Semi-Autonomous Industrial Robotic Inspection: Remote Methane Detection in Oilfield

R. S. Filho, Ching-Ling Huang, Bo Yu, Raju D. Venkataramana, A. El-Messidi, Dustin Sharber, John Westerheide, N. Alkadi
{"title":"Semi-Autonomous Industrial Robotic Inspection: Remote Methane Detection in Oilfield","authors":"R. S. Filho, Ching-Ling Huang, Bo Yu, Raju D. Venkataramana, A. El-Messidi, Dustin Sharber, John Westerheide, N. Alkadi","doi":"10.1109/EDGE.2018.00010","DOIUrl":null,"url":null,"abstract":"Robots have been increasingly used in industrial applications. They usually operate along with other robots and human supervisors in complex tasks such as industrial assets inspection, monitoring and maintenance. Even though fully autonomous robotics applications are still work-in-progress, supervised semi-autonomic operation of robots in industrial applications are going mainstream. They promote overall cost reduction, efficiency, accuracy and safety of human workers. These systems combine human-in-the-loop, semi-autonomous robots, edge computing and cloud services to achieve the automation of complex industrial tasks. This paper is a first in series where we describe a robotic platform developed within BHGE and GE-GRC, discussing its use in one example of industrial inspection case study for remote methane inspection in oilfield. We outline the requirements for the system, sharing the experience of our design and implementation trade-offs. In particular, the synergy among the semi-autonomous robots, human supervisors, model-based edge controls, and the cloud services is designed to achieve the responsive onsite monitoring and to cope with the limited connectivity, bandwidth and processing constraints in typical industrial setting.","PeriodicalId":396887,"journal":{"name":"2018 IEEE International Conference on Edge Computing (EDGE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Edge Computing (EDGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDGE.2018.00010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Robots have been increasingly used in industrial applications. They usually operate along with other robots and human supervisors in complex tasks such as industrial assets inspection, monitoring and maintenance. Even though fully autonomous robotics applications are still work-in-progress, supervised semi-autonomic operation of robots in industrial applications are going mainstream. They promote overall cost reduction, efficiency, accuracy and safety of human workers. These systems combine human-in-the-loop, semi-autonomous robots, edge computing and cloud services to achieve the automation of complex industrial tasks. This paper is a first in series where we describe a robotic platform developed within BHGE and GE-GRC, discussing its use in one example of industrial inspection case study for remote methane inspection in oilfield. We outline the requirements for the system, sharing the experience of our design and implementation trade-offs. In particular, the synergy among the semi-autonomous robots, human supervisors, model-based edge controls, and the cloud services is designed to achieve the responsive onsite monitoring and to cope with the limited connectivity, bandwidth and processing constraints in typical industrial setting.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
半自主工业机器人检测:油田甲烷远程检测
机器人在工业应用中得到越来越多的应用。它们通常与其他机器人和人类监督员一起执行复杂的任务,如工业资产检查、监控和维护。尽管完全自主的机器人应用仍在进行中,但机器人在工业应用中的监督半自动操作正在成为主流。它们促进了人类工人的整体成本降低、效率、准确性和安全性。这些系统结合了人在环、半自动机器人、边缘计算和云服务,以实现复杂工业任务的自动化。本文是系列文章中的第一篇,介绍了BHGE和GE-GRC开发的机器人平台,并讨论了其在油田远程甲烷检测的工业检测案例研究中的应用。我们概述了系统的需求,分享了我们的设计和实现权衡的经验。特别是,半自主机器人、人类监督员、基于模型的边缘控制和云服务之间的协同作用,旨在实现响应式现场监控,并应对典型工业环境中有限的连接、带宽和处理限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Publisher's Information Edge Powered Industrial Control: Concept for Combining Cloud and Automation Technologies Enterprise Scale Privacy Aware Occupancy Sensing Message from the IEEE EDGE 2018 Chairs Real-Time Traffic Pattern Collection and Analysis Model for Intelligent Traffic Intersection
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1