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Robotics and Artificial Intelligence for Nuclear (RAIN)

Robotics and Artificial Intelligence for Nuclear (RAIN)
核工业机器人和人工智能 (RAIN)
批准号:
EP/R026084/1
负责人:
Barry Lennox
金额:
$1631.98万
依托单位:
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
项目状态:
已结题
起止时间:
2017 至 --

项目摘要

项目成果

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中文摘要
翻译
核工业有一些世界上最极端的环境,辐射水平和其他危害经常限制人们进入设施。即使人工进入是可能的,风险也可能很大,生产力水平也很低。迄今为止,机器人系统对核工业的影响有限,但很明显,它们为提高生产率和显著降低人类风险提供了相当大的机会。核工业面临着跨越整个行业的一系列高度复杂和多样化的挑战:退役和废物管理、工厂寿命延长(PLEX)、新建核反应堆(NNB)、小型模块化反应堆(smr)和核聚变。尽管整个核工业面临的挑战各不相同,但它们与目前的极端条件有许多相似之处。至关重要的是,这些相似之处也可以转化为其他环境,例如空间、石油和天然气以及采矿,所有这些环境都面临与辐射(空间中的高能宇宙射线以及采矿和石油和天然气中天然存在的放射性物质(NORM))相关的挑战。与核工业有关的主要危害包括辐射;存储介质(如水、空气、真空);缺乏公用设施(如照明、电力或通讯);限制访问;非结构化环境。这些危险意味着,在缺乏依赖于机器人和人工智能(RAI)未来能力的解决方案的情况下,一些挑战目前是棘手的。可靠的机器人系统不仅对未来核工业的运行至关重要,而且还具有改变全球核工业的潜力。在退役过程中,将需要机器人来描述设施特征(例如绘制剂量率图、生成地形图和识别材料)、检查船只和基础设施、移动、操作、切割、分类和隔离废物,并协助操作人员。为了支持延长现有核电站的寿命,将需要机器人系统来检查和评估设备和设施的完整性和状况,甚至可能用于在难以到达的核电站区域进行紧急维修。NNB、聚变反应堆和小型堆也需要类似的系统。此外,至关重要的是,过去核设施设计中的错误(这使得机器人系统的部署极具挑战性)不能延续到未来的建设中。即使是新建的设施,如欧洲核子研究中心,现在有许多区域由于高放射性剂量率而无法进入,也是为人类而不是机器人干预而设计的。RAIN将努力应对的另一个主要挑战是在核部门使用数字技术。虚拟现实和增强现实、人工智能和机器学习已经到来,但核能行业在理解和使用这些迅速崛起的技术方面处于不利地位。RAIN将为基础机器人科学提供必要的步骤变化,并建立影响途径,从而能够创建一个具有领导世界核机器人能力的研究和创新生态系统。虽然我们的重心是围绕核能,但我们热切关注在更广泛的具有挑战性的环境中的应用和开发。
英文摘要
The 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.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
Input Shaping Predictive Functional Control for Different Types of Challenging Dynamics Processes
针对不同类型的挑战性动力学过程的输入整形预测功能控制
DOI: 10.3390/pr6080118
发表时间: 2018
期刊: Processes
影响因子: 3.5
作者: [Abdullah M]
通讯作者: Abdullah M
The effect of model structure on the noise and disturbance sensitivity of Predictive Functional Control
模型结构对预测函数控制噪声和扰动灵敏度的影响
DOI: --
发表时间: 2018
期刊:
影响因子: --
作者: [Abdullah, M.]
通讯作者: Abdullah, M.
Alternative Method for Predictive Functional Control to Handle an Integrating Process
处理积分过程的预测功能控制的替代方法
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [Abdullah, M.]
通讯作者: Abdullah, M.
DOI: 10.1109/mis.2018.111144814
发表时间: 2018-11-01
期刊: IEEE INTELLIGENT SYSTEMS
影响因子: 6.4
作者: [Aitken, Jonathan M., Veres, Sandor M., Mort, Paul E.]
通讯作者: Mort, Paul E.
共 7 条
    Centre for Robotic Autonomy in Demanding and Long-lasting Environments (CRADLE)
    • 批准号:
      EP/X02489X/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $469.17万
    • 财政年份:
      2023
    • 负责人:
      Barry Lennox
    • 依托单位:
    Robotics and Artificial Intelligence for Nuclear Plus (RAIN+)
    • 批准号:
      EP/W001128/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $251.71万
    • 财政年份:
      2021
    • 负责人:
      Barry Lennox
    • 依托单位:
    Advancing Location Accuracy via Collimated Nuclear Assay for Decommissioning Robotic Applications (ALACANDRA)
    • 批准号:
      EP/V026925/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $67.19万
    • 财政年份:
      2021
    • 负责人:
      Barry Lennox
    • 依托单位:
    Robotics for Nuclear Environments
    • 批准号:
      EP/P01366X/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $592.54万
    • 财政年份:
      2017
    • 负责人:
      Barry Lennox
    • 依托单位:
    海外基金