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MoTiS Parameters for Expressive Multi-robot Systems: Relative Motion, Timing, and Spacing

INTERNATIONAL JOURNAL OF SOCIAL robotICS 2022年第9期14卷 1965-1993页

作者： Bacula, A. Knight, H. Oregon State Univ Collaborat Robot & Intelligent Syst Inst Corvallis OR 97331 USA

Multi-robot systems are moving into human spaces, such as working with people in factories (Bacula et al., in: Companion of the 2020 acm/ieee international conference on human-robot interaction, pp 119-121, 2020) or in emergency support (Wagner in Front robot AI 8, 2021;Baxter et al., in: Autonomous robots and agents, Springer, pp 9-16, 2007) and it is crucial to consider how robots can communicate with the humans in the space. Our work evaluates a parameter framework to allow multi-robot groups of x, y, theta robots to effectively communicate using expressive motion. While expressive motion has been extensively studied in single robots (Knight et al., in: 2016 ieee international conference on intelligent robots and systems (EROS), ieee, 2016;Bacula and LaViers in Int J Soc robot, 1-16, 2020;Dragan et al., in: 2013 8th acm/ieee international conference on human-robot interaction (hri), WF.F, pp 301-308, 2013;Kirby et al., in: The 18th JEFF international symposium on robot and human interactive communication, 2009, RO-MAN 2009, ieee, pp 607-612, 2009), moving to multi-robots creates new challenges as the state space expands and becomes more complex. We evaluate a hierarchical framework of six parameters to generate multi-robot expressive motion consisting of: (1) relative direction, (2) coherence, (3) relative speed, (4) relative start time, (5) proximity, and (6) geometry. We conducted six independent online studies to explore each parameter, finding that four out of six of the parameters had significant impact on people's perception of the multi-robot group. Additional takeaways of our studies clarify what humans interpret as a robot group, when the group is perceived positively versus negatively, and the critical role of architectural floor plan in interpreting robot intent.

关键词： Expressivity Multi-robot systems Social robotics human-robot interaction

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Towards Unlimited Task Coverage and Direct (far-off) Manipulation in eXtended Reality Remote Collaboration 24

Towards Unlimited Task Coverage and Direct (far-off) Manipul...

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19th Annual acm/ieee International conference on human-robot interaction, hri 2024

作者： Marques, Bernardo Silva, Samuel Pedrosa, Eurico Barros, Fábio Teixeira, António Santos, Beatriz Sousa IEETA DETI LASI University of Aveiro Aveiro Portugal

ISBN: (纸本)9798400703232

The growing interest in remote collaboration is driven by multiple factors. Advances in digital technology have made it increasingly feasible to collaborate from anywhere, breaking down geographical barriers. Despite the rise of new tools several challenges still exist. These include limitations on the remote member's perspective, confined to what on-site members can capture, as well as potential shortcomings for interacting with on-site physical objects. This position paper discusses the potential of leveraging mobile robots within eXtended Reality (XR) environments to transform how remote collaboration is performed. Mobile robots, equipped with cameras, microphones, articulated arms and various sensors, can serve as physical avatars for remote team members, allowing to navigate through physical spaces, enabling real-time, immersive experiences. Combined with XR tools, these robots may empower on-site and remote collaborators to engage in shared activities. These and other arguments in favor of this position are presented and future directions are proposed. © 2024 Copyright held by the owner/author(s)

关键词： conceptual model extended reality human-robot collaboration human-robot interaction mobile robots remote collaboration

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Trust-aware planning: Modeling trust evolution in iterated human-robot interaction 23

Trust-aware planning: Modeling trust evolution in iterated h...

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18th Annual acm/ieee International conference on human-robot interaction, hri 2023

作者： Zahedi, Zahra Verma, Mudit Sreedharan, Sarath Kambhampati, Subbarao Arizona State University United States Colorado State University United States

ISBN: (纸本)9781450399647

Trust between team members is an essential requirement for any successful cooperation. Thus, engendering and maintaining the fellow team members' trust becomes a central responsibility for any member trying to not only successfully participate in the task but to ensure the team achieves its goals. The problem of trust management is particularly challenging in mixed human-robot teams where the human and the robot may have diferent models about the task at hand and thus may have diferent expectations regarding the current course of action, thereby forcing the robot to focus on the costly explicable behavior. We propose a computational model for capturing and modulating trust in such iterated human-robot interaction settings, where the human adopts a supervisory role. In our model, the robot integrates human's trust and their expectations about the robot into its planning process to build and maintain trust over the interaction horizon. By establishing the required level of trust, the robot can focus on maximizing the team goal by eschewing explicit explanatory or explicable behavior without worrying about the human supervisor monitoring and intervening to stop behaviors they may not necessarily understand. We model this reasoning about trust levels as a meta reasoning process over individual planning tasks. We additionally validate our model through a human subject experiment. © 2023 Association for Computing Machinery.

关键词： Decision making

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Raising Stars: Influences of robotic Peer Liking on Emergent Leadership 25

Raising Stars: Influences of Robotic Peer Liking on Emergent...

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acm/ieee International conference on human-robot interaction (hri)

作者： Elior Carsenti Adi Manor Agam Oberlender Avi Parush Hadas Erel Media Innovation Lab Reichman University Israel Faculty of Data and Decision Sciences Technion Israel

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

Emergent leadership in teams is known as a special type of informal leadership that has unique benefits. Given that this form of leadership can be developed only organically from within the team, an informal leader may not emerge and the associated advantages can be missed. We explored the possibility of leveraging robotic social behavior to facilitate the emergence of leadership in a team. We evaluated whether a robot displaying explicit peer liking towards a specific team member would encourage that team member to take the lead. Two (stranger) participants were asked to engage in a search task together with a robotic dog who either presented peer-liking behavior toward one or both of them during the opening encounter. Our findings suggest that the robot's peer liking led the “Liked” participant to report higher sense of leadership and higher sense of responsibility over the task. Behavioral measures also indicated that the “Liked” participant managed the team's performance. We suggest that integrating a robot into human teams presents an opportunity to facilitate unique dynamics that would not develop when imposing a structure on the team from the outside.

关键词： Leadership Shape Atmospheric measurements human-robot interaction Stars Dogs robot sensing systems Particle measurements

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robot Gaze Can Mediate Participation Imbalance in Groups with Different Skill Levels 21

Robot Gaze Can Mediate Participation Imbalance in Groups wit...

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16th acm/ieee International conference on human-robot interaction (hri)

作者： Gillet, Sarah Cumbal, Ronald Pereira, Andre Lopes, Jose Engwall, Olov Leite, Iolanda KTH Royal Inst Technol Stockholm Sweden Heriot Watt Univ Edinburgh Scotland

ISBN: (纸本)9781450382892

Many small group activities, like working teams or study groups, have a high dependency on the skill of each group member. Differences in skill level among participants can affect not only the performance of a team, but also influence the social interaction of its members. In these circumstances, an active member could balance individual participation without exerting direct pressure on specific members by using indirect means of communication, such as gaze behaviors. Similarly, in this study, we evaluate whether a social robot can balance the level of participation in a language skill-dependent game, played by a native speaker and a second language learner. In a between-subjects study (N = 72), we compared an adaptive robot gaze behavior, that was targeted to increase the level of contribution of the least active player, with a non-adaptive gaze behavior. Our results imply that, while overall levels of speech participation were influenced predominantly by personal traits of the participants, the robot's adaptive gaze behavior could shape the interaction among participants which lead to more even participation during the game.

关键词： Multiparty interaction gaze group dynamics language learning

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robot gaze can mediate participation imbalance in groups with diferent skill levels

Robot gaze can mediate participation imbalance in groups wit...

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2021 acm/ieee International conference on human-robot interaction, hri 2021

作者： Gillet, Sarah Cumbal, Ronald Pereira, André Lopes, José Engwall, Olov Leite, Iolanda KTH Royal Institute of Technology Stockholm Sweden Heriot-Watt University Edinburgh United Kingdom

ISBN: (纸本)9781450382892

Many small group activities, like working teams or study groups, have a high dependency on the skill of each group member. Differences in skill level among participants can afect not only the performance of a team, but also infuence the social interaction of its members. In these circumstances, an active member could balance individual participation without exerting direct pressure on specifc members by using indirect means of communication, such as gaze behaviors. Similarly, in this study, we evaluate whether a social robot can balance the level of participation in a language skill-dependent game, played by a native speaker and a second language learner. In a between-subjects study (N = 72), we compared an adaptive robot gaze behavior, that was targeted to increase the level of contribution of the least active player, with a non-adaptive gaze behavior. Our results imply that, while overall levels of speech participation were infuenced predominantly by personal traits of the participants, the robot's adaptive gaze behavior could shape the interaction among participants which lead to more even participation during the game. © 2021 ieee Computer Society. All rights reserved.

关键词： Gaze Group dynamics Language learning Multiparty interaction

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Strategies for the Inclusion of human members within human-robot teams 20

Strategies for the Inclusion of Human Members within Human-R...

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acm/ieee International conference on human-robot interaction (hri)

作者： Sebo, Sarah Strohkorb Dong, Ling Liang Chang, Nicholas Scassellati, Brian Yale Univ New Haven CT 06520 USA

ISBN: (纸本)9781450367462

team member inclusion is vital in collaborative teams. In this work, we explore two strategies to increase the inclusion of human team members in a human-robot team: 1) giving a person in the group a specialized role (the 'robot liaison') and 2) having the robot verbally support human team members. In a human subjects experiment (N = 26 teams, 78 participants), groups of three participants completed two rounds of a collaborative task. In round one, two participants (ingroup) completed a task with a robot in one room, and one participant (outgroup) completed the same task with a robot in a different room. In round two, all three participants and one robot completed a second task in the same room, where one participant was designated as the robot liaison. During round two, the robot verbally supported each participant 6 times on average. Results show that participants with the robot liaison role had a lower perceived group inclusion than the other group members. Additionally, when outgroup members were the robot liaison, the group was less likely to incorporate their ideas into the group's final decision. In response to the robot's supportive utterances, outgroup members, and not ingroup members, showed an increase in the proportion of time they spent talking to the group. Our results suggest that specialized roles may hinder human team member inclusion, whereas supportive robot utterances show promise in encouraging contributions from individuals who feel excluded.

关键词： human-robot interaction Inclusion Groups and teams

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robot Gaze Can Mediate Participation Imbalance in Groups with Different Skill Levels

Robot Gaze Can Mediate Participation Imbalance in Groups wit...

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acm/ieee International conference on human-robot interaction (hri)

作者： Sarah Gillet Ronald Cumbal André Pereira José Lopes Olov Engwall Iolanda Leite KTH Royal Institute of Technology Stockholm Sweden Heriot-Watt University Edinburgh United Kingdom

ISBN: (纸本)9798350321500

Many small group activities, like working teams or study groups, have a high dependency on the skill of each group member. Differences in skill level among participants can affect not only the performance of a team, but also influence the social interaction of its members. In these circumstances, an active member could balance individual participation without exerting direct pressure on specific members by using indirect means of communication, such as gaze behaviors. Similarly, in this study, we evaluate whether a social robot can balance the level of participation in a language skill-dependent game, played by a native speaker and a second language learner. In a between-subjects study (N=72), we compared an adaptive robot gaze behavior, that was targeted to increase the level of contribution of the least active player, with a non-adaptive gaze behavior. Our results imply that, while overall levels of speech participation were influenced predominantly by personal traits of the participants, the robot’s adaptive gaze behavior could shape the interaction among participants which lead to more even participation during the game.

关键词： Shape Social robots Games Real-time systems Behavioral sciences Mediation robots

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Strategies for the Inclusion of human members within human-robot teams

Strategies for the Inclusion of Human Members within Human-R...

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acm/ieee International conference on human-robot interaction (hri)

作者： Sarah Strohkorb Sebo Ling Liang Dong Nicholas Chang Brian Scassellati Yale University New Haven CT

team member inclusion is vital in collaborative teams. In this work, we explore two strategies to increase the inclusion of human team members in a human-robot team: 1) giving a person in the group a specialized role (the ‘robot liaison’) and 2) having the robot verbally support human team members. In a human subjects experiment $( _{N}\,_{=}\,26$ teams, 78 participants), groups of three participants completed two rounds of a collaborative task. In round one, two participants (ingroup) completed a task with a robot in one room, and one participant (outgroup) completed the same task with a robot in a different room. In round two, all three participants and one robot completed a second task in the same room, where one participant was designated as the robot liaison. During round two, the robot verbally supported each participant 6 times on average. Results show that participants with the robot liaison role had a lower perceived group inclusion than the other group members. Additionally, when outgroup members were the robot liaison, the group was less likely to incorporate their ideas into the group’s final decision. In response to the robot’s supportive utterances, outgroup members, and not ingroup members, showed an increase in the proportion of time they spent talking to the group. Our results suggest that specialized roles may hinder human team member inclusion, whereas supportive robot utterances show promise in encouraging contributions from individuals who feel excluded. CCS CONCEPTS •human-centeredcomputing → Userstudies; Empiricalstudies in collaborative and social computing. acm Reference Format: Sarah Strohkorb Sebo, Ling Liang Dong, Nicholas Chang, and Brian Scassellati. 2020. Strategies for the Inclusion of human members within human-robot teams. In Proceedings of the 2020 acm/ieee International conference on human-robot interaction (hri ’20), March 23–26, 2020, Cambridge,United Kingdom. acm, New York, NY, USA, 9 pages. https://***/10.1145/3319502.3374

关键词： Social computing Collaboration human-robot interaction Task analysis robots

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Multi-Armed Bandits with Fairness Constraints for Distributing Resources to human teammates

Multi-Armed Bandits with Fairness Constraints for Distributi...

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acm/ieee International conference on human-robot interaction (hri)

作者： Houston Claure Yifang Chen Jignesh Modi Malte Jung Stefanos Nikolaidis Cornell University Ithaca New York University of Southern California Los Angeles California

How should a robot that collaborates with multiple people decide upon the distribution of resources (e.g. social attention, or parts needed for an assembly)? People are uniquely attuned to how resources are distributed. A decision to distribute more resources to one team member than another might be perceived as unfair with potentially detrimental effects for trust. We introduce a multi-armed bandit algorithm with fairness constraints, where a robot distributes resources to human teammates of different skill levels. In this problem, the robot does not know the skill level of each human teammate, but learns it by observing their performance over time. We define fairness as a constraint on the minimum rate that each human teammate is selected throughout the task. We provide theoretical guarantees on performance and perform a large-scale user study, where we adjust the level of fairness in our algorithm. Results show that fairness in resource distribution has a significant effect on users’ trust in the system. acm Reference Format: Houston Claure, Yifang Chen, Jignesh Modi, Malte Jung, and Stefanos Nikolaidis. 2020. Multi-Armed Bandits with Fairness Constraints for Distributing Resources to human teammates. In Proceedings of the 2020acm/ieee International conference on human-robot interaction (hri’20), March 23-26, 2020, Cambridge, United Kingdom. acm, New York, NY, USA, 10 pages. https://***/10.1145/3319502.3374806

关键词： robotic assembly human-robot interaction Games Resource management Task analysis robots Faces

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