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，提高用于检查和维护工业设施的移动的机器人的操作能力。在许多工业环境中的主要任务是回收样品用于化学或生物分析。表面抽汲通常是手动进行的，但这会对可以采集的样本数量及其位置造成限制。由于位置（很高，或在封闭/受限的访问空间）或环境危险（如热或辐射），人们通常无法到达许多地方。本项目将开发一个多域，多代理机器人样本检索系统，该系统将能够在一系列环境中获取样本。这些样本将被储存在实验室进行非原位分析，或被带到移动的实验室进行原位实时分析。由于操作环境的性质，完全的自主性是不可取的，因此需要共享自主性（人在环）。主要应用重点将是核环境，但这些技术将适用于许多其他部门，包括石化，海上和农业。