Robot Appearance Research Articles

“You Scare Me”: The Effects of Humanoid Robot Appearance, Emotion, and Interaction Skills on Uncanny Valley Phenomenon

This study investigates the effects of humanoid robot appearance, emotional expression, and interaction skills on the uncanny valley phenomenon among university students using the social humanoid robot (SHR) Ameca. Two fundamental studies were conducted within a university setting: Study 1 assessed student expectations of SHRs in a hallway environment, emphasizing the need for robots to integrate seamlessly and engage effectively in social interactions; Study 2 compared the humanlikeness of three humanoid robots, ROMAN, ROBIN, and EMAH (employing the EMAH robotic system implemented on Ameca). The initial findings from corridor interactions highlighted a diverse range of human responses, from engagement and curiosity to indifference and unease. Additionally, the online survey revealed significant insights into expected non-verbal communication skills, continuous learning, and comfort levels during hallway conversations with robots. Notably, certain humanoid robots evoked stronger emotional reactions, hinting at varying degrees of humanlikeness and the influence of interaction quality. The EMAH system was frequently ranked as most humanlike before the study, while post-study perceptions indicated a shift, with EMAH and ROMAN showing significant changes in perceived humanlikeness, suggesting a re-evaluation by participants influenced by their interactive experiences. This research advances our understanding of the uncanny valley phenomenon and the role of humanoid design in enhancing human–robot interaction, marking the first direct comparison between the most advanced, humanlike research robots.

Breaking into the black box of customer perception towards robot service: Empirical evidence from service sector

The advent of artificial intelligence and machine learning has enabled robots to serve in consumer market for a better customer experience. Nevertheless, acceptance of robotic technology among consumers is still lacking. Therefore, this study has developed an integrated model with robot appearance, expectation confirmation model, diffusion of innovation and theory of planned behavior and empirically investigates customer intention to use service robot. The research model is empirically tested with 349 responses retrieved from customers visiting retail stores. Statistical results have revealed that customer innovativeness, compatibility, behavioral control, expectation confirmation, service robot appearance and subjective norms explained R2 80.1 % variance in customer attitude to use service robot. Practically, this research has suggested that policy makers should pay attention in innovativeness, compatibility, perceived behavioral control, expectation confirmation, robot appearance and subjective norms to boost robot service acceptance among customers. This study is original as it develops an integrated model with the combination robot appearance, theory of planned behavior, expectation confirmation and diffusion of innovation theory. In addition to that customer self-identity is conceptualized as moderating factor and hence distinguishing current research with past studies.

Humans Vs. Service Robots as Social Actors in Persuasion Settings

Our study departs from existing research, which primarily focuses on the benefits of automated social presence in customer service. Instead, we investigate the potential downsides of a service robot’s social presence in marketing persuasion, particularly its influence on consumers’ use of persuasion knowledge. Across five experiments, we aim to: (1) identify factors affecting the social presence of a salesclerk as a persuasion agent (type of service provider, persuasive intent, and robot appearance); and (2) reveal that anthropomorphized service robots in persuasion contexts lead to a decrease in perceived salesclerk sincerity (i.e., social presence effect), ultimately impacting consumer attitudes and behaviors. Additionally, we explore the mechanism behind the social presence effect by examining the moderating role of consumers’ dispositional persuasion knowledge. By applying the persuasion knowledge model to robot-mediated service encounters, this research offers valuable insights into the potential drawbacks of using anthropomorphic robots for marketing persuasion in service relationships.

Enhancing emotional expression in cat-like robots: strategies for utilizing tail movements with human-like gazes.

In recent years, there has been a significant growth in research on emotion expression in the field of human-robot interaction. In the process of human-robot interaction, the effect of the robot's emotional expression determines the user's experience and acceptance. Gaze is widely accepted as an important media to express emotions in human-human interaction. But it has been found that users have difficulty in effectively recognizing emotions such as happiness and anger expressed by animaloid robots that use eye contact individually. In addition, in real interaction, effective nonverbal expression includes not only eye contact but also physical expression. However, current animaloid social robots consider human-like eyes as the main emotion expression pathway, which results in a dysfunctional robot appearance and behavioral approach, affecting the quality of emotional expression. Based on retaining the effectiveness of eyes for emotional communication, we added a mechanical tail as a physical expression to enhance the robot's emotional expression in concert with the eyes. The results show that the collaboration between the mechanical tail and the bionic eye enhances emotional expression in all four emotions. Further more, we found that the mechanical tail can enhance the expression of specific emotions with different parameters. The above study is conducive to enhancing the robot's emotional expression ability in human-robot interaction and improving the user's interaction experience.

Tourists prefer competent appearance robot over warm one: The effect of busyness perception

This article indicates that perceived busyness affects tourists' appearance preferences for service robots in tourist scenarios. Results from three studies reveal that tourists who feel busy will prefer competent-appearance to warm-appearance service robots. This relationship is serial mediated by efficiency motivation and tourists’ functional value focus, and it is moderated by time orientation. Specifically, we find that the effect occurs only among tourists with high present-orientation and low future-orientation but not among tourists with high future-orientation and low present-orientation. Our study examines tourists' preferences for the appearance of service robots from an individual perspective, providing recommendations for the hotel and tourism industry when considering the implementation of service robots.

Exploring the Developmental Aspects of the Uncanny Valley Effect on Children’s Preferences for Robot Appearance

As robotic technology advances, robots are increasingly being designed and utilized for applications involving children across various fields. Since the acceptance of robots is profoundly affected by their appearance, understanding children’s preferences for the looks of robots becomes imperative. The uncanny valley effect (UVE) posits that the perceived likeability of robots increases as their appearance becomes more humanlike but then sharply drops when they approach near-perfect human similarity before rising once an extremely realistic likeness is achieved. Due to inconsistent results in the literature regarding when humans develop a sense of uncanniness toward humanlike robots, the present study aims to examine the emergence of the UVE in children. 67 1st-graders (aged six to seven years) and 95 4th-graders (aged nine to ten years) evaluated 12 robot faces on the scales of likeability, disgust, humanness, and intention to play with the robots (i.e., acceptance). The results demonstrated that the UVE was not observed in 1st-graders or 4th-grade boys. Nevertheless, a UVE-like pattern emerged among 4th-grade girls, particularly in their ratings of likeability and acceptance as a function of robots’ degree of humanness. A positive correlation between likeability and acceptance was consistently found across all age and gender groups. Additionally, negative correlations were found between likeability and disgust, as well as disgust and acceptance, specifically in the fourth graders but not in the first graders. These results suggest that the UVE may not be fully developed in 10-year-old children, with girls potentially exhibiting earlier development than boys. We conclude that age and gender differences should be considered when evaluating children’s preferences for robot appearance and their willingness to interact with robots.

A Survey on Dialogue Management in Human-robot Interaction

As social robots see increasing deployment within the general public, improving the interaction with those robots is essential. Spoken language offers an intuitive interface for the human–robot interaction (HRI), with dialogue management (DM) being a key component in those interactive systems. Yet, to overcome current challenges and manage smooth, informative, and engaging interaction, a more structural approach to combining HRI and DM is needed. In this systematic review, we analyze the current use of DM in HRI and focus on the type of dialogue manager used, its capabilities, evaluation methods, and the challenges specific to DM in HRI. We identify the challenges and current scientific frontier related to the DM approach, interaction domain, robot appearance, physical situatedness, and multimodality.

Minimal Social Cues, Body Proportion, Head Shape, and Participant’s Gender on the Trustworthiness of Social Robots

Exploring and validating factors that may influence the trustworthiness of social robots is of great significance to improving the effect of human-robot interaction. The purpose of this study was to explore the impact of several design factors on people’s perceptions of the trustworthiness of social robots. The research variables were social cues (ie, watching-eyes configuration, control configuration, and neutral configuration), head shape (ie, round head and rectangular head), body proportion (ie, low body proportion and high body proportion), and participant’s gender (ie, male and female). Twelve static synthetic social robots were created and presented to the participants as digital pictures. A total of 175 participants took part in the experiment through the online survey via the convenience sampling method. The generated results were as follows: (1) The robots with round heads appear to be more trustworthy than those with rectangular heads. (2) Robots with high body proportion are considered to be more trustworthy than robots with low body proportion. (3) Minimal social cues and body proportion of robots also have a significant interaction effect on improving the trustworthiness of robots. In the watching-eyes configuration, high body proportion is considered more trustworthy than low body proportion. On one hand, the results of this study can provide a good reference for the appearance form of social robots in human-robot interaction to serve human beings, and on the other hand, it also lays a foundation for further exploring the influence of social cues elicited by a series of social robot appearances and social behaviors regarding the trustworthiness of social robots.

Optimizing service encounters through mascot-like robot with a politeness strategy

Mascot-like service robots embody anthropomorphic features, fostering affinity, and cultural representation. It is unknown whether they have politeness strategies that are more effective compared to humanoid robots. Drawing on politeness, uncanny valley, and mind perception theories, this study investigates the interaction effect of service robot appearance types (humanoid and mascot-like) and politeness strategies on customers’ service encounter evaluation, as well as the psychological mechanisms and boundary conditions of this effect. The findings reveal the superiority of mascot-like robots over humanoid robots in positive politeness contexts; human identity threat mediated this effect. Sense of power plays a moderating role; specifically, mascot robots with positive politeness strategies are more appealing to customers with low sense of power. This research significantly contributes to our understanding of service robot appearance and communication within the framework of mind perception and politeness theories in human–robot interaction. Moreover, it offers valuable guidance for companies enhancing consumer experiences through service robots.

Effects of robots’ appearance on guest service experiences

ABSTRACT Robots are starting to replace human employees in the accommodation industry. It remains unclear how guests perceive robots. The study aims to evaluate the effectiveness of the humanoid and non-humanoid robots and to compare the guests’ perceptions. The data was collected by web digging and analyzed using text mining and machine learning. The results show that guests experience more positive emotions in non-humanoid robotic experiences. They also stated that they found both types of robot fun and interesting. However, guests have negative perceptions about the perceived usefulness and appearance of humanoid robots. According to the findings of the machine learning analysis, the neural network and logistic regression models show the best statistical performance in both datasets compared to other machine learning models. The study contributes to the literature through an investigation of guests’ opinions regarding robot types with the use of machine learning and text mining methods.

Autoencoder-enabled eye-tracking data analytics for objective assessment of user preference in humanoid robot appearance design

Humanoid robots have been extensively utilized in service industries to provide information and product delivery through direct interactions with users. As the design of humanoid robot appearance significantly impacts human-robot interactions, it is crucial to assess user preference towards it. Traditional evaluation tools, such as surveys, field observations, and interviews, are often time-consuming and subjective. Therefore, this study aims to develop a novel eye-tracking-based assessment tool to investigate user preference towards humanoid robot appearance design. We analyze the critical factors influencing user preference from two perspectives: the attributes of robot appearance and users' selective attention distribution. Accordingly, we propose an integrated machine learning method, combining an autoencoder neural network with a support vector machine to handle the collected visual data. This method, named ASVM, extracts several novel indicators from the eye-tracking data via an unsupervised autoencoder neural network and manual entropy analysis. The proposed ASVM achieves an accuracy of 91%, outperforming other classical machine learning methods, including decision tree, naive Bayes, and support vector machine. ASVM can objectively assess user preference towards humanoid robot appearance design with high time resolution. Furthermore, it can enhance humanoid robot design by revealing the visual attention distribution in assessing robot appearance.

ROS OS Based Environment Mapping of Cyber Physical System Lab by Depth Sensor

The 21st century is a century of Robotics and thus the appearance of robots in the industries made the “Industrial Revolution 4.0” in which we can control and analyse the system using HMI’s or wirelessly over network and it’s a great example of industry 4.0 component. Nowadays robots are very important part of industry’s processing unit as they have the tendency to work 24*7 thus increases the efficiency of processing and production unit.
 In our project a depth sensor (Microsoft’s Xbox Kinect) is mounted on a mobile robot whose main task is to map our Cyber Physical System Lab in 3-Dimensional which uses a ROS OS software installed on linux machine.
 The robot will use a Simultaneous localization and mapping (SLAM) process to map an environment while currently generating an estimate for the location of the Robot.

Sequential model based on human cognitive processing to robot acceptance.

Robots have tremendous potential, and have recently been introduced not only for simple operations in factories, but also in workplaces where customer service communication is required. However, communication robots have not always been accepted. This study proposes a three-stage (first contact, interaction, and decision) model for robot acceptance based on the human cognitive process flow to design preferred robots and clarifies the elements of the robot and the processes that affect robot acceptance decision-making. Unlike previous robot acceptance models, the current model focuses on a sequential account of how people decide to accept, considering the interaction (or carry-over) effect between impressions established at each stage. According to the model, this study conducted a scenario-based experiment focusing on the impression of the first contact (a robot's appearance) and that formed during the interaction with robot (politeness of its conversation and behavior) on robot acceptance in both successful and slightly failed situations. The better the appearance of the robot and the more polite its behavior, the greater the acceptance rate. Importantly, there was no interaction between these two factors. The results indicating that the impressions of the first contact and interaction are additively processed suggest that we should accumulate findings that improving the appearance of the robot and making its communication behavior more human-like in politeness will lead to a more acceptable robot design.

로봇 셰프 의인화와 심리적 파워가 소비자의 맛에 대한 판단에 미치는 영향

The goal of the study is to examine the impact of the anthropomorphism of a robot chef and consumers' psychological power levels on consumers’ taste expectations in a restaurant setting. As robot chefs becomes popular in the dining industry, consumers may rely on the robot's appearance as an extrinsic cue to judge food quality. Anthropomorphism tends to be higher among consumers with low psychological power levels, driven by a desire to compensate for power deficiency through non-human entities. Conversely, high-power consumers exhibit lower intention to rely on anthropomorphism. Two lab experiments are conducted to test the hypotheses. The results reveal that psychological power moderates the influence of anthropomorphism on taste expectations. Low-power consumers expect more flexible and tastier food from an anthropomorphized robot chef. However, this effect is diminished for high-power consumers. These findings provide practical insights into the interplay between psychological power, anthropomorphism, and taste expectations in the context of robot chefs in the dining industry.

How service robots’ human-like appearance impacts consumer trust: a study across diverse cultures and service settings

PurposeThis study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.Design/methodology/approachThe research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).FindingsStudy 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.Practical implicationsThe findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.Originality/valueThe authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.

Pengaruh Penampilan Dan Fitur Robot Quality Check Apilastik Terhadap Tingkat Kepuasan Pengguna

Rapid advances in technology, particularly in the Internet of Things (IoT), are enabling the development of devices and robots that can be operated remotely. This research explores the effects of APILASTIK Quality Check Robot Appearance and Features on User Satisfaction Level. This tool, developed by Computer Engineering Technology students at IPB University's Vocational School, aims to detect defects in production products. The robot attracted great attention when it was presented at IT FEST 2023, showing the potential for wide use. Evaluations of the robot's appearance and features showed a positive and significant influence on the level of user satisfaction, with each variable contributing 66.4% and 25.4%, respectively. Hypothesis testing confirmed the overall positive and significant impact, with the coefficient of determination (R2) reaching 82.7%. The results of multiple linear regression analysis and t-test show that the robot's appearance and features individually contribute significantly to user satisfaction. With these findings, we can understand the factors that influence user satisfaction with damage-scanning robots. The recommendation is to focus on feature development or appearance enhancement to improve overall user satisfaction.

Trust in service robot: the role of appearance anthropomorphism

ABSTRACT An increasing number of hotels and restaurants are using service robots as front-line employees, yet the lack of consumer trust in service robots affects the service experience. To enhance trust, companies have added anthropomorphism designs for service robots. This study investigated the effects of service robot anthropomorphism on trust and psychological mechanisms of trust in service robot. This study conducted three scenario-based experiments to explore the mechanisms of the service robot appearance anthropomorphism effect on trust. The results show that consumers are more likely to trust service robots with a higher degree of appearance anthropomorphism. The anthropomorphism appearance of service robots affects consumers’ perceived interpersonal attraction, including physical attraction, task attraction and social attraction, which in turn affects trust. In addition, consumers’ technology readiness moderates the effect of service robot anthropomorphism on interpersonal attraction. This paper develops research on consumer trust in service robots, and provides guidance for marketing practices of service robots.

Sensorial Feedback Contribution to the Sense of Embodiment in Brain–Machine Interfaces: A Systematic Review

The sense of embodiment (SoE) is an essential element of human perception that allows individuals to control and perceive the movements of their body parts. Brain–machine interface (BMI) technology can induce SoE in real time, and adding sensory feedback through various modalities has been shown to improve BMI control and elicit SoEe. In this study, we conducted a systematic review to study BMI performance in studies that integrated SoE variables and analyzed the contribution of single or multimodal sensory stimulation. Out of 493 results, only 20 studies analyzed the SoE of humans using BMIs. Analysis of these articles revealed that 40% of the studies relating BMIs with sensory stimulation and SoE primarily focused on manipulating visual stimuli, particularly in terms of coherence (i.e., synchronous vs. asynchronous stimuli) and realism (i.e., humanoid or robotic appearance). However, no study has analyzed the independent contributions of different sensory modalities to SoE and BMI performance. These results suggest that providing a detailed description of the outcomes resulting from independent and combined effects of different sensory modalities on the experience of SoE during BMI control may be relevant for the design of neurorehabilitation programs.

Remember me - user-centered implementation of working memory architectures on an industrial robot.

The present research is innovative as we followed a user-centered approach to implement and train two working memory architectures on an industrial RB-KAIROS + robot: GRU, a state-of-the-art architecture, and WorkMATe, a biologically-inspired alternative. Although user-centered approaches are essential to create a comfortable and safe HRI, they are still rare in industrial settings. Closing this research gap, we conducted two online user studies with large heterogeneous samples. The major aim of these studies was to evaluate the RB-KAIROS + robot's appearance, movements, and perceived memory functions before (User Study 1) and after the implementation and training of robot working memory (User Study 2). In User Study 1, we furthermore explored participants' ideas about robot memory and what aspects of the robot's movements participants found positive and what aspects they would change. The effects of participants' demographic background and attitudes were controlled for. In User Study 1, participants' overall evaluations of the robot were moderate. Participant age and negative attitudes toward robots led to more negative robot evaluations. According to exploratory analyses, these effects were driven by perceived low experience with robots. Participants expressed clear ideas of robot memory and precise suggestions for a safe, efficient, and comfortable robot navigation which are valuable for further research and development. In User Study 2, the implementation of WorkMATe and GRU led to more positive evaluations of perceived robot memory, but not of robot appearance and movements. Participants' robot evaluations were driven by their positive views of robots. Our results demonstrate that considering potential users' views can greatly contribute to an efficient and positively perceived robot navigation, while users' experience with robots is crucial for a positive HRI.

Moral Uncanny Valley revisited – how human expectations of robot morality based on robot appearance moderate the perceived morality of robot decisions in high conflict moral dilemmas

Moral Uncanny Valley revisited – how human expectations of robot morality based on robot appearance moderate the perceived morality of robot decisions in high conflict moral dilemmas