在机器人和人造头像运动学中编码信息的数据驱动架构

IF 2.4 Q2 AUTOMATION & CONTROL SYSTEMS
Francesco De Lellis;Marco Coraggio;Nathan C. Foster;Riccardo Villa;Cristina Becchio;Mario Di Bernardo
{"title":"在机器人和人造头像运动学中编码信息的数据驱动架构","authors":"Francesco De Lellis;Marco Coraggio;Nathan C. Foster;Riccardo Villa;Cristina Becchio;Mario Di Bernardo","doi":"10.1109/LCSYS.2024.3416071","DOIUrl":null,"url":null,"abstract":"We present a data-driven control architecture designed to encode specific information, such as the presence or absence of an emotion, in the movements of an avatar or robot driven by a human operator. Our strategy leverages a set of human-recorded examples as the core for generating information-rich kinematic signals. To ensure successful object grasping, we propose a deep reinforcement learning strategy. We validate our approach using an experimental dataset obtained during the reach-to-grasp phase of a pick-and-place task.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10559995","citationCount":"0","resultStr":"{\"title\":\"Data-Driven Architecture to Encode Information in the Kinematics of Robots and Artificial Avatars\",\"authors\":\"Francesco De Lellis;Marco Coraggio;Nathan C. Foster;Riccardo Villa;Cristina Becchio;Mario Di Bernardo\",\"doi\":\"10.1109/LCSYS.2024.3416071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a data-driven control architecture designed to encode specific information, such as the presence or absence of an emotion, in the movements of an avatar or robot driven by a human operator. Our strategy leverages a set of human-recorded examples as the core for generating information-rich kinematic signals. To ensure successful object grasping, we propose a deep reinforcement learning strategy. We validate our approach using an experimental dataset obtained during the reach-to-grasp phase of a pick-and-place task.\",\"PeriodicalId\":37235,\"journal\":{\"name\":\"IEEE Control Systems Letters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10559995\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Control Systems Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10559995/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Control Systems Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10559995/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

我们提出了一种数据驱动型控制架构,旨在将特定信息(如是否存在某种情绪)编码到由人类操作员驱动的化身或机器人的动作中。我们的策略以一组人类记录的示例为核心,生成信息丰富的运动信号。为确保成功抓取物体,我们提出了一种深度强化学习策略。我们利用在拾放任务的伸手抓取阶段获得的实验数据集验证了我们的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-Driven Architecture to Encode Information in the Kinematics of Robots and Artificial Avatars
We present a data-driven control architecture designed to encode specific information, such as the presence or absence of an emotion, in the movements of an avatar or robot driven by a human operator. Our strategy leverages a set of human-recorded examples as the core for generating information-rich kinematic signals. To ensure successful object grasping, we propose a deep reinforcement learning strategy. We validate our approach using an experimental dataset obtained during the reach-to-grasp phase of a pick-and-place task.
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
IEEE Control Systems Letters
IEEE Control Systems Letters Mathematics-Control and Optimization
CiteScore
4.40
自引率
13.30%
发文量
471
×
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