Robotics and Artificial Intelligence for Critical Asset Monitoring (RAICAM)

用于关键资产监控的机器人和人工智能 (RAICAM)

• 批准号: EP/X025004/1
• 负责人: Simon Watson
• 金额: $ 33.8万
• 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: 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: https://gtr.ukri.org/projects?ref=EP%2FX025004%2F1
• 关键词: Robotics; Artificial; Intelligence; Critical; Asset

This project aims to develop technologies which will enhance the operational capabilities of mobile robots for use in the inspection and maintenance of industrial facilities. A major task in many industrial environments is the retrieval of samples for chemical or biological analysis. Surface swabbing is often conducted manually, but this creates limits on the number of samples that can be taken and their location. There are often many places that can't be reached by people either due to the location (very high, or in confined/restricted access spaces) or environmental hazardous (such as heat or radiation).This project will develop a multi-domain, multi-agent robotic sample retrieval system that will be able to obtain samples across a range of environments. These samples will either be stored for ex-situ analysis in labs or taken to mobile labs for in-situ, real-time analysed. Due to the nature of the operational environments, full autonomy is not desirable, so shared autonomy (human-in-the-loop) will be required. The primary application focus will be nuclear environments, however the technologies will be applicable to many other sectors include petrochemical, offshore and agriculture.

该项目旨在开发技术，以增强移动机器人的运行能力，用于检查和维护工业设施。在许多工业环境中的主要任务是检索化学或生物学分析的样品。表面擦拭通常是手动进行的，但这会限制可以采集的样品及其位置的数量。由于位置（非常高，或受到限制的访问空间）或环境危险（例如热量或辐射），人们通常无法到达许多地方。该项目将开发一个多域，多机器人的机器人样品检索系统，这些系统将能够在环境中获取样品。这些样本将存储在实验室中进行现场分析，或者将其带到移动实验室进行实时分析。由于操作环境的性质，完全自治是不可取的，因此将需要共享的自主权（人类在循环）中。主要的应用重点是核环境，但是该技术将适用于许多其他部门，包括石化，离岸和农业。