Machine-like Robot Research Articles

Robots do not judge: service robots can alleviate embarrassment in service encounters

Although robots are increasingly used in service provision, research cautions that consumers are reluctant to accept service robots. Five lab, field, and online studies reveal an important boundary condition to earlier work and demonstrate that consumers perceive robots less negatively when human social presence is the source of discomfort. We show that consumers feel less judged by a robot (vs. a human) when having to engage in an embarrassing service encounter, such as when acquiring medication to treat a sexually transmitted disease or being confronted with one’s own mistakes by a frontline employee. As a consequence, consumers prefer being served by a robot instead of a human when having to acquire an embarrassing product, and a robot helps consumers to overcome their reluctance to accept the service provider’s offering when the situation becomes embarrassing. However, robot anthropomorphism moderates the effect as consumers ascribe a higher automated social presence to a highly human-like robot (vs. machine-like robot), making consumers feel more socially judged.

British Children’s and Adults’ Perceptions of Robots

Robotics and artificial intelligence (AI) systems are quickly becoming a familiar part of different aspects of everyday life. We know very little about how children and adults perceive the abilities of different robots and whether these ascriptions are associated with a willingness to interact with a robot. In the current study, we asked British children aged 4–13 years and British adults to complete an online experiment. Participants were asked to describe what a robot looks like, give their preference for various types of robots (a social robot, a machine-like robot, and a human-like robot), and answer whether they were willing to engage in different activities with the different robots. Results showed that younger children (4 to 8 years old) are more willing to engage with robots compared to older children (9 to 13 years) and adults. Specifically, younger children were more likely to see robots as kind compared to older children and adults. Younger children were also more likely to rate the social robot as helpful compared to older children and adults. This is also the first study to examine preferences for robots engaging in religious activities, and results show that British adults prefer humans over robots to pray for them but such biases may not be generally applicable to children. These results provide new insight into how children and adults in the United Kingdom accept the presence and function of robots.

Advice from Robots: Would You Choose a Robot that Looked More or Less Human?

Humans are increasingly turning to non-human agents for advice. Therefore, it is important to investigate if human-likeness of a robot affects advice-seeking. In this experiment, participants chose robot advisors with different levels of human-likeness when completing either social or analytical tasks, and the task was either known or unknown when the robot advisor was selected. In the agent first condition, participants chose the advisor before receiving their task assignment, and in the task first condition participants received their task assignment before choosing the advisor. Results indicated that task type did not play a role in agent selection in either condition. However, in the agent first condition, more human-like robots (Nao and Kodomoroid) were selected at a higher rate than machine-like robots (Cozmo) and, in the task first condition, Nao was selected at a higher rate than Cozmo or Kodomoroid. These results should be considered when designing robots for giving advice to improve human-robot interaction.

Body Language for Personal Robot Arm Assistant

This article presents an exploratory study aimed at: (i) understanding participants’ first impression of the Cyton Gamma 1500, a small machine-like robot arm, and (ii) designing robot body language to convey certain intentions with regard to a personal assistant robotic application. The between-group study comprised of three distinct groups of participants. Each group had a different first encounter with the robot arm: the first group saw an idly sitting robot arm; the second group watched another person working with the robot; lastly, the third group worked with the robot themselves. They rated the robot arm on a bipolar adjective questionnaire after the first encounter which gives us insights into participant’s “first impression”. Then they performed a categorization task where they chose the most suitable posture for conveying specific messages. The objective here was to select postures that can easily convey the robot assistant’s intentions to users in future. The two main findings of the study are: (1) participants’ impression of the robot arm does not differ significantly across the three groups despite having different “first encounter” with the robot, and (2) certain postures are easily relatable to the message they convey (like, Robot is saying “Hi!”), while certain others are not (like, Robot has surrendered). In light of phenomenological theories of communication, it was concluded that tempered forms of anthropomorphic or zoomorphic postures are more easily identified than completely abstract postures. The findings of this study can be used to design robot-specific body language for robot arms.

Dave versus HAL 9000

Robot Behavior Cooperation between people depends on a willingness to establish common ground. Zanatto et al. asked how the basic rules of human cooperation apply when the other entity is a robot that has as much decision-making range as a human (like HAL 9000 in the film 2001: A Space Odyssey ). In a money-investment game in which cooperativity enhanced gain, just as between two humans, the human-robot pair rewarded cooperativity and punished selfishness. But the human response was tuned according to whether the game was more or less successful than expected and whether the robot was more anthropomorphic or more machinelike. In a benign setting, the machinelike robot elicited more cooperation from the human game players. In a less rewarding setting, the more anthropomorphic robot elicited more cooperation from the human. The authors speculate that in the more hostile environment, people draw more on social attributes to develop cooperation. PLOS ONE 14 , e0225028 (2019).

One robot doesn’t fit all: aligning social robot appearance and job suitability from a Middle Eastern perspective

Social robots are expected to take over a significant number of jobs in the coming decades. The present research provides the first systematic evaluation of occupation suitability of existing social robots based on user perception derived classification of them. The study was conducted in the Middle East since the views of this region are rarely considered in human–robot interaction research, although the region is poised to increasingly adopt the use of robots. Laboratory-based experimental data revealed that a robot’s appearance plays an important role in the perception of its capabilities and preference for it to perform a particular job. Participants showed a preference for machine-like robots to perform dull and dirty occupations and humanoids, but not androids, to perform jobs requiring extensive social interaction with humans. However, other aspects of appearance than morphology determine whether a robot is preferred for a job irrespective of its perceived capability to do it.

Exploring University Students’ Preferences for Educational Robot Design by Means of a User-Centered Design Approach

User-centered design approaches have become more prominent in various domains and have slowly been adopted in robotics research. Previous research on user-centered design highlights the beneficial effects of actively involving end users into the design process. Results further imply that end users have different notions about ideal robot design, placing special demands on social robots depending on the context and personal factors. In the present exploratory research, we applied a user-centered design method and investigated university students’ (N = 116) preferences regarding the design of educational robots. With regard to robot design, university students prefer a medium-sized machinelike robot with human characteristics and minimal facial features. Our results further suggest that a robot should primarily interact via speech and be able to display basic emotions, especially the positive ones. Additionally, from a university students’ perspective, an ideal educational robot should display behavior that is marked by conscientiousness, agreeableness, and openness. We discuss implications of our results for educational robot design, and highlight the gains of user involvement in design decisions for human–robot interaction research.

There's More to Humanity Than Meets the Eye: Differences in Gaze Behavior Toward Women and Gynoid Robots.

Based on evolutionary psychological theories, numerous eye-tracking studies have demonstrated how people visually perceive a potential mate in order to efficiently estimate the person’s mate value. Companies are currently working on sexualized robots that provide numerous human-like visual cues which foster the visual resemblance to humans. To gain more elaborated knowledge on how people react to sexualized robots compared with humans, the present study empirically investigated whether heterosexual males transfer deep-rooted evolutionary psychological processes of mate perception to human-like and machine-like sexualized robots. Moreover, we aimed to learn more about the processes of orienting responses toward human and non-human stimuli and about potential predictors of visual attention to robots. Therefore, we conducted an eye-tracking study in which 15 heterosexual men, 12 homosexual men, and 18 heterosexual women were confronted with stimuli showing women, human-like gynoid robots and machine-like gynoid robots. For the sample as a whole, there was no difference in the amount of time spent looking at the human and non-human breasts. However, the results for the heterosexual males supported the assumption that human breasts attract more visual attention than do the breast areas of human-like and machine-like robots. The pelvic region yielded an unexpected gaze pattern, as all participants spent more time looking at the robotic pelvic area than at the human one, with more visual attention paid to the machine-like robots than to the human-like robots. The results of the viewing times toward the head revealed that all participants had a stronger need to gain visual information about the human head in comparison to the robotic heads, underlining the importance of authenticity in terms of emotions and motivations that can only be decoded in humans. Moreover, the study showed that individuals more frequently switched their visual attention toward different body parts of the robots in comparison to the female stimuli, implying that non-human sexualized representations evoked a higher need for visual exploration.

Saving the Robot or the Human? Robots Who Feel Deserve Moral Care

Robots are becoming an integral part of society, yet our moral stance toward these non-living objects is unclear. In two experiments, we investigated whether anthropomorphic appearance and anthropomorphic attributions modulated people's utilitarian decision making about robotic agents. In Study 1, participants were presented with moral dilemmas in which the to-be-sacrificed agent was either a human, a human-like robot, or a machine-like robot. These victims were described in either neutral or anthropomorphic priming stories. Study 2 teased apart anthropomorphic attributions of agency and affect. Results indicate that although robot-like robots were sacrificed significantly more often than humans and humanlike robots, the effect of humanized priming was the same for all three agent types (Study 1), and this effect was mainly due to the attribution of affective states rather than agency (Study 2). That is, when people attribute affective states to robots, they are less likely to sacrifice them in order to save humans.

What Does A Robot Look Like?: A Multi-Site Examination of User Expectations About 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 Effects of Exposure to Different Social Robots on Attitudes toward Preferences

AbstractWe present results of a quasi-experimental study investigating how user preference might change after direct interaction with two different types of robot regarding morphology and affordances: a machine-like that interacts through touch, and a human-like that interacts verbally. The study was performed in an art exhibition setting, where visitors had the opportunity to interact with the robots voluntarily, and were asked to fill out questionnaires before and after the experience. Post interactions, visitors preferred to touch the machine-like “hard” robot despite initial stated preference for soft materials, preferred mutual contact despite initial preference of subject to initiate touch, and preferred communication with a robot that could touch rather than initial preference for a robot that could “see”. Overall, users showed a significant constant preference for the machine-like robot, reportedly feeling a stronger connection with it than with the human-like one as it met their expectations, and they found its movements more appealing. Social conditioning can render people reluctant to touch a robot with very human-like appearance, and set the expectations for interaction too high to meet. Our results, lastly, indicate that interaction with more than one type of social robot can affect the interaction experience for each of the robots.

Appearance of a Robot Affects the Impact of its Behaviour on Perceived Trustworthiness and Empathy

AbstractAn increasing number of companion robots have started reaching the public in the recent years. These robots vary in their appearance and behavior. Since these two factors can have an impact on lasting human–robot relationships, it is important to understand their effect for companion robots.We have conducted an experiment that evaluated the impact of a robot’s appearance and its behaviour in repeated interactions on its perceived empathy, trustworthiness and anxiety experienced by a human. The results indicate that a highly humanlike robot is perceived as less trustworthy and empathic than a more machinelike robot. Moreover, negative behaviour of a machinelike robot reduces its trustworthiness and perceived empathy stronger than for highly humanlike robot. In addition, we found that a robot which disapproves of what a human says can induce anxiety felt towards its communication capabilities. Our findings suggest that more machinelike robots can be more suitable as companions than highly humanlike robots. Moreover, a robot disagreeing with a human interaction partner should be able to provide feedback on its understanding of the partner’s message in order to reduce her anxiety.

If a Robot did “The Robot,” would it still be called “The Robot” or just Dancing? Perceptual and Social Factors in Human-Robot Interactions

One day in the future, robots will become a normal feature of everyday life and effective human-robotic partnerships will be important. The purpose of the present study was to identify the impact certain social design elements have on likability and fear in human-robot interactions through examination of human-like feminine, human-like masculine, human-like gender-neutral, and machine-like robots. The current study examined college students at a small private university. Analyses revealed that robot appearance did influence likability, with the human-like gender-neutral robot liked most by participants. Robot appearance also played a role in shaping evaluations of fear, with the human-like feminine robot feared more than the human-like gender-neutral and machine-like robots, but no more than the human-like masculine robot. The discussion centers on the importance of studying likability and fear in the context of HRI.

Persistence of the uncanny valley: the influence of repeated interactions and a robot's attitude on its perception.

The uncanny valley theory proposed by Mori has been heavily investigated in the recent years by researchers from various fields. However, the videos and images used in these studies did not permit any human interaction with the uncanny objects. Therefore, in the field of human-robot interaction it is still unclear what, if any, impact an uncanny-looking robot will have in the context of an interaction. In this paper we describe an exploratory empirical study using a live interaction paradigm that involved repeated interactions with robots that differed in embodiment and their attitude toward a human. We found that both investigated components of the uncanniness (likeability and eeriness) can be affected by an interaction with a robot. Likeability of a robot was mainly affected by its attitude and this effect was especially prominent for a machine-like robot. On the other hand, merely repeating interactions was sufficient to reduce eeriness irrespective of a robot's embodiment. As a result we urge other researchers to investigate Mori's theory in studies that involve actual human-robot interaction in order to fully understand the changing nature of this phenomenon.

Special Issue of IJSR on Social Robots: Form, Content, Critique

This special issue is an outcome of theCOSTStrategicWorkshop on Social Robotic and Sustainability that took place in Brussels, Belgium, on 10–13 June 2013 ( ). We would like to begin by thanking both participants and organizers of the workshop for a very rich and inspiring event. Particular thanks go to Professor Leopoldina Fortunati (Facolta di Scienze della Formazione Universita degli Studi di Udine, Udine, Italy) who encouraged us to pursue the possibility of this special issue in conversation with the Editor in chief, Shuzhi S. Ge. We have organized our issue around the three primary themes announced in the call, beginning with (1) Form/appearance (e.g., human/animal likeness in appearance; everyday media forms and robotic functions; cultural attitudes toward robot forms, etc.) In this section, we begin with Eleanor Sandry, “Reevaluating the form and communication of social robots: The benefits of collaborating with machinelike robots.” Sandry highlights a first thematic for this special issue—namely, that among the manifold disciplines required for adequate attention to social robots, media and communication studies must be included for what these fields can offer in terms of better understanding what is required for human sociability

Re-evaluating the Form and Communication of Social Robots

This paper re-evaluates what constitutes a social robot by analysing how a range of different forms of robot are interpreted as socially aware and communicative. Its argument juxtaposes a critical assessment of the development of humanlike and animal-like robotic companions with a consideration of human relations with machinelike robots in working teams. The paper employs a range of communication theories alongside ideas relating to anthropomorphism and zoomorphism in discussing human–robot interactions. Some traditions of communication theory offer perspectives that support the development of humanlike and animal-like social robots. However, these perspectives have been critiqued within communications scholarship as unethically closed to the possibilities of otherness and difference. This paper therefore reconfigures and extends the use of communication theory to explore how machinelike robots are interpreted by humans as social and communicative others. This involves an analysis of human relations with explosive ordnance disposal robots and with the robotic desk lamp, AUR. The paper positions social robotics research as important in understanding working teams containing humans and robots. In particular, this paper introduces the value of tempered anthropomorphism and zoomorphism as processes that support communication between humans and machinelike robots, while also ensuring that a sense of the otherness of the machine and respect for its non-human abilities is retained.

When humanoid robots become human-like interaction partners: Corepresentation of robotic actions.

In human-human interactions, corepresenting a partner's actions is crucial to successfully adjust and coordinate actions with others. Current research suggests that action corepresentation is restricted to interactions between human agents facilitating social interaction with conspecifics. In this study, we investigated whether action corepresentation, as measured by the social Simon effect (SSE), is present when we share a task with a real humanoid robot. Further, we tested whether the believed humanness of the robot's functional principle modulates the extent to which robotic actions are corepresented. We described the robot to participants either as functioning in a biologically inspired human-like way or in a purely deterministic machine-like manner. The SSE was present in the human-like but not in the machine-like robot condition. These findings suggest that humans corepresent the actions of nonbiological robotic agents when they start to attribute human-like cognitive processes to the robot. Our findings provide novel evidence for top-down modulation effects on action corepresentation in human-robot interaction situations.

Effects of Appearance and Functions on Likability and Perceived Occupational Suitability of Robots

This article reports three experiments that examined the association between (a) appearances and perceived capabilities of robots, (b) appearance and capabilities of robots and liking for the robots, and (c) perceived capabilities of robots and judgments concerning their suitability for different occupations. In Experiment 1, the authors found that participants perceived human- and animal-like robots to have relatively more warmth-related (e.g., emotion) capabilities than machinelike robots have. In Experiment 2, the authors found that liking for robots was not affected by their human likeness or their having warmth or competence capabilities. In Experiment 3, participants generally thought that robots should have information-processing and communication capabilities more than sensory and emotion capabilities. More interestingly, participants considered robots with different capabilities to be suitable for different occupations, preferring robots with emotion capabilities more in occupations that require frequent interactions with humans than in occupations that do not.

The carrot and the stick

This paper presents two studies that investigate how people praise and punish robots in a collaborative game scenario. In a first study, subjects played a game together with humans, computers, and anthropomorphic and zoomorphic robots. The different partners and the game itself were presented on a computer screen. Results showed that praise and punishment were used the same way for computer and human partners. Yet robots, which are essentially computers with a different embodiment, were treated differently. Very machine-like robots were treated just like the computer and the human; robots very high on anthropomorphism / zoomorphism were praised more and punished less. However, barely any of the participants believed that they actually played together with a robot. After this first study, we refined the method and also tested if the presence of a real robot, in comparison to a screen representation, would influence the measurements. The robot, in the form of an AIBO, would either be present in the room or only be represented on the participants’ computer screen (presence). Furthermore, the robot would either make 20% errors or 40% errors (error rate) in the collaborative game. We automatically measured the praising and punishing behavior of the participants towards the robot and also asked the participant to estimate their own behavior. Results show that even the presence of the robot in the room did not convince all participants that they played together with the robot. To gain full insight into this human–robot relationship it might be necessary to directly interact with the robot. The participants unconsciously praised AIBO more than the human partner, but punished it just as much. Robots that adapt to the users’ behavior should therefore pay extra attention to the users’ praises, compared to their punishments.

2P2-I02 エージェントの外見がユーザの機能推定に与える影響(ヒューマン・エージェント・インタラクション)

We conducted questionnaire investigations how liberal arts and informatics students estimated the agents' abilities on three different artificial agents that have different appearances; a PaPeRo human-like robot, an AIBO dog-like robot and a MindStorms machine-like robot. The results showed that 1) the PaPeRo robot received the better estimations from all students, 2) the AIBO and the MindStorms received the significantly better estimations from the informatics students whereas did the worse ones from the liberal arts students.