuvia (United Kingdom),Chinese Academy of Sciences,Sellafield (United Kingdom),Italian Institute of Technology,Forth Engineering Ltd,James Fisher Nuclear Limited,Nuclear Decommissioning Authority,Tharsus,Uniper Technologies Ltd.,Japan Atomic Energy Agency,CAS,Imitec Ltd,Virtual Engineering Centre (VEC),Shadow Robot (United Kingdom),Innotec Ltd,Nuclear Decommissioning Authority,BP British Petroleum,Italian Institute of Technology,Createc (United Kingdom),Department for International Trade,Valtegra,Moog Controls Ltd,Oxford Investment Opportunity Network,Tharsus,Sprint Robotics,Chinese Academy of Sciences,Valtegra,OC Robotics,Rolls-Royce (United Kingdom),Shadow Robot Company Ltd,Nuclear AMRC,Fusion for Energy,Longenecker and Associates,EDF Energy Plc (UK),Oxford Investment Opportunity Network,FSC,The University of Manchester,NDA,Rolls-Royce Plc (UK),Sprint Robotics,Japan Atomic Energy Agency,Beihang University,Createc Ltd,Gassco,Imitec Ltd,ITER - International Fusion Energy Org,Festo Ltd,James Fisher Nuclear Limited,University of Manchester,ABB (Switzerland),Nuclear AMRC,Sellafield Ltd,Innotec (United Kingdom),NNL,The University of Texas at Austin,University of Salford,Gassco (Norway),Beihang University (BUAA),Uniper Technologies Ltd.,Atomic Weapons Establishment,Moog Controls Ltd,Festo Ltd,EDF Energy (United Kingdom),MTC,AWE,Virtual Engineering Centre (VEC),Manufacturing Technology Centre (United Kingdom),Fusion For Energy,ITER - International Fusion Energy Org,ABB (United Kingdom),National Nuclear Laboratory (NNL),Forth Engineering Ltd,Rolls-Royce (United Kingdom)Funder: UK Research and Innovation Project Code: EP/R026084/1Funder Contribution: 12,807,900 GBPThe nuclear industry has some of the most extreme environments in the world, with radiation levels and other hazards frequently restricting human access to facilities. Even when human entry is possible, the risks can be significant and very low levels of productivity. To date, robotic systems have had limited impact on the nuclear industry, but it is clear that they offer considerable opportunities for improved productivity and significantly reduced human risk. The nuclear industry has a vast array of highly complex and diverse challenges that span the entire industry: decommissioning and waste management, Plant Life Extension (PLEX), Nuclear New Build (NNB), small modular reactors (SMRs) and fusion. Whilst the challenges across the nuclear industry are varied, they share many similarities that relate to the extreme conditions that are present. Vitally these similarities also translate across into other environments, such as space, oil and gas and mining, all of which, for example, have challenges associated with radiation (high energy cosmic rays in space and the presence of naturally occurring radioactive materials (NORM) in mining and oil and gas). Major hazards associated with the nuclear industry include radiation; storage media (for example water, air, vacuum); lack of utilities (such as lighting, power or communications); restricted access; unstructured environments. These hazards mean that some challenges are currently intractable in the absence of solutions that will rely on future capabilities in Robotics and Artificial Intelligence (RAI). Reliable robotic systems are not just essential for future operations in the nuclear industry, but they also offer the potential to transform the industry globally. In decommissioning, robots will be required to characterise facilities (e.g. map dose rates, generate topographical maps and identify materials), inspect vessels and infrastructure, move, manipulate, cut, sort and segregate waste and assist operations staff. To support the life extension of existing nuclear power plants, robotic systems will be required to inspect and assess the integrity and condition of equipment and facilities and might even be used to implement urgent repairs in hard to reach areas of the plant. Similar systems will be required in NNB, fusion reactors and SMRs. Furthermore, it is essential that past mistakes in the design of nuclear facilities, which makes the deployment of robotic systems highly challenging, do not perpetuate into future builds. Even newly constructed facilities such as CERN, which now has many areas that are inaccessible to humans because of high radioactive dose rates, has been designed for human, rather than robotic intervention. Another major challenge that RAIN will grapple with is the use of digital technologies within the nuclear sector. Virtual and Augmented Reality, AI and machine learning have arrived but the nuclear sector is poorly positioned to understand and use these rapidly emerging technologies. RAIN will deliver the necessary step changes in fundamental robotics science and establish the pathways to impact that will enable the creation of a research and innovation ecosystem with the capability to lead the world in nuclear robotics. While our centre of gravity is around nuclear we have a keen focus on applications and exploitation in a much wider range of challenging environments.
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