Robotics for Nuclear Environments

核环境机器人

• 批准号: EP/P01366X/1
• 负责人: Barry Lennox
• 金额: $ 592.54万
• 依托单位: University of Manchester
• 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%2FP01366X%2F1
• 关键词: Robotics; Nuclear; Environments

The vision for this Programme is to deliver the step changes in Robotics and Autonomous Systems (RAS) capability that are necessary to overcome crucial challenges facing the nuclear industry in the coming decades. The RAS challenges faced in the nuclear industry are extremely demanding and complex. Many nuclear installations, particularly the legacy facilities, present highly unstructured and uncertain environments. Additionally, these "high consequence" environments may contain radiological, chemical, thermal and other hazards. To minimise risks of contamination and radiological shine paths, many nuclear facilities have very small access ports (150 mm - 250 mm diameter), which prevent large robotic systems being deployed. Smaller robots have inherent limitations with power, sensing, communications and processing power, which remain unsolved. Thick concrete walls mean that communication bandwidths may be severely limited, necessitating increased levels of autonomy. Grasping and manipulation challenges, and the associated computer vision and perception challenges are profound; a huge variety of legacy waste materials must be sorted, segregated, and often also disrupted (cut or sheared). Some materials, such as plastic sheeting, contaminated suits/gloves/respirators, ropes, chains can be deformed and often present as chaotic self-occluding piles. Even known rigid objects (e.g. fuel rod casings) may present as partially visible or fragmented. Trivial tasks are complicated by the fact that the material properties of the waste, the dose rates and the layout of the facility within which the waste is stored may all be uncertain. It is therefore vital that any robotic solution be capable of robustly responding to uncertainties. The problems are compounded further by contamination risks, which typically mean that once deployed, human interaction with the robot will be limited at best, autonomy and fault tolerance are therefore important. The need for RAS in the nuclear industry is spread across the entire fuel cycle: reactor operations; new build reactors; decommissioning and waste storage and this Programme will address generic problems across all these areas. It is anticipated that the research will have a significant impact on many other areas of robotics: space, sub-sea, mining, bomb-disposal and health care, for example and cross sector initiatives will be pursued to ensure that there is a two-way transfer of knowledge and technology between these sectors, which have many challenges in common with the nuclear industry.The work will build on the robotics and nuclear engineering expertise available within the three academic organisations, who are each involved in cutting-edge, internationally leading research in relevant areas. This expertise will be complemented by the industrial and technology transfer experience and expertise of the National Nuclear Laboratory who have a proven track record of successfully delivering innovation in to the nuclear industry. The partners in the Programme will work jointly to develop new RAS related technologies (hardware and software), with delivery of nuclear focused demonstrators that will illustrate the successful outcomes of the Programme. Thus we will provide the nuclear supply chain and end-users with the confidence to apply RAS in the nuclear sector. To develop RAS technology that is suitable for the nuclear industry, it is essential that the partners work closely with the nuclear supply chain. To achieve this, the Programme will be based in west Cumbria, the centre of much of the UK's nuclear industry. Working with researchers at the home campuses of the academic institutions, the Programme will create a clear pipeline that propels early stage research from TRL 1 through to industrially relevant technology at TRL 3/4. Utilising the established mechanisms already available in west Cumbria, this technology can then be taken through to TRL 9 and commercial deployment.

该计划的愿景是实现机器人和自主系统（RAS）能力的阶段性变化，这是克服未来几十年核工业面临的关键挑战所必需的。核工业所面临的RAS挑战极其苛刻和复杂。许多核设施，特别是遗留设施，呈现出高度非结构化和不确定的环境。此外，这些“后果严重”的环境可能含有放射性、化学、热和其他危害。为了最大限度地减少污染和辐射照射路径的风险，许多核设施都有非常小的入口（直径150 mm - 250 mm），这阻止了大型机器人系统的部署。较小的机器人在电力、传感、通信和处理能力方面存在固有的局限性，这些问题尚未解决。厚厚的混凝土墙意味着通信带宽可能受到严重限制，需要提高自主性。抓取和操作的挑战，以及相关的计算机视觉和感知挑战是深刻的;各种各样的遗留废物必须分类，隔离，并且通常也要中断（切割或剪切）。一些材料，如塑料布、污染的防护服/手套/消毒器、绳索、链条可能会变形，并经常呈现为混乱的自封闭堆。甚至已知的刚性物体（例如，燃料棒外壳）也可以呈现为部分可见或碎片。由于废物的材料特性、剂量率和储存废物的设施的布局都可能不确定，使一些琐碎的任务变得复杂。因此，任何机器人解决方案都必须能够对不确定性做出稳健的响应。污染风险进一步加剧了这些问题，这通常意味着一旦部署，人类与机器人的互动将受到限制，因此自主性和容错性非常重要。核工业对RAS的需求遍及整个燃料循环：反应堆运行;新建反应堆;退役和废物储存，本计划将解决所有这些领域的一般问题。预计这项研究将对机器人技术的许多其他领域产生重大影响：例如，空间、海底、采矿、炸弹处理和保健，将采取跨部门举措，以确保这些部门之间双向转让知识和技术，这与核工业有许多共同的挑战。这项工作将建立在三个学术组织的机器人技术和核工程专业知识的基础上，他们都参与了相关领域的尖端国际领先研究。这种专业知识将得到国家核实验室的工业和技术转让经验和专业知识的补充，该实验室在成功向核工业提供创新方面有着良好的记录。该计划的合作伙伴将共同努力开发新的RAS相关技术（硬件和软件），并提供以核为重点的演示器，以展示该计划的成功成果。因此，我们将为核供应链和最终用户提供在核部门应用RAS的信心。为了开发适合核工业的RAS技术，合作伙伴必须与核供应链密切合作。为了实现这一目标，该计划将设在西坎布里亚郡，英国大部分核工业的中心。该计划将与学术机构所在校园的研究人员合作，创建一个明确的管道，推动从TRL 1到TRL 3/4的工业相关技术的早期研究。利用西坎布里亚郡已经建立的机制，这项技术可以被带到TRL 9和商业部署。

项目成果

Haptic-guided assisted telemanipulation approach for grasping desired objects from heaps

用于从堆中抓取所需物体的触觉引导辅助远程操作方法

• DOI: 10.48550/arxiv.2307.07053
• 发表时间: 2023
• 作者: Adjigble M

Mona: an Affordable Mobile Robot for Swarm Robotic Applications

• DOI: 10.31256/ukras17.16
• 发表时间: 2018-10
• 期刊: UK-RAS Conference: Robots Working For and Among Us Proceedings
• 作者: F. Arvin;J. Mendoza;Benjamin Bird;A. West;S. Watson;B. Lennox

Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging

• DOI: 10.1007/s10846-017-0673-8
• 发表时间: 2018-12-01
• 期刊: JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
• 影响因子: 3.3
• 作者: Arvin，Farshad;Watson，Simon;Lennox，Barry
• 通讯作者: Lennox，Barry

PhiClust pheromone based aggregation for robotic swarms

基于 PhiClust 信息素的机器人群聚合

• 发表时间: 2018
• 作者: Arvin F

3D Spectral Domain Registration-Based Visual Servoing

• DOI: 10.1109/icra48891.2023.10160430
• 发表时间: 2023-03
• 期刊: 2023 IEEE International Conference on Robotics and Automation (ICRA)
• 作者: Maxime Adjigble;B. Tamadazte;Cristiana Miranda de Farias;R. Stolkin;Naresh Marturi