Talk to Me: Verbal Communication Improves Perceptions of Friendship and Social Presence in Human-Robot Interaction

Author(s):  
Elena Corina Grigore ◽  
Andre Pereira ◽  
Ian Zhou ◽  
David Wang ◽  
Brian Scassellati
2016 ◽  
Vol 17 (3) ◽  
pp. 461-490 ◽  
Author(s):  
Maartje M. A. de Graaf ◽  
Somaya Ben Allouch ◽  
Jan A. G. M. van Dijk

Abstract This study aims to contribute to emerging human-robot interaction research by adding longitudinal findings to a limited number of long-term social robotics home studies. We placed 70 robots in users’ homes for a period of up to six months, and used questionnaires and interviews to collect data at six points during this period. Results indicate that users’ evaluations of the robot dropped initially, but later rose after the robot had been used for a longer period of time. This is congruent with the so-called mere-exposure effect, which shows an increasing positive evaluation of a novel stimulus once people become familiar with it. Before adoption, users focus on control beliefs showing that previous experiences with robots or other technologies allows to create a mental image of what having and using a robot in the home would entail. After adoption, users focus on utilitarian and hedonic attitudes showing that especially usefulness, social presence, enjoyment and attractiveness are important factors for long-term acceptance.


2021 ◽  
Vol 8 ◽  
Author(s):  
Sebastian Zörner ◽  
Emy Arts ◽  
Brenda Vasiljevic ◽  
Ankit Srivastava ◽  
Florian Schmalzl ◽  
...  

As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilize two Neuro-Inspired COmpanion (NICO) - robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of non-verbal communication. We observe a correlation of 0.43 (p=0.02) between self-assessed trust and trust measured from the game, and a positive impact of non-verbal communication on trust (p=0.0008) and robot perception for anthropomorphism (p=0.007) and animacy (p=0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human’s trust in robots.


Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6529
Author(s):  
Masaya Iwasaki ◽  
Mizuki Ikeda ◽  
Tatsuyuki Kawamura ◽  
Hideyuki Nakanishi

Robotic salespeople are often ignored by people due to their weak social presence, and thus have difficulty facilitating sales autonomously. However, for robots that are remotely controlled by humans, there is a need for experienced and trained operators. In this paper, we suggest crowdsourcing to allow general users on the internet to operate a robot remotely and facilitate customers’ purchasing activities while flexibly responding to various situations through a user interface. To implement this system, we examined how our developed remote interface can improve a robot’s social presence while being controlled by a human operator, including first-time users. Therefore, we investigated the typical flow of a customer–robot interaction that was effective for sales promotion, and modeled it as a state transition with automatic functions by accessing the robot’s sensor information. Furthermore, we created a user interface based on the model and examined whether it was effective in a real environment. Finally, we conducted experiments to examine whether the user interface could be operated by an amateur user and enhance the robot’s social presence. The results revealed that our model was able to improve the robot’s social presence and facilitate customers’ purchasing activity even when the operator was a first-time user.


2018 ◽  
Vol 161 ◽  
pp. 01001 ◽  
Author(s):  
Karsten Berns ◽  
Zuhair Zafar

Human-machine interaction is a major challenge in the development of complex humanoid robots. In addition to verbal communication the use of non-verbal cues such as hand, arm and body gestures or mimics can improve the understanding of the intention of the robot. On the other hand, by perceiving such mechanisms of a human in a typical interaction scenario the humanoid robot can adapt its interaction skills in a better way. In this work, the perception system of two social robots, ROMAN and ROBIN of the RRLAB of the TU Kaiserslautern, is presented in the range of human-robot interaction.


2019 ◽  
Author(s):  
Cecilia Roselli ◽  
Francesca Ciardo ◽  
Agnieszka Wykowska

In near future, robots will become a fundamental part of our daily life; therefore, it appears crucial to investigate how they can successfully interact with humans. Since several studies already pointed out that a robotic agent can influence human’s cognitive mechanisms such as decision-making and joint attention, we focus on Sense of Agency (SoA). To this aim, we employed the Intentional Binding (IB) task to implicitly assess SoA in human-robot interaction (HRI). Participants were asked to perform an IB task alone (Individual condition) or with the Cozmo robot (Social condition). In the Social condition, participants were free to decide whether they wanted to let Cozmo press. Results showed that participants performed the action significantly more often than Cozmo. Moreover, participants were more precise in reporting the occurrence of a self-made action when Cozmo was also in charge of performing the task. However, this improvement in evaluating self-performance corresponded to a reduction in SoA. In conclusion, the present study highlights the double effect of robots as social companions. Indeed, the social presence of the robot leads to a better evaluation of self-generated actions and, at the same time, to a reduction of SoA.


Author(s):  
Samantha F. Warta ◽  
Olivia B. Newton ◽  
Jihye Song ◽  
Andrew Best ◽  
Stephen M. Fiore

This study investigated how humans interact socially with robots. Participants engaged in a hallway navigation task with a robot. Throughout twelve trials, the display on the robot and its proxemics behavior was varied while participants were tasked with first, reacting to the robot’s actions and second, interpreting its behavior. Results indicated that proxemic behavior and robotic display characteristics influence the degree to which individuals perceive the robot as socially present, with more human-like displays and assertive robotic behaviors resulting in greater assessments of social presence. When examined in isolation, repeated interactions over time do not appear to affect the perception of a socially present robot under these particular circumstances. Results are discussed in the context of how social signals theory inform research in human-robot interaction.


2019 ◽  
Vol 47 (3) ◽  
pp. 140-148 ◽  
Author(s):  
Dagoberto Cruz-Sandoval ◽  
Jesus Favela

Background: Socially assistive robots (SARs) have the potential to assist nonpharmacological interventions based on verbal communication to support the care of persons with dementia (PwDs). However, establishing verbal communication with a PwD is challenging. Thus, several authors have proposed strategies to converse with PwDs. While these strategies have proved effective at enhancing communication between PwDs and their caregivers, they have not been used or tested in the domain of human-robot interaction. Objectives: This study aimed to assess the effectiveness of incorporating conversational strategies proposed in the literature for caregivers, during PwD-robot interactions. Methods: We conducted a total of 23 group sessions based on music and conversation therapy, where a SAR interacted with 12 PwDs (mean = 80.25 years) diagnosed with mild to moderate-stage dementia. Using a single subject research approach, we designed an AB study to assess the effectiveness of the conversational strategies in the PwD-robot interaction. Our analysis focuses on the direct communication between the PwDs and the robot, and the perceived enjoyment of PwDs. Results: The number of utterances made from a PwD to the robot increased significantly when the conversational strategies were included in the robot. In addition, PwDs engaged in more sustained conversations. Additionally, PwDs enjoyed conversing with the robot Eva, as much as listening to music. These results indicate that the use of these conversational strategies is ­effective at increasing the interaction between PwD and a SAR. Conclusions: PwDs who participated in the study engaged and enjoyed the interaction with the SAR. The results provide evidence of the importance of incorporating appropriate conversational strategies in SARs that support interventions for the care and social stimulation of PwDs.


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