Evaluation Of Human-robot Interaction Research Articles

Factors influencing consumers' willingness to accept service robots: Based on online reviews of Chinese hotels.

The application of robots in service industry is increasing. Compared with related studies in other countries, the research on users’ acceptance of mid-range and high-range hotel service robots in China is preliminary. Based on the interaction between Chinese consumers and hotel service robots, this study explored the factors that influence consumers’ willingness to accept robots in human–robot interaction. According to the service robot integration willingness scale (performance efficacy, intrinsic motivation, anthropomorphism, social influence, facilitating conditions, and emotion), this study conducted content analysis and sentiment analysis on 4,107 online reviews from 68 mid-range and high-range hotels in Qunar. The results showed that users’ overall evaluation of robot service in mid-range and high-range hotels is positive. The most frequently mentioned dimension by users is performance efficacy, followed by intrinsic motivation, anthropomorphism, and emotion, finally, the facilitating conditions, the five dimensions have positive impact on users’ evaluation of service robots; the influence of social influence on human–robot interaction evaluation has not been found. This study supplements the research on service robot and provides a reference for hotel managers to make decisions.

A Methodology to Design and Evaluate HRI Teaming Tasks in Robotic Competitions

As social robots become more prominent in our lives, their interaction with humans takes an increasing role, and new collaborative scenarios emerge. This development brings the need to realize robust test methods enabling the design and evaluation of Human-Robot Interaction (HRI) teaming tasks to prove functionality and promote adoption. In this article, we present a general-purpose and repeatable methodology for conducting studies in collaborative HRI in the range of robotic competitions. The methodology includes a step-by-step approach to design HRI teaming tasks tailored to be enacted in a robotic competition and to evaluate the performance of social robots to execute the designed tasks, exploring the relationship between robots’ performance and user perceptions based on the feedback of the users participating to such tasks. We assess the feasibility of the methodology to design and evaluate an HRI teaming task in the context of “Smart CIties RObotics Challenges” (SciRoc) competition, which targets at investigating the impact of social of robots in smart cities.

I vs. robot: Sociodigital self-comparisons in hybrid teams from a theoretical, empirical, and practical perspective

This article in the journal Gruppe. Interaktion. Organisation. (GIO) introduces sociodigital self-comparisons (SDSC) as individual evaluations of own abilities in comparison to the knowledge and skills of a cooperating digital actor in a group. SDSC provide a complementary perspective for the acceptance and evaluation of human-robot interaction (HRI). As social robots enter the workplace, in addition to human-human comparisons, digital actors also become objects of comparisons (i.e., I vs. robot). To date, SDSC have not been systematically reflected in HRI. Therefore, we introduce SDSC from a theoretical perspective and reflect its significance in social robot applications. First, we conceptualize SDSC based on psychological theories and research on social comparison. Second, we illustrate the concept of SDSC for HRI using empirical data from 80 hybrid teams (two human actors and one autonomous agent) who worked together in an interdependent computer-simulated team task. SDSC in favor of the autonomous agent corresponded to functional (e.g., robot trust, or team efficacy) and dysfunctional (e.g., job threat) team-relevant variables, highlighting the two-sidedness of SDSC in hybrid teams. Third, we outline the (practical) potential of SDSC for social robots in the field and the lab.

Extending the Evaluation of Social Assistive Robots With Accessibility Indicators: The AUSUS Evaluation Framework

The introduction of robots in the real world requires previous evaluation of the envisaged performance. Factors like usability, user experience, social acceptance, or societal impact, among others, have been taken into account in evaluation frameworks defined during the last years. However, one of the most important factors that need to be evaluated in any kind of interaction is whether all the users are able to work with the system with the same opportunities and easiness, and none of the current human–robot interaction (HRI) evaluation frameworks include this factor yet. This article proposes an extension of a popular HRI evaluation framework, including accessibility as a new evaluation factor. The proposed approach, named AUSUS, considers Accessibility, Usability, Social acceptance, User experience, and Societal impact. This article presents a use case of the framework, which is evaluated through a socially assistive robotic platform created to perform comprehensive geriatric assessment: the CLARC system. The details of the evaluation process in a hospital and a retirement home are reported, and the main difficulties and recommendations of using AUSUS are discussed.

Perception and Evaluation in Human–Robot Interaction: The Human–Robot Interaction Evaluation Scale (HRIES)—A Multicomponent Approach of Anthropomorphism

The evaluation of how (human) individuals perceive robots is a central issue to better understand human–robot interaction (HRI). On this topic, promising proposals have emerged. However, present tools are not able to assess a sufficient part of the composite psychological dimensions involved in the evaluation of HRI. Indeed, the percentage of variance explained is often under the recommended threshold for a construct to be valid. In this article, we consolidate the lessons learned from three different studies and propose a further developed questionnaire based on a multicomponent approach of anthropomorphism by adding traits from psychosocial theory about the perception of others and the attribution and deprivation of human characteristics: the de-humanization theory. Among these characteristics, the attribution of agency is of main interest in the field of social robotics as it has been argued that robots could be considered as intentional agents. Factor analyses reveal a four sub-dimensions scale including Sociability, Agency, Animacy, and the Disturbance. We discuss the implication(s) of these dimensions on future perception of and attitudes towards robots.

Optimization of criterion for objective evaluation of HRI performance that approximates subjective evaluation: a case study in robot competition

The standard approach to evaluate the performance of human-robot interaction (HRI) is subjective evaluation, for example, using questionnaires. Because such subjective evaluation is time-consuming, an alternative evaluation method based on only objective factors (i.e. human reaction behavior) is required for autonomous learning by robots and for scoring in robot competitions, etc. To this end, we aimed to investigate the extent to which subjective evaluation results can be approximated using objective factors. We observed and stored HRI history data through a robot-competition task in which the robot was required to generate comprehensible and unambiguous natural language expressions and gestures to guide inexpert users in virtual everyday environments. In addition, to acquire subjective evaluation results, we asked third-parties to evaluate the HRI performance by reviewing the stored interaction histories. From the results of a case study of robot-competition, we demonstrate the necessity for an objective method for the evaluation of HRI performance and a determination process for an effective evaluation criterion. The results of a multiple linear regression analysis to estimate the subjective evaluation results reveal that the subjective evaluation of HRI can indeed be reasonably approximated base on objective factors.

Social Media in Human–Robot Interaction

The objective of this paper is to discuss and demonstrate in a case study the application of social media as a tool for acceptance, sociability and interaction in human–robot interaction (HRI). By adopting the concept of mediatization as discussed in media and communication studies, we aim to propose an extended usage of social media in the design of robots but also in collecting data on their acceptance and sociability. We aim to provide a starting point for ongoing studies into the extension of HRI evaluation frameworks, which provide additional ways to measure HRI based on a media and communication studies approach. Our discussion is supported by results of an HRI public engagement project, which included a social media strategy. The project was designed around a hitchhiking robot, called hitchBOT, which was dependent on the public’s engagement and support in its hitchhiking objectives. The robot’s social media strategies included accounts and profiles on Facebook, Twitter, Instagram, and a website. The aim was to use social media in order to engage not only with those people finding hitchBOT on the side of the road, but also a wider international audience. The robot’s social media accounts provided a tool to communicate hitchBOT’s origins, personality, goals, and travels. Our use of social media to communicate hitchBOT’s personality and to instill trust, interest and emotional engagement constituted a novel contribution to the design of social robots and to the scope and scale of evaluation in HRI.

Refining levels of collaboration to support the design and evaluation of human-robot interaction in the manufacturing industry

The manufacturing industry has high expectations for the benefits of collaborative robots. The term collaborative robots, however, encompasses multiple levels of collaboration ranging from coexistence to joint object manipulation. We attempt to refine the levels of collaboration between human workers and collaborative robots by reviewing literature and using case study examples. Distinguishing between the different levels is important because of the requisite safety issues and for the purpose of designing and evaluating the worker aspects of human-robot interaction, e.g., acceptance and workflow. This work facilitates finding the best ways to implement future human-robot collaboration on the factory floor.

Generation and Evaluation of Communicative Robot Gesture

How is communicative gesture behavior in robots perceived by humans? Although gesture is crucial in social interaction, this research question is still largely unexplored in the field of social robotics. Thus, the main objective of the present work is to investigate how gestural machine behaviors can be used to design more natural communication in social robots. The chosen approach is twofold. Firstly, the technical challenges encountered when implementing a speech-gesture generation model on a robotic platform are tackled. We present a framework that enables the humanoid robot to flexibly produce synthetic speech and co-verbal hand and arm gestures at run-time, while not being limited to a predefined repertoire of motor actions. Secondly, the achieved flexibility in robot gesture is exploited in controlled experiments. To gain a deeper understanding of how communicative robot gesture might impact and shape human perception and evaluation of human-robot interaction, we conducted a between-subjects experimental study using the humanoid robot in a joint task scenario. We manipulated the non-verbal behaviors of the robot in three experimental conditions, so that it would refer to objects by utilizing either (1) unimodal (i.e., speech only) utterances, (2) congruent multimodal (i.e., semantically matching speech and gesture) or (3) incongruent multimodal (i.e., semantically non-matching speech and gesture) utterances. Our findings reveal that the robot is evaluated more positively when non-verbal behaviors such as hand and arm gestures are displayed along with speech, even if they do not semantically match the spoken utterance.