Stop! That is close enough. How body postures influence human-robot proximity

Obaid, Mohammad; Sandoval, Eduardo Benítez; Złotowski, Jakub; Moltchanova, Elena; Basedow, Christina Anne; Bartneck, Christoph

doi:10.1109/roman.2016.7745155

Cited by 37 publications

(27 citation statements)

References 29 publications

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“…Many studies investigated the effect of these factors on trust. Of these factors, individual's gender, subjective feeling toward robots [40], initial expectations of people toward automation [69], previous experience of the individuals with robots [62], culture [32] and also the human's understanding of the system [43] are some of the human-related factors that are addressed in different studies. 3.…”

Section: Factors Affecting Trustmentioning

confidence: 99%

Modeling Trust in Human-Robot Interaction: A Survey

Khavas

Ahmadzadeh

Robinette

2020

Lecture Notes in Computer Science

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As the autonomy and capabilities of robotic systems increase, they are expected to play the role of teammates rather than tools and interact with human collaborators in a more realistic manner, creating a more human-like relationship. Given the impact of trust observed in human-robot interaction (HRI), appropriate trust in robotic collaborators is one of the leading factors influencing the performance of human-robot interaction. Team performance can be diminished if people do not trust robots appropriately by disusing or misusing them based on limited experience. Therefore, trust in HRI needs to be calibrated properly, rather than maximized, to let the formation of an appropriate level of trust in human collaborators. For trust calibration in HRI, trust needs to be modeled first. There are many reviews on factors affecting trust in HRI [22], however, as there are no reviews concentrated on different trust models, in this paper, we review different techniques and methods for trust modeling in HRI. We also present a list of potential directions for further research and some challenges that need to be addressed in future work on human-robot trust modeling.

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Section: Factors Affecting Trustmentioning

confidence: 99%

Modeling Trust in Human-Robot Interaction: A Survey

Khavas

Ahmadzadeh

Robinette

2020

Lecture Notes in Computer Science

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“…Out of them, cues associated with proxemic behavior were found to significantly affect human perception of robot's social presence and emotional state of that encounter [15]. On the other hand, proxemics is one aspect in improving robot's perception on environment where the robot manipulates the interpretation of distance [16,17]. According to the studies, there are many emotional and psychophysiological aspects in proxemic behavior such as gender, social norms, and personality.…”

Section: Related Workmentioning

confidence: 99%

A probabilistic evaluation of human activity space for proactive approach behavior of a social robot

Sirithunge

Bandara

Jayasekara

et al. 2020

Paladyn, Journal of Behavioral Robotics

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Intelligent robot companions contribute significantly to improve the living standards of people in the modern society. Therefore, humanlike decision-making skills are sought after during the design of such robots. On the one hand, such features enable the robot to be easily handled by its human user. On the other hand, the robot will have the capability of dealing with humans without disturbing them by its behavior. Perception of Behavioral Ontology prior to an interaction is an important aspect in this regard. Furthermore, humans make an instant evaluation of task-related movements of others before approaching them. In this article, we present a mechanism to monitor how the activity space is utilized by a particular user on a temporal basis as an ontological assessment of the situation and then determine an appropriate approach behavior for a proactive robot to initiate an interaction with its user. This evaluation was then used to determine appropriate proxemic behavior to approach that person. The usage of activity space varies depending on the task of an individual. We used a probabilistic approach to find the areas that are the most and least likely to be occupied within the activity space of a particular individual during various tasks. As the robot approaches its subject after analyzing the spatial behavior of the subject within his/her activity space, spatial constraints occurred as a result of which robot’s movement could be demolished. Hence, a more socially acceptable spatial behavior could be observed from the robot. In other words, an etiquette based on approach behavior is derived considering the user’s activity space. Experiment results used to validate the system are presented, and critical observations during the study and implications are discussed.

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“…Research in human-robot interaction is often inspired by Hall's theory. This results in a lot research on how robots and humans approach each other and finding the right distance (e.g., [5], [6], [7], [8]), or how sociallyaware navigation can be implemented while taking proxemic conventions into account [9].…”

Section: Background and Related Work A Proxemicsmentioning

confidence: 99%

Let Me Show You Your New Home: Studying the Effect of Proxemic-awareness of Robots on Users’ First Impressions

Petrak

Weitz

Aslan

et al. 2019

2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

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First impressions play an important part in social interactions, establishing the foundation of a person's opinion about their counterparts. Since interpersonal communication is essentially multimodal, people are judged during first encounters by both their verbal utterances and nonverbal behavior, such as how they utilize eye contact, body distance, and body orientation. In this paper, we argue that robots would provide better user experiences, including being perceived as more likable if they were able to make a good first impression when introduced to a new home. Moreover, we wanted to test if robots can improve their perceived impression by behaving in a proxemic-aware manner; i.e., by following established social norms, which prescribe, for example how far people should position themselves around other objects to improve the facilitation of social interactions. In order to test this hypothesis, we conducted a user study with 16 participants in a virtual reality setting, comparing the impression of two agents being introduced to their new homes by users. We found that the proxemic-aware agent was indeed perceived as significantly better considering multiple constructs, including perceived anthropomorphism and trustworthiness.

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Stop! That is close enough. How body postures influence human-robot proximity

Cited by 37 publications

References 29 publications

Modeling Trust in Human-Robot Interaction: A Survey

Modeling Trust in Human-Robot Interaction: A Survey

A probabilistic evaluation of human activity space for proactive approach behavior of a social robot

Let Me Show You Your New Home: Studying the Effect of Proxemic-awareness of Robots on Users’ First Impressions

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