Toward Designing Social Human-Robot Interactions for Deep Space Exploration

Huili Chen Cynthia Breazeal MIT Media Lab MIT Media Lab [email protected] [email protected]

ABSTRACT sleep deprivation, decrease in group cohesion, and decrease in mo- In planning for future human space exploration, it is important to tivation [8]. On the team level, factors related to interpersonal consider how to design for uplifting interpersonal communications communications and group dynamics among astronauts also deci- and social dynamics among crew members. What if embodied social sively impact mission success. For example, astronauts will have to robots could help to improve the overall team interaction experi- live in an ICE condition for the entirety of the mission, necessitating ence in space? On Earth, social robots have been shown effective group living skills to combat potential interpersonal problems [11]. in providing companionship, relieving stress and anxiety, fostering Their diverse cultural backgrounds may additionally impact coping connection among people, enhancing team performance, and medi- in an ICE environment and interplanetary crew’s behavior [49]. ating conflicts in human groups. In this paper, we introduce asetof Unlike shorter-duration space missions, LDSE missions require as- novel research questions exploring social human-robot interactions tronauts to have an unprecedented level of autonomy, leading to in long-duration space exploration missions. greater importance of interpersonal communication among crew members for mission success. The real-time support and interven- KEYWORDS tions from human specialists on Earth (e.g., psychologist, doctor, conflict mediator) are reduced to minimal due to costly communi- Human-robot Interaction, Long-duration Human Space Mission, cation and natural delays in communication between space and Space Robot Companion, Social Connection Earth. All these human factor risks could lead to serious detrimental ACM Reference Format: impacts on a LDSE mission if left unmitigated. To address them, Huili Chen and Cynthia Breazeal. 2021. Toward Designing Social Human- socially interactive technologies such as social robots offer great Robot Interactions for Deep Space Exploration. In CHI ’21 workshop SpaceCHI: opportunities of delivering effective interventions. Human-Computer Interaction for Space Exploration. 5 pages. 1.2 Human-robot Interaction (HRI) in Space 1 INTRODUCTION Exploration 1.1 Human Factors in LDSE Missions In the past decades, most research on HRI in space exploration NASA is actively planning for long-duration space exploration focused on the engineering and cognitive aspects of space robot- (LDSE) missions such as an anticipated manned mission to Mars in ics. Space robots were often envisioned with advanced cognitive the 2030s [33]. In planning for future LDSE missions, one major risk systems (e.g.,CARACaS) capable of model building, continuous area pertaining to human factors concerns the ability of astronauts planning/re-planning, self-diagnosis, and novel situation under- to adapt to the isolated, confined, and extreme (ICE) conditions [34]. standing [15]. These space robots could assist crew members with a Living in ICE conditions for a long duration is highly stressful. The variety of physical and cognitive tasks, but they did not necessarily psycho-environmental factors of living and working in such ICE support social and affective communications with crew members. environments, as documented by studies of these ICE analogues In recent years, sociable space robots started to emerge, able to and evidence from past spaceflights, include crowding, lack of pri- display and recognize social cues. An in-cabin flying robot named vacy, social isolation, and sensory restriction [35, 36]. The sense Astronaut Assistant Robot (AAR) [24] allows astronauts to use hand of isolation will become further heightened with longer distances gestures to communicate with it face-to-face [12]. As the first free- arXiv:2105.08631v1 [cs.RO] 18 May 2021 from Earth and communication lag with Earth [34]. floating, sphere-shaped interactive companion robot in space, Crew To ensure the success of a LDSE mission, adaptation is needed Interactive Mobile Companion (CIMON) designed by NASA and for both individual astronauts and the crew team as a whole. On IBM [31] can display human-like facial expressions on its screen the individual level, astronauts will need to cope with a variety and respond to voice questions or directions without the need for a of observed behavioral, physiological and psychological problems tablet or computer when assisting astronauts in their daily work. including anger, anxiety, interpersonal conflict, social withdrawal, The potential benefits of social robots in space are also suggested by prior HRI work conducted on Earth, which found social robots Permission to make digital or hard copies of part or all of this work for personal or effective in improving people’s mental health and well-being [39] classroom use is granted without fee provided that copies are not made or distributed as well as human group dynamics and team performance [41]. In for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. LDSE missions, the needs of astronauts for social robots will very For all other uses, contact the owner/author(s). likely become heightened given the LDSE-related human factor CHI ’21 Workshop SpaceCHI, May 8-13, 2021, Yokohama, Japan (Online Virtual Confer- risks listed in Section 1.1, thereby providing a greater motivation ence) © 2021 Copyright held by the owner/author(s). for more research on social HRI in space. In this paper, we focus on the opportunity of using social robots as a multimodal medium for CHI ’21 Workshop SpaceCHI, May 8-13, 2021, Yokohama, Japan (Online Virtual Conference) Huili Chen and Cynthia Breazeal ameliorating interpersonal communications and group dynamics design situates a robot as a passive entity in a group. For example, of crew members in LDSE missions. a robotic microphone that exhibits implicit engagement behaviors (e.g., nonverbal backchanneling) in a group problem solving context 2 SOCIAL HRI ON EARTH encouraged more active participation from passive human members 2.1 Robot Social Roles in Human Groups and promoted more effective group collaboration performance [50]. As shown above, a robot’s social influence on human groups can be Social robots can play a variety of roles ranging from highly knowl- achieved through both its use of speech and nonverbal social cues. edgeable agents to social-emotional companions across human Nevertheless, an excessive or inappropriate display of social cues group interaction contexts. When engaging with a human group may distract or interrupt humans in some circumstances [18, 55]. as a highly knowledgeable agent and expert in a task area, a social For example, the frequency and length of a robot’s speech affected robot, for example, can provide counseling to couples [53], offer humans’ interaction outcomes more significantly than its content direction guide in public space [9], host group game activities [56], due to the disturbing effects of the inappropriate speech display [17, and allocate turns to players [3]. In contrast to an expert role, a 45]. Penalizing high frequency of speech as the “communication robot can take a peer role that strategically displays its vulnerability cost” can yield more effective human-robot communication52 [ ]. or emotions with the goal of ameliorating human group dynamics. For nonverbal behaviors, a robot’s congruent display of social cues, For example, a robot Kip1 was designed as a peripheral conversation e.g., contingent gaze and pointing gestures, can elicit greater human companion that promotes non-aggressive conversation between participation in an interaction [26], while the asynchrony of social people by expressing either curious interest or fear via its gesture cues, e.g. robot head-gazes and pointing gestures made in different cues [14]. Similarly, vulnerable statements made by a robot in a directions, may lead to interference effects and slow down human human group can positively impact the dynamics and collaboration processing time [20, 21]. among the group members (e.g., more equal conversation distribu- Hence, understanding the relations between the display of robot tion and more positive group perception [51]). social behaviors and interaction contexts is crucial for designing In addition to the expert and social-emotional companion roles, successful multi-party HRI. a robot can take a mediator role to directly resolve human team con- flicts. For example, a social robot can improve people’s interpersonal 2.3 Human Trust in Robots conflict resolution skills by flagging a conflict onset and offering prompts for conflict resolution [43]. Mediation via the Telenoid Trust is a result of dynamic interactions [29]. Successful interac- robot was also found to produce more agreements and more inte- tions will lead to feelings of security, trust and optimism, while grative agreements among human teammates in comparison with failed interactions may result in human’s unsecured feelings or mis- both a screen mediator and a human mediator [6]. The last social trust. Much empirical evidence shows trust essential for successful role category that a robot often takes in a human group is a moder- human-human interactions [30]. In human-robot interactions, hu- ator/supporter role. When taking this role, a robot could improve a mans’ trust in robots also plays a critical role such as influencing human group’s social dynamics [46] and a dyadic human team’s their willingness to accept information from robots [13] and to performance on a collaborative task by posing questions [48]. cooperate with robots [10]. A person’s trust in a robot is often in- Overall, a robot’s social role in a human group interaction dis- tertwined with the robot’s task performance, display of nonverbal tinctly shapes how humans interact with each other and how they behaviors, and interaction personalization. A single error of the perceive the robot. robot can impact humans’ trust of it, especially in critical situa- tions [37]. If a robot displays nonverbal signals that humans often 2.2 Robot Social Behaviors in Human Groups exhibit to indicate distrust, the robot would also be perceived as less trustworthy [5]. In the context of workplace-based long-term Both of a robot’s verbal and nonverbal social behaviors can posi- HRI, a personalized human-robot discussion was found to increase tively influence human groups when displayed appropriately, though the person’s rapport and cooperation with the robot as compared in their unique ways. Specifically, a robot’s verbal communication with a social but not personalized discussion [22]. Humans’ trust can support its expressions of emotion [4, 23] and share informa- in robots, given its importance in HRIs, is often used as an evalua- tional content [38] with humans. It can also improve a variety of tion measure on robot decision making [2] and human-robot team affective phenomena in human-human interactions such as trust effectiveness [10] across contexts and tasks. building [4], group engagement [27], psychological safety of out- group team members [40], equality and positivity within conversa- 3 FUTURE SOCIAL HRI IN SPACE tional groups [51], and the inclusion of human members within a team [42]. EXPLORATION In addition to its verbal utterances, a robot’s nonverbal behaviors Despite extensive HRI research conducted on Earth, we barely know such as gestures [25], gaze [32, 47] navigation [19, 28], and physical to what extent these prior findings can be readily applied to the orientation [44, 54] can influence people’s responses in a group deep space exploration context. Contextualizing the HRI research interaction and their perception of the group [41]. For example, in LDSE missions would unlock the full potential of using social robots were designed, in some interactions [7, 50], as peripheral robots to foster positive interpersonal communications and social or passive entities that shaped human group dynamics via implicit dynamics among crew members in future space exploration. Hence, nonverbal behaviors without eliciting users’ awareness. Often in- we propose a set of key design questions (DQ) pertaining to social spired by Ju’s theory of implicit interactions [16], this alternative HRI in space. Toward Designing Social Human-Robot Interactions for Deep Space Exploration CHI ’21 Workshop SpaceCHI, May 8-13, 2021, Yokohama, Japan (Online Virtual Conference)

3.1 Robot Social Role Design When interacting with a human group, social robots have been tak- ing a variety of roles from resource providers to listeners, each of which offers unique benefits contingent on the interaction context. However, barely any prior work focused on the design and impact of robot roles on the group dynamics and processes of space crew teams, posing a new urgency to investigate the nuanced challenges for social HRI in space. For example, a robot mediator has been empirically shown to resolve people’s interpersonal conflicts more effectively than a screen mediator or a human mediator [6], but the design considerations for a robot mediation in astronaut-astronaut interactions remain unexplored. Understanding astronauts’ percep- (a) Robot Role Switching tion, acceptance and needs of social robots in different LDSE-related interaction contexts would help design for more astronaut-centered HRI. Therefore, we propose the first two research questions as fol- lows:

• DQ1: What robot interactions would astronauts perceive to be socially, cognitively and affectively beneficial to the crew team in a LDSE mission? • DQ2: How would individual characteristics and cultural backgrounds of astronauts affect their perception, accep- tance and preference of social HRI in space?

In LDSE missions, crew members engage in a variety of group interactions ranging from highly-critical team cooperation and ur- (b) Robot Identity Switching gent problem-solving meetings to leisure and recreational activities. In these activities, the crew team’s social dynamics may vary as Figure 1: Two design approaches to address the constraint the social roles of the members are adaptive to the context, e.g., on robot hardware resources in LDSE missions. superior-subordinate communication and peer interaction. The way • a social robot engages with the team should thus be contingent on DQ6: How would the aforementioned role-switching and the team’s social dynamics. Designing a diverse set of robot social identity-switching approaches influence astronauts’ percep- roles customized to different group interaction contexts could po- tion and acceptance of robot interactions such as their trust tentially promote the overall positive astronaut-robot interaction in robots? experience in space. We summarize this research topic as follows: 3.2 Robot Social Behavior Design • DQ3: What robot role(s) could be designed for each crew Robots can positively influence a human group via diverse combi- team interaction context in a LDSE mission? nations of social cues, from actively utilizing animated speech to solely using nonverbal cues without eliciting human awareness. In Since all group interactions take place in an ICE environment order to be interpreted correctly and efficiently, robot social cues with limited physical space and resources for a long duration, dif- need be contingent on specific interactions as well as congruent ferent robot roles designed for specific group contexts, e.g., coach, with other social cues being utilized. Unlike the Earth environments peer and mediator, may likely have to share a robot hardware where the most prior HRI studies were conducted, outer space envi- embodiment rather than each owning a different physical embodi- ronment imposes much more stressful challenges on human bodies ment. This constraint on robot hardware resources further poses and minds, resulting in a variety of expected physiological, psycho- additional design challenges pertaining to robot role and identity logical, cognitive and physical changes of astronauts. Investigating switching, as summarized below. how astronauts encode and decode multimodal social cues when • DQ4: Should a robot’s social identity (e.g., name, memory interacting with a robot in various physical and mental conditions and personality) remain consistent while its social role switches would help design for space robots that can adapt their social- across interaction contexts, as illustrated in Figure 1a? Should affective expression styles based on both physical environment and its social identity switch across contexts so that each robot in-the-moment states of astronauts to improve human-robot and role is uniquely associated with a distinct robot identity, as human-human communications. Thus, we summarize this design illustrated in Figure 1b? question on robot social cues as follows: • DQ5: How should a physical robot embodiment identify • DQ7: How would different gravity conditions, e.g., micro- group contexts and dynamics, and proactively switch its gravity, lunar and Martian gravity, impact astronauts’ social, social role or identity to effectively promote positive crew cognitive and affective reactions to a variety of robot social team experience? cues, e.g., gaze sharing, body motion and speech, in both CHI ’21 Workshop SpaceCHI, May 8-13, 2021, Yokohama, Japan (Online Virtual Conference) Huili Chen and Cynthia Breazeal

group and single-person HRI contexts? What social cues REFERENCES would astronauts prefer to use for human-robot communi- [1] Paul T. Bartone, Robert R. Roland, Jocelyn V. Bartone, Gerald P. Krueger, Albert A. cations in different gravity conditions? Sciarretta, and Bjorn Helge Johnsen. 2019. Human Adaptability for Deep Space Missions: An Exploratory Study. Journal of Human Performance in Extreme Living in ICE conditions for a long duration exposes astronauts Environments 15 (2019). Issue 1. https://doi.org/10.7771/2327-2937.1124 [2] Min Chen, Stefanos Nikolaidis, Harold Soh, David Hsu, and Siddhartha Srinivasa. to long-term sensory restriction. Unaffected by ICE conditions, 2018. Planning with Trust for Human-Robot Collaboration. In Proceedings of the social robots hence have great potential of delivering high-quality 2018 ACM/IEEE International Conference on Human-Robot Interaction (Chicago, consistent multi-sensory intervention to astronauts. This design IL, USA) (HRI ’18). Association for Computing Machinery, New York, NY, USA, 307–315. https://doi.org/10.1145/3171221.3171264 question is summarized as follows: [3] Houston Claure, Yifang Chen, Jignesh Modi, Malte Jung, and Stefanos Niko- laidis. 2020. Multi-Armed Bandits with Fairness Constraints for Distributing • DQ8: How could different robot social cues and behaviors Resources to Human Teammates. In Proceedings of the 2020 ACM/IEEE Inter- be designed to provide positive multi-sensory stimulation to national Conference on Human-Robot Interaction (Cambridge, United Kingdom) the crew team as well as enhance multimodal social-affective (HRI ’20). Association for Computing Machinery, New York, NY, USA, 299–308. https://doi.org/10.1145/3319502.3374806 communications among crew members, e.g., rapport, social [4] Filipa Correia, Samuel Mascarenhas, Rui Prada, Francisco S. Melo, and Ana Paiva. touch, and social reciprocity? 2018. Group-Based Emotions in Teams of Humans and Robots. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (Chicago, IL, USA) (HRI ’18). Association for Computing Machinery, New York, NY, USA, 3.3 Robot Social Adaptation Design 261–269. https://doi.org/10.1145/3171221.3171252 [5] David DeSteno, Cynthia Breazeal, Robert H. Frank, David Pizarro, Jolie Human adaptability for deep space environment is crucial for mis- Baumann, Leah Dickens, and Jin Joo Lee. 2012. Detecting the Trust- sion success. In addition to traditional coping and resource strate- worthiness of Novel Partners in Economic Exchange. Psychological Sci- ence 23, 12 (2012), 1549–1556. https://doi.org/10.1177/0956797612448793 gies for astronauts’ adaptation [1], a space robot’s social adaptability arXiv:https://doi.org/10.1177/0956797612448793 PMID: 23129062. to astronauts could also facilitate their adaptation to deep space [6] Daniel Druckman, Lin Adrian, Malene Flensborg Damholdt, Michael Filzmoser, with the long-term goal of maintaining their health and productiv- Sabine T Koszegi, Johanna Seibt, and Christina Vestergaard. 2020. Who is Best at Mediating a Social Conflict? Comparing Robots, Screens and Humans. Group ity. Multiple social-affective signal modalities of astronauts could Decision and Negotiation (2020). https://doi.org/10.1007/s10726-020-09716-9 be leveraged to develop a robot social adaptation system, includ- [7] Julia Fink, Séverin Lemaignan, Pierre Dillenbourg, Philippe Rétornaz, Florian Vaussard, Alain Berthoud, Francesco Mondada, Florian Wille, and Karmen ing their physiological signals (e.g., blood pressure, sleep patterns), Franinović. 2014. Which Robot Behavior Can Motivate Children to Tidy up physical conditions (e.g., malnutrition), as well as their psychologi- Their Toys? Design and Evaluation of "Ranger". In Proceedings of the 2014 cal and cognitive states (e.g., depressive mood, anxiety, loneliness), ACM/IEEE International Conference on Human-Robot Interaction (Bielefeld, Ger- many) (HRI ’14). Association for Computing Machinery, New York, NY, USA, alongside the robot’s audiovisual observation of the naturalistic 439–446. https://doi.org/10.1145/2559636.2559659 crew interactions. For example, if a robot can monitor each astro- [8] Christopher F Flynn. 2005. An operational approach to long-duration mission naut’s sleep quality, it can adapt its social role and social cues to behavioral health and performance factors. Aviation, space, and environmental medicine 76, 6 Suppl (jun 2005), B42–51. minimize the negative effect of astronauts’ sleep deprivation on [9] Marlena R. Fraune, Selma Šabanović, and Takayuki Kanda. 2019. Human Group team decision making and other cognitive processes. The access to Presence, Group Characteristics, and Group Norms Affect Human-Robot In- teraction in Naturalistic Settings. Frontiers in Robotics and AI 6 (jun 2019). a more diverse set of astronauts’ social-affective signal modalities https://doi.org/10.3389/frobt.2019.00048 would enable a robot’s more strategic and timely adaptation. How- [10] A. Freedy, E. DeVisser, G. Weltman, and N. Coeyman. 2007. Measurement of trust ever, a robot’s overaggressive data-driven adaptation may increase in human-robot collaboration. In 2007 International Symposium on Collaborative Technologies and Systems. 106–114. https://doi.org/10.1109/CTS.2007.4621745 the risk of exacerbating astronauts’ perceived lack of privacy in [11] Laura Galarza and Albert W. Holland. 1999. Critical Astronaut Proficiencies an ICE environment and weakening their interpersonal trust in Required for Long-Duration Space Flight, In SAE Technical Paper. https://doi. the robot and the team, potentially resulting in lower overall crew org/10.4271/1999-01-2096 [12] Qing Gao, Jinguo Liu, Zhaojie Ju, Yangmin Li, Tian Zhang, and Lu Zhang. 2017. team dynamics and productivity. Investigating the optimal robot Static Hand Gesture Recognition with Parallel CNNs for Space Human-Robot adaptation in LDSE missions requires an astronaut-centered design Interaction. In Intelligent Robotics and Applications, YongAn Huang, Hao Wu, Honghai Liu, and Zhouping Yin (Eds.). Springer International Publishing, Cham, approach. Therefore, we propose two astronaut-centered design 462–473. questions as follows: [13] Peter Hancock, Deborah Billings, Kristin Schaefer, Jessie Chen, Ewart de Visser, and Raja Parasuraman. 2011. A Meta-Analysis of Factors Affecting Trust in • DQ9: What social-affective signal modalities of astronauts Human-Robot Interaction. Human factors 53 (10 2011), 517–27. https://doi.org/ could a robot have access to for its long-term social adapta- 10.1177/0018720811417254 [14] Guy Hoffman, Oren Zuckerman, Gilad Hirschberger, Michal Luria, andTal tion? Shani Sherman. 2015. Design and Evaluation of a Peripheral Robotic Con- • DQ10: How to design a robot’s social adaptation system that versation Companion. In Proceedings of the Tenth Annual ACM/IEEE Interna- can maintain and even foster crew members’ perceived pri- tional Conference on Human-Robot Interaction (Portland, Oregon, USA) (HRI ’15). Association for Computing Machinery, New York, NY, USA, 3–10. https: vacy and interpersonal trust in the robot and other members //doi.org/10.1145/2696454.2696495 in LDSE missions? [15] Terry Huntsberger and Adrian Stoica. 2010. Envisioning cognitive robots for future space exploration. In Multisensor, Multisource Information Fusion: Architec- tures, Algorithms, and Applications 2010, Jerome J. Braun (Ed.), Vol. 7710. Interna- 4 CONCLUSION tional Society for Optics and Photonics, SPIE. https://doi.org/10.1117/12.853284 [16] W. Ju and L. Leifer. 2008. The Design of Implicit Interactions: Making Interactive This paper introduces novel opportunities for social human-robot Systems Less Obnoxious. Design Issues 24 (2008), 72–84. interactions in deep space exploration. We believe that exploring [17] Malte F. Jung, Nikolas Martelaro, and Pamela J. Hinds. 2015. Using Robots to Moderate Team Conflict: The Case of Repairing Violations. In Proceedings of the the design questions listed in the paper would help shed light on Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction how social robotics could be potentially used to promote interper- (Portland, Oregon, USA) (HRI ’15). Association for Computing Machinery, New sonal communications and facilitate group interactions among crew York, NY, USA, 229–236. https://doi.org/10.1145/2696454.2696460 members in long-duration space exploration missions. Toward Designing Social Human-Robot Interactions for Deep Space Exploration CHI ’21 Workshop SpaceCHI, May 8-13, 2021, Yokohama, Japan (Online Virtual Conference)

[18] James Kennedy, Paul Baxter, and Tony Belpaeme. 2015. The Robot Who Tried Too [39] Arielle AJ Scoglio, Erin D Reilly, Jay A Gorman, and Charles E Drebing. 2019. Use Hard: Social Behaviour of a Robot Tutor Can Negatively Affect Child Learning. of Social Robots in Mental Health and Well-Being Research: Systematic Review. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human- J Med Internet Res 21, 7 (24 Jul 2019), e13322. https://doi.org/10.2196/13322 Robot Interaction (Portland, Oregon, USA) (HRI ’15). Association for Computing [40] Sarah Sebo, Ling Liang Dong, Nicholas Chang, Michal Lewkowicz, Michael Machinery, New York, NY, USA, 67–74. https://doi.org/10.1145/2696454.2696457 Schutzman, and Brian Scassellati. 2020. The Influence of Robot Verbal Support on [19] H. Kidokoro, T. Kanda, D. Bršcic, and M. Shiomi. 2013. Will I bother here? - Human Team Members: Encouraging Outgroup Contributions and Suppressing A robot anticipating its influence on pedestrian walking comfort. In 2013 8th Ingroup Supportive Behavior. Frontiers in Psychology 11 (2020), 3584. https: ACM/IEEE International Conference on Human-Robot Interaction (HRI). 259–266. //doi.org/10.3389/fpsyg.2020.590181 https://doi.org/10.1109/HRI.2013.6483597 [41] Sarah Sebo, Brett Stoll, Brian Scassellati, and Malte F Jung. 2020. Robots in [20] S. Langton and V. Bruce. 2000. You must see the point: automatic processing Groups and Teams: A Literature Review. Proc. ACM Hum.-Comput (2020), 37. of cues to the direction of social attention. Journal of experimental psychology. https://doi.org/10.1145/3415247 Human perception and performance 26 2 (2000), 747–57. [42] Sarah Strohkorb Sebo, Ling Liang Dong, Nicholas Chang, and Brian Scassellati. [21] Stephen R. H. Langton. 2000. The Mutual Influence of Gaze and Head Orientation 2020. Strategies for the inclusion of human members within human-robot teams. in the Analysis of Social Attention Direction. The Quarterly Journal of Experimen- In ACM/IEEE International Conference on Human-Robot Interaction. IEEE Com- tal Psychology Section A 53, 3 (2000), 825–845. https://doi.org/10.1080/713755908 puter Society, New York, NY, USA, 309–317. https://doi.org/10.1145/3319502. arXiv:https://doi.org/10.1080/713755908 PMID: 10994231. 3374808 [22] Min Kyung Lee, J. Forlizzi, S. Kiesler, Paul E. Rybski, John Antanitis, and Sarun [43] Solace Shen, Petr Slovak, and Malte F. Jung. 2018. "stop. i See a Conflict Happen- Savetsila. 2012. Personalization in HRI: A longitudinal field experiment. 2012 ing.": A Robot Mediator for Young Children’s Interpersonal Conflict Resolution. In 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (2012), ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer 319–326. Society, 69–77. https://doi.org/10.1145/3171221.3171248 [23] I. Leite, A. Pereira, Samuel Mascarenhas, C. Martinho, R. Prada, and Ana Paiva. [44] M. Shiomi, T. Kanda, H. Ishiguro, and N. Hagita. 2010. A larger audience, please! — 2013. The influence of empathy in human-robot relations. Int. J. Hum. Comput. Encouraging people to listen to a guide robot. In 2010 5th ACM/IEEE International Stud. 71 (2013), 250–260. Conference on Human-Robot Interaction (HRI). 31–38. https://doi.org/10.1109/ [24] Jinguo Liu, Qing Gao, Zhiwei Liu, and Yangmin Li. 2016. Attitude control for HRI.2010.5453270 astronaut assisted robot in the space station. International Journal of Control, [45] E. Short and M. J. Mataric. 2017. Robot moderation of a collaborative game: Automation and Systems 14, 4 (2016), 1082–1095. https://doi.org/10.1007/s12555- Towards socially assistive robotics in group interactions. In 2017 26th IEEE Inter- 014-0568-4 national Symposium on Robot and Human Interactive Communication (RO-MAN). [25] P. Liu, D. F. Glas, T. Kanda, H. Ishiguro, and N. Hagita. 2013. It’s not polite to point 385–390. Generating socially-appropriate deictic behaviors towards people. In 2013 8th [46] Elaine Schaertl Short, Katherine Sittig-Boyd, and M. Mataric. 2016. Modeling ACM/IEEE International Conference on Human-Robot Interaction (HRI). 267–274. Moderation for Multi-Party Socially Assistive Robotics. In RO-MAN 2016. https://doi.org/10.1109/HRI.2013.6483598 [47] Gabriel Skantze. 2017. Predicting and Regulating Participation Equality in Human- [26] K. S. Lohan, K. Rohlfing, J. Saunders, C. Nehaniv, and B. Wrede. 2012. Contingency Robot Conversations: Effects of Age and Gender. In Proceedings of the 2017 scaffolds language learning. In 2012 IEEE International Conference on Development ACM/IEEE International Conference on Human-Robot Interaction (Vienna, Austria) and Learning and Epigenetic Robotics (ICDL). 1–6. https://doi.org/10.1109/DevLrn. (HRI ’17). Association for Computing Machinery, New York, NY, USA, 196–204. 2012.6400848 https://doi.org/10.1145/2909824.3020210 [27] Yoichi Matsuyama, Iwao Akiba, Shinya Fujie, and Tetsunori Kobayashi. 2015. [48] S. Strohkorb, E. Fukuto, N. Warren, C. Taylor, B. Berry, and B. Scassellati. 2016. Four-participant group conversation: A facilitation robot controlling engagement Improving human-human collaboration between children with a social robot. In density as the fourth participant. Computer Speech and Language 33, 1 (sep 2015), 2016 25th IEEE International Symposium on Robot and Human Interactive Commu- 1–24. https://doi.org/10.1016/j.csl.2014.12.001 nication (RO-MAN). 551–556. [28] C. Mavrogiannis, A. M. Hutchinson, J. Macdonald, P. Alves-Oliveira, and R. A. [49] Carole Tafforin and Francisco Giner Abati. 2017. Cultural ethology asanew Knepper. 2019. Effects of Distinct Robot Navigation Strategies on Human Behav- approach of interplanetary crew’s behavior. Acta Astronautica 139 (2017), 102–110. ior in a Crowded Environment. In 2019 14th ACM/IEEE International Conference https://doi.org/10.1016/j.actaastro.2017.06.017 on Human-Robot Interaction (HRI). 421–430. https://doi.org/10.1109/HRI.2019. [50] H. Tennent, S. Shen, and M. Jung. 2019. Micbot: A Peripheral Robotic Object to 8673115 Shape Conversational Dynamics and Team Performance. In 2019 14th ACM/IEEE [29] Roger C. Mayer, James H. Davis, and F. David Schoorman. 1995. An Integrative International Conference on Human-Robot Interaction (HRI). 133–142. Model of Organizational Trust. The Academy of Management Review 20, 3 (1995), [51] Margaret L. Traeger, Sarah Strohkorb Sebo, Malte Jung, Brian Scassellati, and 709–734. http://www.jstor.org/stable/258792 Nicholas A. Christakis. 2020. Vulnerable robots positively shape human con- [30] Daniel J. McAllister. 1995. Affect- and Cognition-Based Trust as Foundations versational dynamics in a human-robot team. Proceedings of the National Acad- for Interpersonal Cooperation in Organizations. The Academy of Management emy of Sciences of the United States of America 117, 12 (mar 2020), 6370–6375. Journal 38, 1 (1995), 24–59. http://www.jstor.org/stable/256727 https://doi.org/10.1073/pnas.1910402117 [31] T. I. Murphy. 2018. Hello, i am cimon! http://www.airbus.com/newsroom/press- [52] Vaibhav V. Unhelkar, Shen Li, and Julie A. Shah. 2020. Decision-Making for releases/en/2018/02/hello--i-am-cimon-.html Bidirectional Communication in Sequential Human-Robot Collaborative Tasks. [32] Bilge Mutlu, Toshiyuki Shiwa, Takayuki Kanda, Hiroshi Ishiguro, and Nori- In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot In- hiro Hagita. 2009. Footing in Human-Robot Conversations: How Robots Might teraction (Cambridge, United Kingdom) (HRI ’20). Association for Computing Ma- Shape Participant Roles Using Gaze Cues. In Proceedings of the 4th ACM/IEEE chinery, New York, NY, USA, 329–341. https://doi.org/10.1145/3319502.3374779 International Conference on Human Robot Interaction (La Jolla, California, USA) [53] D. Utami and T. Bickmore. 2019. Collaborative User Responses in Multiparty (HRI ’09). Association for Computing Machinery, New York, NY, USA, 61–68. Interaction with a Couples Counselor Robot. In 2019 14th ACM/IEEE International https://doi.org/10.1145/1514095.1514109 Conference on Human-Robot Interaction (HRI). 294–303. [33] NASA. [n.d.]. NASA’s Journey to Mars. https://www.nasa.gov/content/nasas- [54] M. Vázquez, E. J. Carter, B. McDorman, J. Forlizzi, A. Steinfeld, and S. E. Hud- journey-to-mars son. 2017. Towards Robot Autonomy in Group Conversations: Understanding [34] NASA. 2020. Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric the Effects of Body Orientation and Gaze. In 2017 12th ACM/IEEE International Disorders. https://humanresearchroadmap.nasa.gov/Risks/risk.aspx?i=99 Conference on Human-Robot Interaction (HRI. 42–52. [35] L. Palinkas and D. Browner. 1995. Effects of Prolongea Isolation in Extreme [55] Elmira Yadollahi, Wafa Johal, Ana Paiva, and Pierre Dillenbourg. 2018. When Environments on Stress, Coping, and Depression1. Journal of Applied Social Deictic Gestures in a Robot Can Harm Child-Robot Collaboration. In Proceedings Psychology 25 (1995), 557–576. of the 17th ACM Conference on Interaction Design and Children (Trondheim, [36] Douglas Raybeck. 1991. Proxemics and Privacy: Managing the Problems of Life Norway) (IDC ’18). Association for Computing Machinery, New York, NY, USA, in Confined Environments. In From Antarctica to Outer Space, Albert A. Harrison, 195–206. https://doi.org/10.1145/3202185.3202743 Yvonne A. Clearwater, and Christopher P. McKay (Eds.). Springer New York, New [56] Mateusz Żarkowski. 2019. Multi-party Turn-Taking in Repeated Human–Robot York, NY, 317–330. Interactions: An Interdisciplinary Evaluation. International Journal of Social [37] Paul Robinette, Ayanna M. Howard, and Alan R. Wagner. 2017. Effect of Ro- Robotics 11, 5 (dec 2019), 693–707. https://doi.org/10.1007/s12369-019-00603-1 bot Performance on Human-Robot Trust in Time-Critical Situations. IEEE Transactions on Human-Machine Systems 47, 4 (Aug. 2017), 425–436. https: //doi.org/10.1109/THMS.2017.2648849 [38] Alessandra Maria Sabelli and Takayuki Kanda. 2016. Robovie as a Mascot: A Qual- itative Study for Long-Term Presence of Robots in a Shopping Mall. International Journal of Social Robotics 8, 2 (2016), 211–221. https://doi.org/10.1007/s12369- 015-0332-9