A Method of Mapping Between Information Model and ROS

Donguk Yu, Hong-Seong Park
{"title":"A Method of Mapping Between Information Model and ROS","authors":"Donguk Yu, Hong-Seong Park","doi":"10.5302/j.icros.2023.23.0105","DOIUrl":null,"url":null,"abstract":"This paper proposes a mapping method between ROS (Robot Operating System) and the ISO TC299 WG6\"s software information model standard for robot modules, providing interoperability, reusability, and interchangeability. To achieve this, this paper addresses issues such as the representation of data types for IO variables class and role relationships and data types in Services class, which are present in the current version of the information model, and provides solutions to complement them. It proposes mapping methods between the names, type structures, and type names of topics and services, which are used in ROS nodes, and IO variables class and Services class of the information model. To validate the proposed methods, an XML example for the IO variables and the Services classes for the information model is provided. Based on this example, related skeleton codes are generated for ROS nodes with topics and services. The generated skeleton codes are built and executed, and the information specified in the information model is compared to the results obtained from the execution of the generated codes, validating the proposed method.","PeriodicalId":38644,"journal":{"name":"Journal of Institute of Control, Robotics and Systems","volume":"35 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Institute of Control, Robotics and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5302/j.icros.2023.23.0105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0

Abstract

This paper proposes a mapping method between ROS (Robot Operating System) and the ISO TC299 WG6"s software information model standard for robot modules, providing interoperability, reusability, and interchangeability. To achieve this, this paper addresses issues such as the representation of data types for IO variables class and role relationships and data types in Services class, which are present in the current version of the information model, and provides solutions to complement them. It proposes mapping methods between the names, type structures, and type names of topics and services, which are used in ROS nodes, and IO variables class and Services class of the information model. To validate the proposed methods, an XML example for the IO variables and the Services classes for the information model is provided. Based on this example, related skeleton codes are generated for ROS nodes with topics and services. The generated skeleton codes are built and executed, and the information specified in the information model is compared to the results obtained from the execution of the generated codes, validating the proposed method.
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
一种信息模型与ROS的映射方法
本文提出了机器人操作系统(ROS)与ISO TC299 WG6机器人模块软件信息模型标准之间的映射方法,提供了互操作性、可重用性和互换性。为了实现这一点,本文解决了诸如IO变量类和角色关系的数据类型的表示以及服务类中的数据类型等问题,这些问题存在于当前版本的信息模型中,并提供了解决方案来补充它们。提出了ROS节点中使用的主题和服务的名称、类型结构和类型名称与信息模型的IO变量类和services类之间的映射方法。为了验证所建议的方法,提供了用于IO变量和用于信息模型的Services类的XML示例。基于此示例,为具有主题和服务的ROS节点生成相关的骨架代码。构建并执行生成的骨架代码,并将信息模型中指定的信息与从生成代码的执行中获得的结果进行比较,从而验证所建议的方法。
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
CiteScore
1.50
自引率
0.00%
发文量
128
期刊最新文献
Proposal of MRFScore and a Regression Model for Identification of Music Relationship Indicator Mixed Reality-based Structure Placement Verification System Using AR Marker Optimal Parameter Estimation for Topological Descriptor Based Sonar Image Matching in Autonomous Underwater Robots 3D Space Object and Road Detection for Autonomous Vehicles Using Monocular Camera Images and Deep Learning Algorithms Optimization Methods for Non-linear Least Squares
×
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