How People Talk with Robots: Designing Dialog to Reduce User Uncertainty

AI Magazine ◽  
2011 ◽  
Vol 32 (4) ◽  
pp. 31-38 ◽  
Author(s):  
Kerstin Fischer
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Joint Task ◽  
Linguistic Cues ◽  
User Expectations ◽  
Robot Appearance ◽  
The Impact

If human-robot interaction is mainly shaped by users’ strategies to deal with their unfamiliar artificial com¬munication partner, as it is suggested here, robot dialog design should orient at reducing users’ uncertainty about the affordances of the robot and the joint task. Two experiments are presented that investigate the impact of verbal robot utterances on users’ behavior; results show that users react sensitively to subtle linguistic cues that may guide them into appropriate understandings of the robot. Furthermore, the role of user expectations and robot appearance are discussed in the light of the model presented.

What Does A Robot Look Like?: A Multi-Site Examination of User Expectations About Robot Appearance

2017 ◽  
Vol 61 (1) ◽  
pp. 1215-1219 ◽  
Author(s):  
Elizabeth Phillips ◽  
Daniel Ullman ◽  
Maartje M. A. de Graaf ◽  
Bertram F. Malle
Keyword(s):  
A Priori ◽  
Human Robot Interaction ◽  
Exploratory Analysis ◽  
Robot Design ◽  
Application Domain ◽  
Critical Component ◽  
Robot Interaction ◽  
Common Features ◽  
User Expectations ◽  
Robot Appearance

Robot design is a critical component of human-robot interaction. A robot’s appearance shapes people’s expectations of that robot, which in turn affect human-robot interaction. This paper reports on an exploratory analysis of 155 drawings of robots that were collected across three studies. The purpose was to gain a better understanding of people’s a priori expectations about the appearance of robots across a variety of robot types (household, military, humanoid, generic, and AI). The findings suggest that people’s visualizations of robots have common features that can be grouped into five broad components. People seem to distinguish between human-like and machine-like robots, with a default visualization of robots having a human-like appearance. In addition, expectations about robot appearance may be dependent on application domain.

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

scholarly journals Survey of Emotions in Human–Robot Interactions: Perspectives from Robotic Psychology on 20 Years of Research

2021 ◽  
Author(s):  
Ruth Stock-Homburg
Keyword(s):  
Knowledge Production ◽  
Current Knowledge ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Interdisciplinary Field ◽  
Artificial Emotions ◽  
Art Research ◽  
Research Domain

AbstractKnowledge production within the interdisciplinary field of human–robot interaction (HRI) with social robots has accelerated, despite the continued fragmentation of the research domain. Together, these features make it hard to remain at the forefront of research or assess the collective evidence pertaining to specific areas, such as the role of emotions in HRI. This systematic review of state-of-the-art research into humans’ recognition and responses to artificial emotions of social robots during HRI encompasses the years 2000–2020. In accordance with a stimulus–organism–response framework, the review advances robotic psychology by revealing current knowledge about (1) the generation of artificial robotic emotions (stimulus), (2) human recognition of robotic artificial emotions (organism), and (3) human responses to robotic emotions (response), as well as (4) other contingencies that affect emotions as moderators.

scholarly journals Enactivism and Robotic Language Acquisition: A Report from the Frontier

Philosophies ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 11 ◽  
Author(s):  
Frank Förster
Keyword(s):  
Language Acquisition ◽  
Scientific Investigation ◽  
Human Robot Interaction ◽  
Sense Making ◽  
Robot Interaction ◽  
Design Decisions ◽  
Potential Value ◽  
The Social ◽  
Architecture And Design

In this article, I assess an existing language acquisition architecture, which was deployed in linguistically unconstrained human–robot interaction, together with experimental design decisions with regard to their enactivist credentials. Despite initial scepticism with respect to enactivism’s applicability to the social domain, the introduction of the notion of participatory sense-making in the more recent enactive literature extends the framework’s reach to encompass this domain. With some exceptions, both our architecture and form of experimentation appear to be largely compatible with enactivist tenets. I analyse the architecture and design decisions along the five enactivist core themes of autonomy, embodiment, emergence, sense-making, and experience, and discuss the role of affect due to its central role within our acquisition experiments. In conclusion, I join some enactivists in demanding that interaction is taken seriously as an irreducible and independent subject of scientific investigation, and go further by hypothesising its potential value to machine learning.

The role of emotional congruence in human-robot interaction

2013 ◽  
Author(s):  
Karoline Malchus ◽  
Prisca Stenneken ◽  
Petra Jaecks ◽  
Carolin Meyer ◽  
Oliver Damm ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction

scholarly journals Naturally occurring gestures in a human–robot teaching scenario

2008 ◽  
Vol 9 (3) ◽  
pp. 519-550 ◽  
Author(s):  
Nuno Otero ◽  
Chrystopher L. Nehaniv ◽  
Dag Sverre Syrdal ◽  
Kerstin Dautenhahn
Keyword(s):  
Human Robot Interaction ◽  
Robot Interaction ◽  
Experimental Conditions ◽  
Coding Scheme ◽  
Naturally Occurring ◽  
Actual Type ◽  
Human Gestures ◽  
Within Subjects ◽  
Order Of Presentation

This paper describes our general framework for the investigation of how human gestures can be used to facilitate the interaction and communication between humans and robots. Two studies were carried out to reveal which “naturally occurring” gestures can be observed in a scenario where users had to explain to a robot how to perform a home task. Both studies followed a within-subjects design: participants had to demonstrate how to lay a table to a robot using two different methods — utilizing only gestures or gestures and speech. The first study enabled the validation of the COGNIRON coding scheme for human gestures in Human–Robot Interaction (HRI). Based on the data collected in both studies, an annotated video corpus was produced and characteristics such as frequency and duration of the different gestural classes have been gathered to help capture requirements for the designers of HRI systems. The results from the first study regarding the frequencies of the gestural types suggest an interaction between the order of presentation of the two methods and the actual type of gestures produced. However, the analysis of the speech produced along with the gestures did not reveal differences due to ordering of the experimental conditions. The second study expands the issues addressed by the first study: we aimed at extending the role of the interaction partner (the robot) by introducing some positive acknowledgement of the participants’ activity. The results show no significant differences in the distribution of gestures (frequency and duration) between the two explanation methods, in contrast to the previous study. Implications for HRI are discussed focusing on issues relevant for the design of the robot’s communication skills to support the interaction loop with humans in home scenarios.

Validating extended neglect tolerance model for human robot interactions in humanoid soccer robots

Robotica ◽  
2010 ◽  
Vol 29 (3) ◽  
pp. 421-432 ◽  
Author(s):  
R. E. Mohan ◽  
W. S. Wijesoma ◽  
C. A. A. Calderon ◽  
C. J. Zhou
Keyword(s):  
False Alarm ◽  
Task Complexity ◽  
Human Robot Interaction ◽  
False Alarms ◽  
Robot Interaction ◽  
Tolerance Model ◽  
Robot Performance ◽  
Robot Tasks ◽  
The Impact ◽  
Soccer Robots

SUMMARYEstimating robot performance in human robot teams is a vital problem in human robot interaction community. In a previous work, we presented extended neglect tolerance model for estimation of robot performance, where the human operator switches control between robots sequentially based on acceptable performance levels, taking into account any false alarms in human robot interactions. Task complexity is a key parameter that directly impacts the robot performance as well as the false alarms occurrences. In this paper, we validate the extended neglect tolerance model for two robot tasks of varying complexity levels. We also present the impact of task complexity on robot performance estimations and false alarms demands. Experiments were performed with real and virtual humanoid soccer robots across tele-operated and semi-autonomous modes of autonomy. Measured false alarm demand and robot performances were largely consistent with the extended neglect tolerance model predictions for both real and virtual robot experiments. Experiments also showed that the task complexity is directly proportional to false alarm demands and inversely proportional to robot performance.

scholarly journals An Immersive Investment Game to Study Human-Robot Trust

2021 ◽  
Vol 8 ◽  
Author(s):  
Sebastian Zörner ◽  
Emy Arts ◽  
Brenda Vasiljevic ◽  
Ankit Srivastava ◽  
Florian Schmalzl ◽  
...  
Keyword(s):  
Science Fiction ◽  
Positive Impact ◽  
Space Mission ◽  
Verbal Communication ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Investment Game ◽  
Robot Perception ◽  
The Impact ◽  
Human Robot Collaboration

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.

scholarly journals Joint action with iCub: a successful adaptation of a paradigm of cognitive neuroscience in HRI

2019 ◽  
Author(s):  
Jairo Pérez-Osorio ◽  
Davide De Tommaso ◽  
Ebru Baykara ◽  
Agnieszka Wykowska
Keyword(s):  
Cognitive Psychology ◽  
Human Brain ◽  
Cognitive Neuroscience ◽  
Human Robot Interaction ◽  
Human Cognition ◽  
Social Environments ◽  
Social Signals ◽  
Robot Interaction ◽  
Robot Behavior ◽  
The Impact

Robots will soon enter social environments shared with humans. We need robots that are able to efficiently convey social signals during interactions. At the same time, we need to understand the impact of robots’ behavior on the human brain. For this purpose, human behavioral and neural responses to the robot behavior should be quantified offering feedback on how to improve and adjust robot behavior. Under this premise, our approach is to use methods of experimental psychology and cognitive neuroscience to assess the human’s reception of a robot in human-robot interaction protocols. As an example of this approach, we report an adaptation of a classical paradigm of experimental cognitive psychology to a naturalistic human- robot interaction scenario. We show the feasibility of such an approach with a validation pilot study, which demonstrated that our design yielded a similar pattern of data to what has been previously observed in experiments within the area of cognitive psychology. Our approach allows for addressing specific mechanisms of human cognition that are elicited during human-robot interaction, and thereby, in a longer-term perspective, it will allow for designing robots that are well- attuned to the workings of the human brain.

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