Toward Competent Robot Apprentices: Enabling Proactive Troubleshooting in Collaborative Robots

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Christopher Thierauf, Theresa Law, Tyler M. Frasca, Matthias Scheutz
{"title":"Toward Competent Robot Apprentices: Enabling Proactive Troubleshooting in Collaborative Robots","authors":"Christopher Thierauf, Theresa Law, Tyler M. Frasca, Matthias Scheutz","doi":"10.3390/machines12010073","DOIUrl":null,"url":null,"abstract":"For robots to become effective apprentices and collaborators, they must exhibit some level of autonomy, for example, recognizing failures and identifying ways to address them with the aid of their human teammates. In this systems paper, we present an integrated cognitive robotic architecture for a “robot apprentice” that is capable of assessing its own performance, identifying task execution failures, communicating them to humans, and resolving them, if possible. We demonstrate the capabilities of our proposed architecture with a series of demonstrations and confirm with an online user study that people prefer our robot apprentice compared to robots without those capabilities.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/machines12010073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

Abstract

For robots to become effective apprentices and collaborators, they must exhibit some level of autonomy, for example, recognizing failures and identifying ways to address them with the aid of their human teammates. In this systems paper, we present an integrated cognitive robotic architecture for a “robot apprentice” that is capable of assessing its own performance, identifying task execution failures, communicating them to humans, and resolving them, if possible. We demonstrate the capabilities of our proposed architecture with a series of demonstrations and confirm with an online user study that people prefer our robot apprentice compared to robots without those capabilities.
培养合格的机器人学徒:让协作机器人主动排除故障
要使机器人成为有效的学徒和合作者,它们必须表现出一定程度的自主性,例如,在人类队友的帮助下识别失败并找出解决方法。在这篇系统论文中,我们为 "机器人学徒 "提出了一个综合认知机器人架构,该架构能够评估自身性能、识别任务执行失败、与人类沟通并在可能的情况下解决这些问题。我们通过一系列演示展示了我们提出的架构的能力,并通过在线用户研究证实,与不具备这些能力的机器人相比,人们更喜欢我们的机器人学徒。
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 求助全文
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信