Fault Management of Robot Software Components Based on OPRoS

JongYoung Kim, Heebyung Yoon, Sunghoon Kim, S. Son
{"title":"Fault Management of Robot Software Components Based on OPRoS","authors":"JongYoung Kim, Heebyung Yoon, Sunghoon Kim, S. Son","doi":"10.1109/ISORC.2011.41","DOIUrl":null,"url":null,"abstract":"Component-based robot development has been a vibrant research topic in robotics due to its reusability and interoperability benefits. However, robot application developers using robot components must invest non-trivial amount of time and effort applying fault tolerance techniques into their robot applications. Despite the need for a common, framework-level fault management, the majority of existing robot software frameworks has failed to provide systematic fault management features. In this paper, we propose a fault management method to detect, diagnose, isolate and recover faults based on the OPRoS software framework. The proposed method provides a collective, framework-level management for commonly encountered robot software faults, thereby reducing the application developers' efforts while enhancing the robot system reliability. To verify the effectiveness of the proposed approach, we have implemented a prototype reconnaissance robot using OPRoS components and injected different types of faults. The results of the experiments have shown that our approach effectively detects, diagnoses, and recovers component faults using the software framework.","PeriodicalId":431231,"journal":{"name":"2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 14th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISORC.2011.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Component-based robot development has been a vibrant research topic in robotics due to its reusability and interoperability benefits. However, robot application developers using robot components must invest non-trivial amount of time and effort applying fault tolerance techniques into their robot applications. Despite the need for a common, framework-level fault management, the majority of existing robot software frameworks has failed to provide systematic fault management features. In this paper, we propose a fault management method to detect, diagnose, isolate and recover faults based on the OPRoS software framework. The proposed method provides a collective, framework-level management for commonly encountered robot software faults, thereby reducing the application developers' efforts while enhancing the robot system reliability. To verify the effectiveness of the proposed approach, we have implemented a prototype reconnaissance robot using OPRoS components and injected different types of faults. The results of the experiments have shown that our approach effectively detects, diagnoses, and recovers component faults using the software framework.
基于opro的机器人软件组件故障管理
基于组件的机器人开发由于其可重用性和互操作性的优势,一直是机器人领域一个充满活力的研究课题。然而,使用机器人组件的机器人应用程序开发人员必须投入大量的时间和精力,将容错技术应用到他们的机器人应用程序中。尽管需要通用的框架级故障管理,但大多数现有的机器人软件框架未能提供系统的故障管理功能。本文提出了一种基于OPRoS软件框架的故障管理方法,实现故障的检测、诊断、隔离和恢复。该方法为机器人常见的软件故障提供了一个集体的框架级管理,从而减少了应用程序开发人员的工作量,同时提高了机器人系统的可靠性。为了验证该方法的有效性,我们使用opro组件实现了一个原型侦察机器人,并注入了不同类型的故障。实验结果表明,该方法利用软件框架有效地检测、诊断和恢复组件故障。
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
自引率
0.00%
发文量
0
×
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