Graphical Signage Decreases Negative Attitudes towards Robots and Robot Anxiety in Human-Robot Co-working

To achieve full potential of collaborative robots, human operators need confidence in robotic co-worker technologies and their capacities. We compare the impact of dynamic signage with static signage on the human-robot collaboration task performance. The results provide evidence that dynamic signage participants had higher accuracy rates compared to static signage ones. Furthermore, dynamic signage resulted in a significant decrease of NARS scores and static signage in a decrease of RAS scores after the interaction with the robot

A Systematic Literature Review of User Experience Evaluation Scales for Human-Robot Collaboration

In the last decade, the field of Human-Robot Collaboration (HRC) has received much attention from both research institutions and industries. Robot technologies are in fact deployed in many different areas (e.g., industrial processes, people assistance) to support an effective collaboration between humans and robots. In this transdisciplinary context, User eXperience (UX) has inevitably to be considered to achieve an effective HRC, namely to allow the robots to better respond to the users’ needs and thus improve the interaction quality. The present paper reviews the evaluation scales used in HRC scenarios, focusing on the application context and evaluated aspects. In particular, a systematic review was conducted based on the following questions: (RQ1) which evaluation scales are adopted within the HRI scenario with collaborative tasks?, and (RQ2) how the UX and user satisfaction are assessed?. The records analysis highlighted that the UX aspects are not sufficiently examined in the current HRC design practice, particularly in the industrial field. This is most likely due to a lack of standardized scales. To respond to this recognized need, a set of dimensions to be considered in a new UX evaluation scale were proposed

Robotic Psychology. What Do We Know about Human-Robot Interaction and What Do We Still Need to Learn?

“Robotization”, the integration of robots in human life will change human life drastically. In many situations, such as in the service sector, robots will become an integrative part of our lives. Thus, it is vital to learn from extant research on human-robot interaction (HRI). This article introduces robotic psychology that aims to bridge the gap between humans and robots by providing insights into particularities of HRI. It presents a conceptualization of robotic psychology and provides an overview of research on service-focused human-robot interaction. Theoretical concepts, relevant to understand HRI with are reviewed. Major achievements, shortcomings, and propositions for future research will be discussed

Time-Space Relationship Analysis Model on the Bus Driving Characteristics of Different Drivers Based on the Traffic Performance Index System

With the extensive application of the concept of green traffic, the relationship between the driving characteristics of different drivers and energy consumption and traffic performance conditions, etc. is gradually becoming a research hotspot. Based on bus status data recorded by travel data recorders with a vehicle-mounted satellite positioning function and in view of external bus behaviours and driver’s performance, a bus driving characteristic model of drivers is established. A time-space analysis model of the driving characteristics of different drivers based on traffic performance index is also established through fuzzy association rules and a type-2 fuzzy set prediction algorithm. Test results show that the prediction algorithm can accurately describe the time-space relationship between the traffic congestion index and bus driving characteristic model and achieve relatively high prediction accuracy. The problem of the lagging release of traffic performance index caused by massive calculation for floating vehicle data can be effectively solved through this algorithm, which can serve as an important reference for analyzing traffic performance conditions, as well as the energy conservation and emission reduction of buses

Emotion Transfer from Frontline Social Robots to Human Customers During Service Encounters: Testing an Artificial Emotional Contagion Modell

This research examines mood transitions during human-robot interactions (HRI) compared with human-human interactions (HHI) during service encounters. Based on emotional contagion and social identity theory, we argue that emotion transmission within HRI (e.g., between a frontline service robot and a human customer) may occur through the imitation of the robot’s verbal and bodily expressions by the customer and may be stronger for negative than for positive emotions. The customer’s positive attitude and anxiety toward robots will further be examined as contingencies that strengthen or weaken the emotion transition during the HRI. We already identified the five most important emotions during service encounters (critical incident study with 131 frontline employees). The subsequent output behavior was programmed to a Nao robot and validated (ratings from 234 students). In the next step, we attempt to manipulate the emotional expressions of a frontline social robot and a customer within an experimental study

Facilitation of human empathy through self-disclosure of anthropomorphic agents

As AI technologies progress, social acceptance of AI agents including intelligent virtual agents and robots is getting to be even more important for more applications of AI in human society. One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. By empathizing, humans take positive and kind actions toward agents, and emphasizing makes it easier for humans to accept agents. In this study, we focused on self-disclosure from agents to humans in order to realize anthropomorphic agents that elicit empathy from humans. Then, we experimentally investigated the possibility that an agent's self-disclosure facilitates human empathy. We formulate hypotheses and experimentally analyze and discuss the conditions in which humans have more empathy for agents. This experiment was conducted with a three-way mixed plan, and the factors were the agents' appearance (human, robot), self-disclosure (high-relevance self-disclosure, low-relevance self-disclosure, no self-disclosure), and empathy before and after a video stimulus. An analysis of variance was performed using data from 576 participants. As a result, we found that the appearance factor did not have a main effect, and self-disclosure, which is highly relevant to the scenario used, facilitated more human empathy with statistically significant difference. We also found that no self-disclosure suppressed empathy. These results support our hypotheses.Comment: 20 pages, 8 figures, 2 tables, submitted to PLOS ONE Journa

Trusting Robocop: Gender-Based Effects on Trust of an Autonomous Robot

Little is known regarding public opinion of autonomous robots. Trust of these robots is a pertinent topic as this construct relates to one’s willingness to be vulnerable to such systems. The current research examined gender-based effects of trust in the context of an autonomous security robot. Participants (N = 200; 63% male) viewed a video depicting an autonomous guard robot interacting with humans using Amazon’s Mechanical Turk. The robot was equipped with a non-lethal device to deter non-authorized visitors and the video depicted the robot using this non-lethal device on one of the three humans in the video. However, the scenario was designed to create uncertainty regarding who was at fault – the robot or the human. Following the video, participants rated their trust in the robot, perceived trustworthiness of the robot, and their desire to utilize similar autonomous robots in several different contexts that varied from military use to commercial use to home use. The results of the study demonstrated that females reported higher trust and perceived trustworthiness of the robot relative to males. Implications for the role of individual differences in trust of robots are discussed

Can(’t) wait to have a robot at home? – Japanese and German users’ attitudes toward service robots in smart homes

Bernotat J, Eyssel FA. Can(’t) wait to have a robot at home? – Japanese and German users’ attitudes toward service robots in smart homes. In: Proceedings of the 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). 2018: 15-22