A Review of Personality in Human‒Robot Interactions

Robert, Lionel; Alahmad, Rasha; Esterwood, Connor; Kim, Sangmi; You, Sangseok; Zhang, Qiaoning

doi:10.2139/ssrn.3528496

Cited by 41 publications

(37 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, to use context and the robot/agent, other potential influencing variables on strategy acceptance and user compliance like demographics, robot pre-experiences and attitudes ( Nomura et al, 2008 ), and personality traits ( Robert et al, 2020 ) will be tested exploratively.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Development and Testing of Psychological Conflict Resolution Strategies for Assertive Robots to Resolve Human–Robot Goal Conflict

Babel¹,

Kraus²,

Baumann³

2021

Front. Robot. AI

View full text Add to dashboard Cite

As service robots become increasingly autonomous and follow their own task-related goals, human-robot conflicts seem inevitable, especially in shared spaces. Goal conflicts can arise from simple trajectory planning to complex task prioritization. For successful human-robot goal-conflict resolution, humans and robots need to negotiate their goals and priorities. For this, the robot might be equipped with effective conflict resolution strategies to be assertive and effective but similarly accepted by the user. In this paper, conflict resolution strategies for service robots (public cleaning robot, home assistant robot) are developed by transferring psychological concepts (e.g., negotiation, cooperation) to HRI. Altogether, fifteen strategies were grouped by the expected affective outcome (positive, neutral, negative). In two online experiments, the acceptability of and compliance with these conflict resolution strategies were tested with humanoid and mechanic robots in two application contexts (public: n1 = 61; private: n2 = 93). To obtain a comparative value, the strategies were also applied by a human. As additional outcomes trust, fear, arousal, and valence, as well as perceived politeness of the agent were assessed. The positive/neutral strategies were found to be more acceptable and effective than negative strategies. Some negative strategies (i.e., threat, command) even led to reactance and fear. Some strategies were only positively evaluated and effective for certain agents (human or robot) or only acceptable in one of the two application contexts (i.e., approach, empathy). Influences on strategy acceptance and compliance in the public context could be found: acceptance was predicted by politeness and trust. Compliance was predicted by interpersonal power. Taken together, psychological conflict resolution strategies can be applied in HRI to enhance robot task effectiveness. If applied robot-specifically and context-sensitively they are accepted by the user. The contribution of this paper is twofold: conflict resolution strategies based on Human Factors and Social Psychology are introduced and empirically evaluated in two online studies for two application contexts. Influencing factors and requirements for the acceptance and effectiveness of robot assertiveness are discussed.

show abstract

Section: Theoretical Backgroundmentioning

confidence: 99%

Development and Testing of Psychological Conflict Resolution Strategies for Assertive Robots to Resolve Human–Robot Goal Conflict

Babel¹,

Kraus²,

Baumann³

2021

Front. Robot. AI

View full text Add to dashboard Cite

show abstract

“…As shown in Figure 2, the Double robot wore a t-shirt to personify it as a student because people are inclined to interact with the robots whose personalities conform to the robot's occupational role [64], and the LED circle light on the center of the t-shirt was turned on to make it easy for a participant to recognize when his/her voice was transmitted into robot platform. Considering that when people interact with robots, they have impressions of the robots in terms of perceived robot personality [65], we made these changes with the aim of promoting a social aspect in the setting.…”

Section: The Telepresence Robotic Platformsmentioning

confidence: 99%

The Use of UTAUT and Post Acceptance Models to Investigate the Attitude towards a Telepresence Robot in an Educational Setting

Han

Conti

2020

Robotics

View full text Add to dashboard Cite

(1) Background: in the last decade, various investigations into the field of robotics have created several opportunities for further innovation to be possible in student education. However, despite scientific evidence, there is still strong scepticism surrounding the use of robots in some social fields, such as personal care and education. (2) Methods: in this research, we present a new tool named the HANCON model, which was developed merging and extending the constructs of two solid and proven models—the Unified Theory of Acceptance and Use of Technology (UTAUT) model used to examine the factors that may influence the decision to use a telepresence robot as an instrument in educational practice, and the Post Acceptance Model used to evaluate acceptability after the actual use of a telepresence robot. The new tool is implemented and used to study the acceptance of a double telepresence robot by 112 pre-service teachers in an educational setting. (3) Results: the analysis of the experimental results predicts and demonstrate a positive attitude towards the use of telepresence robot in a school setting and confirm the applicability of the model in an educational context. (4) Conclusions: the constructs of the HANCON model could predict and explain the acceptance of social telepresence robots in social contexts.

show abstract

“…However, the authors mention that in the literature, similarity attraction has more compelling experimental support. Human–robot interaction is still in its infancy in terms of exploring these biases and relationships, so there is a lack of empirical evidence to help designers understand the perceptions of robot attributes, especially for personality [ 141 ].…”

Section: Discussionmentioning

confidence: 99%

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review

Cano

González

Gil

et al. 2021

Sensors

View full text Add to dashboard Cite

Research on affective communication for socially assistive robots has been conducted to enable physical robots to perceive, express, and respond emotionally. However, the use of affective computing in social robots has been limited, especially when social robots are designed for children, and especially those with autism spectrum disorder (ASD). Social robots are based on cognitive-affective models, which allow them to communicate with people following social behaviors and rules. However, interactions between a child and a robot may change or be different compared to those with an adult or when the child has an emotional deficit. In this study, we systematically reviewed studies related to computational models of emotions for children with ASD. We used the Scopus, WoS, Springer, and IEEE-Xplore databases to answer different research questions related to the definition, interaction, and design of computational models supported by theoretical psychology approaches from 1997 to 2021. Our review found 46 articles; not all the studies considered children or those with ASD.

show abstract

A Review of Personality in Human‒Robot Interactions

Cited by 41 publications

References 0 publications

Development and Testing of Psychological Conflict Resolution Strategies for Assertive Robots to Resolve Human–Robot Goal Conflict

Development and Testing of Psychological Conflict Resolution Strategies for Assertive Robots to Resolve Human–Robot Goal Conflict

The Use of UTAUT and Post Acceptance Models to Investigate the Attitude towards a Telepresence Robot in an Educational Setting

Affective Communication for Socially Assistive Robots (SARs) for Children with Autism Spectrum Disorder: A Systematic Review

Contact Info

Product

Resources

About