Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900789
Ningyuan Sun, J. Botev, Yara Khaluf, P. Simoens
Despite already being commonplace, delegation to robotic virtual agents (VAs) is often considered challenging and error-prone in critical situations by the general public. Theory of mind, the human capacity to take another person's perspective, is deemed an important enabler for human-human cooperation. This study explores the effect of a robotic VA's ability to use theory of mind on users' delegation behavior. To this end, we conducted a between-subjects experiment with participants playing the Colored Trails game with robotic VAs of varying levels of theory of mind. The results invalidate our hypothesis that the ToM level is a reliable indicator of delegation choices. Instead, we found that the participants' performance strongly correlates with their delegatory intentions. Therefore, to facilitate delegation, designers of robots and robotic agents may consider refraining from using ToM-resemblance features and focusing on balancing user performance perception instead to induce the desired delegation behaviors.
{"title":"Theory of Mind and Delegation to Robotic Virtual Agents","authors":"Ningyuan Sun, J. Botev, Yara Khaluf, P. Simoens","doi":"10.1109/RO-MAN53752.2022.9900789","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900789","url":null,"abstract":"Despite already being commonplace, delegation to robotic virtual agents (VAs) is often considered challenging and error-prone in critical situations by the general public. Theory of mind, the human capacity to take another person's perspective, is deemed an important enabler for human-human cooperation. This study explores the effect of a robotic VA's ability to use theory of mind on users' delegation behavior. To this end, we conducted a between-subjects experiment with participants playing the Colored Trails game with robotic VAs of varying levels of theory of mind. The results invalidate our hypothesis that the ToM level is a reliable indicator of delegation choices. Instead, we found that the participants' performance strongly correlates with their delegatory intentions. Therefore, to facilitate delegation, designers of robots and robotic agents may consider refraining from using ToM-resemblance features and focusing on balancing user performance perception instead to induce the desired delegation behaviors.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125232208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900746
Uma P. Navare, Kyveli Kompatsiari, F. Ciardo, A. Wykowska
When acting together with another human agent, humans form shared representations with their partner in order to predict and adjust to their partner’s behaviors and ensure a smooth and efficient joint action. Previous work has shown that humans do not form shared representations when acting with partners they do not perceive as intentional, such as computers or robots. In the current study, we investigated the effect in the opposite direction: we asked whether engaging in a task with the humanoid robot iCub, in order to achieve a shared goal, could influence the perceived intentionality of the robot. In our study, participants completed a target tracking and detection task with iCub, in which each agent fulfilled different but complementary roles, thus sharing the task. Participants’ likelihood of perceiving the robot as intentional was assessed before and after the interaction. Results showed that participants were more likely to perceive iCub as an intentional agent after they shared the task with it, suggesting that interacting with a robot to achieve a common goal promotes attribution of intentionality toward the robot.
{"title":"Task sharing with the humanoid robot iCub increases the likelihood of adopting the intentional stance","authors":"Uma P. Navare, Kyveli Kompatsiari, F. Ciardo, A. Wykowska","doi":"10.1109/RO-MAN53752.2022.9900746","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900746","url":null,"abstract":"When acting together with another human agent, humans form shared representations with their partner in order to predict and adjust to their partner’s behaviors and ensure a smooth and efficient joint action. Previous work has shown that humans do not form shared representations when acting with partners they do not perceive as intentional, such as computers or robots. In the current study, we investigated the effect in the opposite direction: we asked whether engaging in a task with the humanoid robot iCub, in order to achieve a shared goal, could influence the perceived intentionality of the robot. In our study, participants completed a target tracking and detection task with iCub, in which each agent fulfilled different but complementary roles, thus sharing the task. Participants’ likelihood of perceiving the robot as intentional was assessed before and after the interaction. Results showed that participants were more likely to perceive iCub as an intentional agent after they shared the task with it, suggesting that interacting with a robot to achieve a common goal promotes attribution of intentionality toward the robot.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125111961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900620
Cristina Getson, G. Nejat
The rapid spread of COVID-19 around the globe has increased the need to adopt autonomous social robots within our healthcare systems. In particular, socially assistive robots can help to improve the day-to-day functioning of our healthcare facilities including long-term care, while keeping residents and staff safe by performing repetitive tasks such as health screening. In this paper, we present the first human-robot interaction study with an autonomous multi-task socially assistive robot used for non-contact screening in long-term care homes. The robot monitors temperature, checks for face masks, and asks screening questions to minimize human-to-human contact. We investigated staff perceptions of 7 attributes: screening experience without and with the robot, efficiency, cognitive attitude, freeing up staff, safety, affective attitude, and intent to use the robot. Furthermore, we investigated the influence of demographics on these attributes. Study results show that, overall, staff rated these attributes high for the screening robot, with a statistically significant increase in cognitive attitude and safety after interacting with the robot. Differences between gender and occupation were also determined. Our study highlights the potential application of an autonomous screening robot for long-term care homes.
{"title":"The Robot Screener Will See You Now: A Socially Assistive Robot for COVID-19 Screening in Long-Term Care Homes","authors":"Cristina Getson, G. Nejat","doi":"10.1109/RO-MAN53752.2022.9900620","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900620","url":null,"abstract":"The rapid spread of COVID-19 around the globe has increased the need to adopt autonomous social robots within our healthcare systems. In particular, socially assistive robots can help to improve the day-to-day functioning of our healthcare facilities including long-term care, while keeping residents and staff safe by performing repetitive tasks such as health screening. In this paper, we present the first human-robot interaction study with an autonomous multi-task socially assistive robot used for non-contact screening in long-term care homes. The robot monitors temperature, checks for face masks, and asks screening questions to minimize human-to-human contact. We investigated staff perceptions of 7 attributes: screening experience without and with the robot, efficiency, cognitive attitude, freeing up staff, safety, affective attitude, and intent to use the robot. Furthermore, we investigated the influence of demographics on these attributes. Study results show that, overall, staff rated these attributes high for the screening robot, with a statistically significant increase in cognitive attitude and safety after interacting with the robot. Differences between gender and occupation were also determined. Our study highlights the potential application of an autonomous screening robot for long-term care homes.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125901363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900609
Curtis L Gittens, Ying Jiang, Patrick C. K. Hung
Social robots are increasingly used in different services such as education, hospitality, healthcare, and elderly care. These robots are often adopted to provide people with information and guidance, which sometimes can be quite different from people’s expectations. Therefore, it is important to understand whether similar or dissimilar opinions or attitudes of a focal subject held by the user and robot affects the user’s perception of the robot and future adoption intentions. We propose that robot design (positive facial expressions and verbal sentiments) may moderate the effect of attitude dissimilarity on robot perception. It is well-documented in the psychology literature that attitude similarity affects human-human relationships; however, no such study has been undertaken in human-robot interactions. Our results showed that when the robot expressed its views using a neutral facial expression and verbal sentiment, attitude similarity influenced robot perception, i.e., those participants who had similar (vs. dissimilar) attitudes as the robot perceived the robot to be positive (vs. negative). However, when the robot expressed its opinion with a positive facial expression and verbal sentiment, participants judged the robot as positive regardless of attitude similarity between the user and the robot. These results indicate that positive facial expressions and the verbal sentiment of a robot can nullify any negative effect when a user and a robot share very different opinions.
{"title":"Positive Facial and Verbal Sentiments of a Social Robot Mitigates Negative User Perceptions in Attitudinally Dissimilar Interactions","authors":"Curtis L Gittens, Ying Jiang, Patrick C. K. Hung","doi":"10.1109/RO-MAN53752.2022.9900609","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900609","url":null,"abstract":"Social robots are increasingly used in different services such as education, hospitality, healthcare, and elderly care. These robots are often adopted to provide people with information and guidance, which sometimes can be quite different from people’s expectations. Therefore, it is important to understand whether similar or dissimilar opinions or attitudes of a focal subject held by the user and robot affects the user’s perception of the robot and future adoption intentions. We propose that robot design (positive facial expressions and verbal sentiments) may moderate the effect of attitude dissimilarity on robot perception. It is well-documented in the psychology literature that attitude similarity affects human-human relationships; however, no such study has been undertaken in human-robot interactions. Our results showed that when the robot expressed its views using a neutral facial expression and verbal sentiment, attitude similarity influenced robot perception, i.e., those participants who had similar (vs. dissimilar) attitudes as the robot perceived the robot to be positive (vs. negative). However, when the robot expressed its opinion with a positive facial expression and verbal sentiment, participants judged the robot as positive regardless of attitude similarity between the user and the robot. These results indicate that positive facial expressions and the verbal sentiment of a robot can nullify any negative effect when a user and a robot share very different opinions.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128844829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900771
K. Hindriks, Marijn Hagenaar, A. L. Huckelba
Clothing is often used as a way to communicate about one’s identity. It can provide information about characteristics such as gender, age, occupation, and status as well as more subjective attributes such as trustworthiness and friendliness. In this paper we report on exploratory research that we conducted by means of three studies to investigate the effects of clothing on a Pepper robot. Three outfits that varied in style and colour were compared with each other and the robot without clothing. Findings from an online survey suggest that gender perception but not human-likeness can be manipulated by clothing. We also found that first impressions on expertise and likeability may vary with clothing style and may induce stereotypical job associations. In a second study, we interviewed experts which were all familiar with the Pepper platform to obtain a more qualitative perspective on robot clothing. The interviews made clear that specific features of clothing may trigger strong associations with, for example, occupations, and that features such as headdress may make an outfit look more like a uniform. Finally, we conducted a field experiment comparing two clothing conditions for a receptionist robot in a natural setting and found that a robot with uniform appears to be more engaging. Our findings suggest that robot clothing may have an effect on first impressions, gender perception, and engagement in interactions with users in the wild.
{"title":"Effects of Robot Clothing on First Impressions, Gender, Human-Likeness, and Suitability of a Robot for Occupations","authors":"K. Hindriks, Marijn Hagenaar, A. L. Huckelba","doi":"10.1109/RO-MAN53752.2022.9900771","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900771","url":null,"abstract":"Clothing is often used as a way to communicate about one’s identity. It can provide information about characteristics such as gender, age, occupation, and status as well as more subjective attributes such as trustworthiness and friendliness. In this paper we report on exploratory research that we conducted by means of three studies to investigate the effects of clothing on a Pepper robot. Three outfits that varied in style and colour were compared with each other and the robot without clothing. Findings from an online survey suggest that gender perception but not human-likeness can be manipulated by clothing. We also found that first impressions on expertise and likeability may vary with clothing style and may induce stereotypical job associations. In a second study, we interviewed experts which were all familiar with the Pepper platform to obtain a more qualitative perspective on robot clothing. The interviews made clear that specific features of clothing may trigger strong associations with, for example, occupations, and that features such as headdress may make an outfit look more like a uniform. Finally, we conducted a field experiment comparing two clothing conditions for a receptionist robot in a natural setting and found that a robot with uniform appears to be more engaging. Our findings suggest that robot clothing may have an effect on first impressions, gender perception, and engagement in interactions with users in the wild.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127623047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900572
Huao Li, Ini Oguntola, Dana Hughes, Michael Lewis, K. Sycara
Theory of Mind (ToM) refers to the ability to make inferences about other’s mental states. Such ability is fundamental for human social activities such as empathy, teamwork, and communication. As intelligent agents come to be involved in diverse human-agent teams, they will also be expected to be socially intelligent in order to become effective teammates. In this paper, we describe a computational ToM model which observes team behaviors and infers their mental states in a urban search and rescue (US&R) task. Our modular ToM model approximates human inference by explicitly representing beliefs, belief updates, and action prediction/generation using Deep Neural Networks (DNNs). To validate our model we compare its performance to the gold standard of human observers asked to make the same inferences. The ToM model proved superior to the average judgments of human observers on all four tests of inference and better than 90th percentile observers on three of the four. While the learning bias provided by modularizing belief and prediction proved sufficient for the simple inferences tested, substantial refinement will be needed to replicate the complex nuanced chains of inference observed in human social interaction.
心理理论(Theory of Mind, ToM)是指推断他人心理状态的能力。这种能力是人类社会活动的基础，比如移情、团队合作和沟通。随着智能代理参与到不同的人类代理团队中，他们也将被期望具有社会智能，以便成为有效的团队成员。本文描述了一个观察城市搜救任务中团队行为并推断其心理状态的计算ToM模型。我们的模块化ToM模型通过使用深度神经网络(dnn)显式表示信念、信念更新和动作预测/生成来近似人类推理。为了验证我们的模型，我们将其性能与被要求做出相同推断的人类观察者的黄金标准进行比较。ToM模型在所有四项推理测试中都优于人类观察者的平均判断，并且在四项测试中的三项测试中优于90百分位观察者。虽然模块化信念和预测提供的学习偏差对于测试的简单推理是足够的，但需要大量的改进来复制在人类社会互动中观察到的复杂细致的推理链。
{"title":"Theory of Mind Modeling in Search and Rescue Teams","authors":"Huao Li, Ini Oguntola, Dana Hughes, Michael Lewis, K. Sycara","doi":"10.1109/RO-MAN53752.2022.9900572","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900572","url":null,"abstract":"Theory of Mind (ToM) refers to the ability to make inferences about other’s mental states. Such ability is fundamental for human social activities such as empathy, teamwork, and communication. As intelligent agents come to be involved in diverse human-agent teams, they will also be expected to be socially intelligent in order to become effective teammates. In this paper, we describe a computational ToM model which observes team behaviors and infers their mental states in a urban search and rescue (US&R) task. Our modular ToM model approximates human inference by explicitly representing beliefs, belief updates, and action prediction/generation using Deep Neural Networks (DNNs). To validate our model we compare its performance to the gold standard of human observers asked to make the same inferences. The ToM model proved superior to the average judgments of human observers on all four tests of inference and better than 90th percentile observers on three of the four. While the learning bias provided by modularizing belief and prediction proved sufficient for the simple inferences tested, substantial refinement will be needed to replicate the complex nuanced chains of inference observed in human social interaction.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127737087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900528
Wyke J P Stommel, Lynn de Rijk, Roel Boumans
This article analyzes various kinds of interactional trouble occurring in task-oriented human-robot interaction. We focus on users' repair strategies, typically used for maintaining communication in social interaction. We use an existing dataset consisting of 36 video-recordings of elderly people completing a lengthy health survey with a Pepper robot. Miscommunication was abundant in the data, with some types of repair being more common than others. These were mainly related to "hearing trouble" on the side of the robot, leading to participants’ repeats and rephrasings. Interactional trouble was also found to escalate, with multiple repair initiations, sometimes leading to "second best answers". This appeared to be a strategy for participants to avoid repair in the service of progressivity. Overall, miscommunication and repair in these task-oriented human-robot interactions require substantial adaptation from the human.
{"title":"“Pepper, what do you mean?” Miscommunication and repair in robot-led survey interaction","authors":"Wyke J P Stommel, Lynn de Rijk, Roel Boumans","doi":"10.1109/RO-MAN53752.2022.9900528","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900528","url":null,"abstract":"This article analyzes various kinds of interactional trouble occurring in task-oriented human-robot interaction. We focus on users' repair strategies, typically used for maintaining communication in social interaction. We use an existing dataset consisting of 36 video-recordings of elderly people completing a lengthy health survey with a Pepper robot. Miscommunication was abundant in the data, with some types of repair being more common than others. These were mainly related to \"hearing trouble\" on the side of the robot, leading to participants’ repeats and rephrasings. Interactional trouble was also found to escalate, with multiple repair initiations, sometimes leading to \"second best answers\". This appeared to be a strategy for participants to avoid repair in the service of progressivity. Overall, miscommunication and repair in these task-oriented human-robot interactions require substantial adaptation from the human.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129715985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900810
Mihai Dragusanu, Danilo Troisi, A. Villani, D. Prattichizzo, M. Malvezzi
Nowadays, especially with the Covid-19 pandemic, researchers are focusing their attention on the remote delivery of devices designed for rehabilitation purposes, allowing people to recover without the physical presence of a doctor. Manual therapy is a physical treatment that is used by therapists for the treatment of musculoskeletal pain and/or disabilities. The aim of this work is to present HAPP, a new haptic portable device, designed to help patients suffering of different patholohgies, as for instance the Complex Regional Pain Syndrome type-I disease, and more in general to investigate the effects of manual therapy for diseases of the carpus and metacarpus, by mimicking traditional mechanical and rhythmic stimuli characteristics of manual treatments. Its structure consists of a plate oriented by revolute-prismatic-spherical joints, with a rack-pinion mechanism that actuates the end-effector, stimulating the user’s hand palm. We provide details about the device, such as the mechanical design, the mathematical model and a graphical user interface. Preliminary studies in order to evaluate the device force exerted at the user’s palm were carried out.
{"title":"HAPP: a Haptic Portable Pad for Hand Disease Manual Treatment","authors":"Mihai Dragusanu, Danilo Troisi, A. Villani, D. Prattichizzo, M. Malvezzi","doi":"10.1109/RO-MAN53752.2022.9900810","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900810","url":null,"abstract":"Nowadays, especially with the Covid-19 pandemic, researchers are focusing their attention on the remote delivery of devices designed for rehabilitation purposes, allowing people to recover without the physical presence of a doctor. Manual therapy is a physical treatment that is used by therapists for the treatment of musculoskeletal pain and/or disabilities. The aim of this work is to present HAPP, a new haptic portable device, designed to help patients suffering of different patholohgies, as for instance the Complex Regional Pain Syndrome type-I disease, and more in general to investigate the effects of manual therapy for diseases of the carpus and metacarpus, by mimicking traditional mechanical and rhythmic stimuli characteristics of manual treatments. Its structure consists of a plate oriented by revolute-prismatic-spherical joints, with a rack-pinion mechanism that actuates the end-effector, stimulating the user’s hand palm. We provide details about the device, such as the mechanical design, the mathematical model and a graphical user interface. Preliminary studies in order to evaluate the device force exerted at the user’s palm were carried out.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129902803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900758
N. Yun, S. Yamada
Today, people are enjoying using teleconference systems like Zoom or Skype for social communication or for having drinks through a screen with others via the internet. In addition, some people have started using embodied systems called telepresence robots, such as the Beam robot. Some schools have started using telepresence robots so that students can attend school. However, in previous studies, systems have not been compared in terms of social presence and anthropomorphism, for example, robots compared with humans. Therefore, we wondered how the presence and anthropomorphism of such systems affect people. Therefore, we carried out a web-based experiment and conducted a one-way ANOVA (smartphone vs. telepresence robot with motion vs. without motion). Some people feel that telepresence robots bring a feeling of presence to remote places. Ironically, from the results, a video teleconference system using a smartphone and a telepresence robot did not create a feeling of presence, but regarding anthropomorphism, participants felt more of a human-likeness in the video teleconference system.
{"title":"Physical embodiment vs. smartphone: which influences presence and anthropomorphism most in telecommunication?","authors":"N. Yun, S. Yamada","doi":"10.1109/RO-MAN53752.2022.9900758","DOIUrl":"https://doi.org/10.1109/RO-MAN53752.2022.9900758","url":null,"abstract":"Today, people are enjoying using teleconference systems like Zoom or Skype for social communication or for having drinks through a screen with others via the internet. In addition, some people have started using embodied systems called telepresence robots, such as the Beam robot. Some schools have started using telepresence robots so that students can attend school. However, in previous studies, systems have not been compared in terms of social presence and anthropomorphism, for example, robots compared with humans. Therefore, we wondered how the presence and anthropomorphism of such systems affect people. Therefore, we carried out a web-based experiment and conducted a one-way ANOVA (smartphone vs. telepresence robot with motion vs. without motion). Some people feel that telepresence robots bring a feeling of presence to remote places. Ironically, from the results, a video teleconference system using a smartphone and a telepresence robot did not create a feeling of presence, but regarding anthropomorphism, participants felt more of a human-likeness in the video teleconference system.","PeriodicalId":250997,"journal":{"name":"2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)","volume":"13 13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129486396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-29DOI: 10.1109/RO-MAN53752.2022.9900589
Lennart Wachowiak, Peter Tisnikar, Gerard Canal, A. Coles, M. Leonetti, O. Çeliktutan
As human–agent collaborations become more prevalent, it is increasingly important for an agent to be able to adapt to their collaborator and explain their own behavior. In order to do so, they need to be able to identify critical states during the interaction that call for proactive clarifications or behavioral adaptations. In this paper, we explore whether the agent could infer such states from the human’s eye gaze for which we compare gaze patterns across different situations in a collaborative task. Our findings show that the human’s gaze patterns significantly differ between times at which the user is confused about the task, times at which the agent makes an error, and times of normal workflow. During errors the amount of gaze towards the agent increases, while during confusion the amount towards the environment increases. We conclude that these signals could tell the agent what and when to explain.
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