Natural head and body orientation for humanoid robots during conversations with moving human partners through motion capture analysis

Pranav Barot, Ewen N. MacDonald, K. Mombaur
{"title":"Natural head and body orientation for humanoid robots during conversations with moving human partners through motion capture analysis","authors":"Pranav Barot, Ewen N. MacDonald, K. Mombaur","doi":"10.1109/ARSO56563.2023.10187462","DOIUrl":null,"url":null,"abstract":"In conversations between humans, a natural body and head orientation towards the interlocutor is important for their social interaction. Humanoids communicating with humans have to learn how to orient themselves properly which becomes a challenging task in the case of moving conversation partners. Studies of conversational behaviour often involve only stationary partners. In this research, we perform a motion capture study to address the scenario of moving subjects. Specifically, study trials were recorded during conversation between a human participant and interlocutor, with a focus on the behaviour of the head, shoulders, and feet. The results help better understand how humans behave while conversing with non-stationary interlocutors. The data from the trials was used to generate a mathematical model describing the relationship of the angle at which the interlocutor is located to the orientations of the head, shoulders and feet while tracking is performed. A new model setup to couple the motion of the interlocutor, the head and the shoulders is introduced, as well as a model to represent stepping in order to better replicate participant behaviour. The models are evaluated and then deployed to the REEM-C Humanoid Robot, for the purposes of generating a natural behavior of the robot and improving human-robot interaction.","PeriodicalId":382832,"journal":{"name":"2023 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)","volume":"226 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARSO56563.2023.10187462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

In conversations between humans, a natural body and head orientation towards the interlocutor is important for their social interaction. Humanoids communicating with humans have to learn how to orient themselves properly which becomes a challenging task in the case of moving conversation partners. Studies of conversational behaviour often involve only stationary partners. In this research, we perform a motion capture study to address the scenario of moving subjects. Specifically, study trials were recorded during conversation between a human participant and interlocutor, with a focus on the behaviour of the head, shoulders, and feet. The results help better understand how humans behave while conversing with non-stationary interlocutors. The data from the trials was used to generate a mathematical model describing the relationship of the angle at which the interlocutor is located to the orientations of the head, shoulders and feet while tracking is performed. A new model setup to couple the motion of the interlocutor, the head and the shoulders is introduced, as well as a model to represent stepping in order to better replicate participant behaviour. The models are evaluated and then deployed to the REEM-C Humanoid Robot, for the purposes of generating a natural behavior of the robot and improving human-robot interaction.
通过动作捕捉分析,人形机器人在与移动的人类伙伴对话时的自然头部和身体方向
在人类之间的对话中,身体和头部朝向对话者的自然方向对他们的社会互动很重要。与人类交流的类人机器人必须学会如何正确地定位自己,这在移动对话伙伴的情况下成为一项具有挑战性的任务。对会话行为的研究通常只涉及静止的伙伴。在这项研究中,我们进行了一项运动捕捉研究,以解决移动受试者的场景。具体来说,研究试验记录了人类参与者和对话者之间的对话,重点关注头部、肩膀和脚的行为。研究结果有助于更好地理解人类在与不固定的对话者交谈时的行为。来自试验的数据被用来生成一个数学模型,该模型描述了对话者在跟踪时所处的角度与头部、肩膀和脚的方向之间的关系。引入了一个新的模型来耦合对话者、头部和肩膀的运动,以及一个代表步的模型,以便更好地复制参与者的行为。对模型进行评估,然后将其部署到REEM-C类人机器人中,以生成机器人的自然行为并改善人机交互。
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:604180095
Book学术官方微信