用Simulink控制工业机器人

Bucur Cosmin, Andrei Alexandru, Tasu Sorin
{"title":"用Simulink控制工业机器人","authors":"Bucur Cosmin, Andrei Alexandru, Tasu Sorin","doi":"10.1109/ECAI58194.2023.10193974","DOIUrl":null,"url":null,"abstract":"Implementing machine learning algorithms like reinforcement learning in robotics is a continuously changing topic due to continuous tool changes and updates to keep track of new algorithms and tools. This paper presents a new toolchain to implement such algorithms with open-source packages like ROS2 for industrial robots. We developed new tools and procedures to enable the implementation of reinforcement learning algorithms through simulation or controlling real robots with Matlab.","PeriodicalId":391483,"journal":{"name":"2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Controlling industrial robots with Simulink\",\"authors\":\"Bucur Cosmin, Andrei Alexandru, Tasu Sorin\",\"doi\":\"10.1109/ECAI58194.2023.10193974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Implementing machine learning algorithms like reinforcement learning in robotics is a continuously changing topic due to continuous tool changes and updates to keep track of new algorithms and tools. This paper presents a new toolchain to implement such algorithms with open-source packages like ROS2 for industrial robots. We developed new tools and procedures to enable the implementation of reinforcement learning algorithms through simulation or controlling real robots with Matlab.\",\"PeriodicalId\":391483,\"journal\":{\"name\":\"2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECAI58194.2023.10193974\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECAI58194.2023.10193974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在机器人中实现机器学习算法(如强化学习)是一个不断变化的话题,因为工具不断变化和更新,以跟踪新的算法和工具。本文提出了一个新的工具链来实现这些算法与开源包,如工业机器人的ROS2。我们开发了新的工具和程序,通过Matlab模拟或控制真实机器人来实现强化学习算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Controlling industrial robots with Simulink
Implementing machine learning algorithms like reinforcement learning in robotics is a continuously changing topic due to continuous tool changes and updates to keep track of new algorithms and tools. This paper presents a new toolchain to implement such algorithms with open-source packages like ROS2 for industrial robots. We developed new tools and procedures to enable the implementation of reinforcement learning algorithms through simulation or controlling real robots with Matlab.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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