How Can I Help?

Holthaus, Patrick; Pitsch, Karola; Wachsmuth, Sven

doi:10.1007/s12369-011-0108-9

Cited by 27 publications

(17 citation statements)

References 26 publications

(26 reference statements)

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“…-Gaze behavior: although Holthaus et al [58] employed robots with occasional random gazes and slight body movements to signal availability, we chose to characterize the neutral robot with a static gaze direction throughout the interaction [49] in order to differentiate it more from the dynamic gaze of friendly interaction style; -A fixed posture with arms along to the body and with open hands slightly moving [34]. This was realized by keeping the robot in the "autonomous life" but disabling gestures in animated speech boxes; -Low tone of voice (50%) and low speed of speech (80%)…”

Section: Neutral Peppermentioning

confidence: 99%

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

Maggi

Dell’Aquila

Cucciniello

et al. 2020

Int J of Soc Robotics

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Social robots are developed to provide companionship and assistance in the daily life of the children, older, and disable people but also have great potential as educational technology by facilitating learning. In these application areas, a social robot can take the role of a coach by training and assisting individuals also in cognitive tasks. Since a robot’s interaction style affects users’ trust and acceptance, customizing its behavior to the proposed tasks could, potentially, have an impact on the users’ performance. To investigate these phenomena, we enrolled sixty volunteers and endowed a social robot with a friendly and an authoritarian interaction style. The aim was to explore whether and how the robot’s interaction style could enhance users’ cognitive performance during a psychometric evaluation. The results showed that the authoritarian interaction style seems to be more appropriate to improve the performance when the tasks require high cognitive demands. These differences in cognitive performance between the groups did not depend on users’ intrinsic characteristics, such as gender and personality traits. Nevertheless, in the authoritarian condition, participants’ cognitive performance was related to their trust and the acceptance of the technology. Finally, we found that users’ non-compliant behavior was not related to their personality traits. This finding indirectly supports the role of the robot’s interaction style in influencing the compliance behavior of the users.

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Section: Neutral Peppermentioning

confidence: 99%

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

Maggi

Dell’Aquila

Cucciniello

et al. 2020

Int J of Soc Robotics

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“…Group interaction introduces new factors that can affect and should be studied in HRI, such as characteristics of the human group (Sabanovic et al, 2006 ; Johansson and Skantze, 2015 ). Researchers have also begun to address solutions to group technical problems, such as tracking multiple people in group configurations (Holthaus et al, 2011 ; Taylor and Riek, 2016 ; Tseng et al, 2016 ) or switching attention between multiple people (Bennewitz et al, 2005 ). However, there are many open questions as to how varied group social dynamics in HRI should be addressed.…”

Section: Introductionmentioning

confidence: 99%

Human Group Presence, Group Characteristics, and Group Norms Affect Human-Robot Interaction in Naturalistic Settings

2019

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As robots become more prevalent in public spaces, such as museums, malls, and schools, they are coming into increasing contact with groups of people, rather than just individuals. Groups, compared to individuals, can differ in robot acceptance based on the mere presence of a group, group characteristics such as entitativity (i.e., cohesiveness), and group social norms; however, group dynamics are seldom studied in relation to robots in naturalistic settings. To examine how these factors affect human-robot interaction, we observed 2,714 people in a Japanese mall receiving directions from the humanoid robot Robovie. Video and survey responses evaluating the interaction indicate that groups, especially entitative groups, interacted more often, for longer, and more positively with the robot than individuals. Participants also followed the social norms of the groups they were part of; participants who would not be expected to interact with the robot based on their individual characteristics were more likely to interact with it if other members of their group did. These results illustrate the importance of taking into account the presence of a group, group characteristics, and group norms when designing robots for successful interactions in naturalistic settings.

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“…The behaviors are transformation units; they map the percept to an appropriate head gaze act. The [25,27,45]. The motor schema represents the template for physical activities and is connected to the actuators [48].…”

Section: Resulting Reference Architecturementioning

confidence: 99%

“…The strength of act r may be modified by a gain G, which may amplify or reduce the contribution of an individual behavior to the overall behavior. Examples of gains in social head gaze are covariate factors such as culture, gender, or proxemics, which are identified to have a significant influence on head gaze [25,27,49,50,68]. Table 2 illustrates a social head gaze example using behavioral robotics terminologies; the terminologies from ethology are also included for readers familiar with that field.…”

Section: Construction Of Conceptual Architecturesmentioning

confidence: 99%

A Reference Architecture for Social Head Gaze Generation in Social Robotics

Srinivasan

Murphy

Bethel

2015

Int J of Soc Robotics

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This article outlines a reference architecture for social head gaze generation in social robots. The architecture discussed here is grounded in human communication, based on behavioral robotics theory, and captures the commonalities, essence, and experience of 32 previous social robotics implementations of social head gaze. No such architecture currently exists, but such an architecture is needed to: (1) serve as a template for creating or re-engineering systems, (2) provide analyses and understanding of different systems, and (3) provide a common lexicon and taxonomy that facilitates communication across various communities. A constructed reference architecture and the Software Architecture Analysis Method (SAAM) are used to evaluate, improve, and re-engineer two existing head gaze system architectures (Human-Robot Collaboration architecture and Robot Behavior Toolkit architecture). SAAM shows that no existing architecture incorporated the summation of functionalities found in the 32 studies. SAAM suggests several architectural improvements so that the two existing architectures can better support adaptation to a new environment and extension of capability. The resulting reference architecture guides the implementation of social head gaze in a rescue robot for the purpose of victim management in urban B Vasant Srinivasan search and rescue (US&R). Using the proposed reference architecture will benefit social robotics because it will simplify the principled implementations of head gaze generation and allow for comparisons between such implementations.

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How Can I Help?

Cited by 27 publications

References 26 publications

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

“Don’t Get Distracted!”: The Role of Social Robots’ Interaction Style on Users’ Cognitive Performance, Acceptance, and Non-Compliant Behavior

Human Group Presence, Group Characteristics, and Group Norms Affect Human-Robot Interaction in Naturalistic Settings

A Reference Architecture for Social Head Gaze Generation in Social Robotics

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