Centre for Robotic Autonomy in Demanding and Long-lasting Environments (CRADLE)
高要求和持久环境下的机器人自主中心 (CRADLE)
基本信息
- 批准号:EP/X02489X/1
- 负责人:
- 金额:$ 469.17万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2023
- 资助国家:英国
- 起止时间:2023 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
CRADLE brings together the industrial experience that Jacobs have in applied Robotics and Autonomous Systems (RAS) with the research expertise at the University of Manchester in this field, to create a collaborative research centre that is internationally leading and sustainable in the long-term. Our vision for CRADLE is that it will deliver novel and transformational RAS technology for demanding environments, such as space, nuclear, energy generation and urban infrastructure, allowing the benefits promised by this technology to be realised across wide sectors of UK industry. Whilst there has been significant progress made in robotic systems in recent years, the step to truly autonomous robotics and smart machines, which will deliver the greatest impact to UK industry, remains a significant barrier, particularly in complex, demanding and heavily regulated environments. Here, incorrect decisions and inappropriate actions can have significant consequences, such as the release of radioactive materials or the loss of high value equipment. We have seen that incremental extensions to RAS components have not been sufficient to surmount this autonomy barrier and believe that a step change is required to:- create an autonomy-focussed framework that brings together the many independent robotic components that includes sensors, actuators, software and safety systems;- address key research gaps that exist in the specific components within this framework that affect the reliability, resilience and trustworthiness of the overall autonomous system; and- clarify, and embed, the wide range of end-user, business and regulatory constraints that must be accommodated within this framework for long-lasting autonomy.CRADLE has been guided by future industry needs and addresses major research obstacles to RAS development. Furthermore, CRADLE will create a pathway to impact that enables low-TRL RAS technologies to be developed and then translated into safe, reliable and innovative solutions that can be deployed to address long-term industry and societal problems in a range of demanding environments. We will focus on generic technologies that will allow RAS to be deployed across multiple industry sectors, and we will target specific use cases that will enable this technology to be demonstrated in sectors of particular importance to the industrial supply chain. These use cases will be drawn from sectors where Jacobs have existing capability, such as nuclear, space and urban infrastructure, but we will also explore areas of growing interest and opportunity, such as clean energy generation, sustainable transportation, healthcare and security.
CRADLE将Jacobs在应用机器人和自主系统(RAS)方面的工业经验与曼彻斯特大学在该领域的研究专长结合在一起,创建了一个国际领先且长期可持续发展的合作研究中心。我们对CRADLE的愿景是,它将为苛刻的环境,如空间,核能,能源发电和城市基础设施,提供新颖和变革性的RAS技术,使这项技术所承诺的好处在英国工业的广泛领域得到实现。虽然近年来机器人系统取得了重大进展,但真正自主的机器人和智能机器仍然是一个重大障碍,特别是在复杂、苛刻和严格监管的环境中,这将对英国工业产生最大的影响。在这里,不正确的决定和不适当的行动可能会产生严重的后果,例如放射性物质的释放或高价值设备的损失。我们已经看到,RAS组件的增量扩展不足以克服这种自主性障碍,并认为需要逐步改变:创建一个以自主性为重点的框架,将许多独立的机器人组件(包括传感器、执行器、软件和安全系统)整合在一起;-解决该框架内特定组件中存在的关键研究空白,这些空白会影响整个自治系统的可靠性、弹性和可信度;明确并嵌入广泛的终端用户、商业和监管约束,这些约束必须在这一框架内得到适应,以实现持久的自治。CRADLE以未来的行业需求为指导,解决了RAS发展的主要研究障碍。此外,CRADLE将创造一条影响途径,使低trl RAS技术得以开发,然后转化为安全、可靠和创新的解决方案,可用于解决一系列苛刻环境下的长期行业和社会问题。我们将专注于允许RAS在多个行业部门部署的通用技术,并且我们将针对特定的用例,这些用例将使该技术能够在对工业供应链特别重要的部门中得到演示。这些用例将来自雅各布斯现有能力的领域,如核能、空间和城市基础设施,但我们也将探索日益增长的兴趣和机会领域,如清洁能源发电、可持续交通、医疗保健和安全。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Barry Lennox其他文献
A Recursive Multi-Block PLS Algorithm for Monitoring Industrial Processes
- DOI:
10.1016/s1474-6670(17)32949-x - 发表时间:
2001-11-01 - 期刊:
- 影响因子:
- 作者:
Xun Wang;Uwe Krugerz;Andrew Y.T. Leung;Barry Lennox - 通讯作者:
Barry Lennox
Analysis of multivariate statistical methods for continuous systems
- DOI:
10.1016/s0098-1354(99)80051-9 - 发表时间:
1999-06-01 - 期刊:
- 影响因子:
- 作者:
Barry Lennox;Peter R. Goulding;David J. Sandoz - 通讯作者:
David J. Sandoz
An assessment of contamination pickup on ground robotic vehicles for nuclear surveying application
用于核测量应用的地面机器人车辆污染拾取的评估
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:1.5
- 作者:
Antonios Banos;Jim Hayman;Tom Wallace;Benjamin Bird;Barry Lennox;Thomas B. Scott - 通讯作者:
Thomas B. Scott
Moving Window MSPC and Its Application to Batch Processes
- DOI:
10.1016/s1474-6670(17)34193-9 - 发表时间:
2001-06-01 - 期刊:
- 影响因子:
- 作者:
Barry Lennox;Gary Montague;Hugo Hiden;Georg KornfeId - 通讯作者:
Georg KornfeId
Barry Lennox的其他文献
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{{ truncateString('Barry Lennox', 18)}}的其他基金
Robotics and Artificial Intelligence for Nuclear Plus (RAIN+)
核+机器人和人工智能(RAIN)
- 批准号:
EP/W001128/1 - 财政年份:2021
- 资助金额:
$ 469.17万 - 项目类别:
Research Grant
Advancing Location Accuracy via Collimated Nuclear Assay for Decommissioning Robotic Applications (ALACANDRA)
通过用于退役机器人应用的准直核分析提高定位精度 (ALACANDRA)
- 批准号:
EP/V026925/1 - 财政年份:2021
- 资助金额:
$ 469.17万 - 项目类别:
Research Grant
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 - 财政年份:2017
- 资助金额:
$ 469.17万 - 项目类别:
Research Grant
Development of a monitoring tool for high pressure oil and gas pipelines.
高压油气管道监测工具的开发。
- 批准号:
EP/I500944/1 - 财政年份:2011
- 资助金额:
$ 469.17万 - 项目类别:
Research Grant
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