UK Robotics and Artificial Intelligence Hub for Offshore Energy Asset Integrity Management

英国海上能源资产完整性管理机器人和人工智能中心

• 批准号: EP/R026173/1
• 负责人: David Lane
• 金额: $ 1939.74万
• 依托单位: Heriot-Watt University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR026173%2F1
• 关键词: UK; Robotics; Artificial; Intelligence; Hub

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.

国际海上能源行业目前面临三重挑战：油价预计将保持在每桶50美元以下，旧基础设施（特别是北海）的退役承诺非常昂贵，海上可再生能源每千瓦时的交易商品价格利润率很小。此外，离岸劳动力正在老龄化，因为新一代合适的毕业生不愿意在离岸危险的地方工作。因此，运营商寻求更具成本效益，更安全的方法和商业模式来检查，维修和维护其上部和海上离岸基础设施。机器人技术和人工智能被视为这方面的关键推动因素，因为离岸员工的减少降低了成本，提高了安全性和工作场所的吸引力。因此，长期的行业愿景是建立一个完全自主的海上能源领域，从海岸进行操作、检查和维护。现在是时候进一步开发，整合和降低风险，将其纳入可认证的评估原型，因为迫切需要保持英国海上石油和可再生能源领域的经济性，并开发更具生产力和灵活性的产品和服务，英国初创公司，中小企业和供应链可以出口到国际。这将保持一个目前价值400亿英镑的关键经济部门和44万个就业岗位，以及一个供应链，进一步增加60亿英镑的商品和服务出口。ORCA Hub是一项雄心勃勃的计划，汇集了来自5所英国大学的国际领先专家和30多个行业合作伙伴（投资超过1750万英镑）。由爱丁堡机器人中心（HWU/UoE）牵头，与帝国理工学院、牛津大学和利物浦大学合作，这个多学科联盟带来了其独特的专业知识：水下（HWU），地面（UoE，Oxf）和空中机器人（ICL）;以及人机交互（HWU，UoE），用于无损评估和低成本传感器网络的创新传感器（ICL，UoE）;以及资产管理和认证（HWU，UoE，LIV）。该中心将使用机器人和人工智能提供改变游戏规则的远程解决方案，这些解决方案可与现有和未来的资产和传感器集成，并且可以在复杂和混乱的环境中以自主或半自主模式安全地运行和交互。我们将开发机器人解决方案，实现海上资产的准确测绘、导航和互动，支持部署传感器网络进行资产监控。人机系统将能够通过智能界面与远程操作员合作，该界面管理用户在这些复杂，高风险情况下的认知负荷。机器人和传感器将被集成到一个广泛的资产完整性信息和规划平台中，该平台支持资产和机器人的自我认证。

项目成果

Online Optimal Impedance Planning for Legged Robots

足式机器人在线最优阻抗规划

• DOI: 10.1109/iros40897.2019.8967696
• 发表时间: 2019
• 作者: Angelini F

Soft Robots for Ocean Exploration and Offshore Operations: A Perspective.

• DOI: 10.1089/soro.2020.0011
• 发表时间: 2021-12
• 期刊: Soft robotics
• 影响因子: 7.9
• 作者: Aracri S;Giorgio-Serchi F;Suaria G;Sayed ME;Nemitz MP;Mahon S;Stokes AA
• 通讯作者: Stokes AA

Integrated real-time, non-intrusive Measurements for Mental Load

集成的实时、非侵入式精神负荷测量

• 发表时间: 2019
• 作者: Ahmad, M. I.

Using Causal Analysis to Learn Specifications from Task Demonstrations

使用因果分析从任务演示中了解规范

• DOI: 10.48550/arxiv.1903.01267
• 发表时间: 2019
• 期刊: arXiv e-prints
• 作者: Angelov Daniel

A framework to estimate cognitive load using physiological data

• DOI: 10.1007/s00779-020-01455-7
• 发表时间: 2020-09-27
• 期刊: PERSONAL AND UBIQUITOUS COMPUTING
• 作者: Ahmad, Muneeb Imtiaz;Keller, Ingo;Lohan, Katrin S.
• 通讯作者: Lohan, Katrin S.