Jasmin Bernotat

Shape It – The Influence of Robot Body Shape on Gender Perception in Robots

Previous research has shown that gender-related stereotypes are even applied to robots. In HRI, a robot’s appearance, for instance, visual facial gender cues such as hairstyle of a robot have successfully been used to elicit gender-stereotypical judgments about male and female prototypes, respectively. To complement the set of features to visually indicate a robot’s gender, we explored the impact of waist-to-hip ratio (WHR) and shoulder width (SW) in robot prototypes. Specifically, we investigated the effect of male vs. female appearance on perceived robot gender, the attribution of gender stereotypical traits, the robots’ suitability for stereotypical tasks, and participants’ trust toward the robots. Our results have demonstrated that the manipulation of WHR and SW correctly elicited gendered perceptions of the two prototypes. However, the perception of male robot gender did not affect the attribution of agentic traits and cognitive trust. Nevertheless, participants tended to rate the male robot as more suitable for stereotypically male tasks. In line with our predictions, participants preferred to use the female robot shape for stereotypically female tasks. They tended to attribute more communal traits and showed more affective trust toward the robot that was designed with a female torso versus a male robot torso. These results demonstrate that robot body shape activates stereotypes toward robots. These in turn, deeply impact people’s attitudes and trust toward robots which determine people’s motivation to engage in HRI.

Welcome to the Future – How Naïve Users Intuitively Address an Intelligent Robotics Apartment

The purpose of this Wizard-of-Oz study was to explore the intuitive verbal and non-verbal goal-directed behavior of naive participants in an intelligent robotics apartment. Participants had to complete seven mundane tasks, for instance, they were asked to turn on the light. Participants were explicitly instructed to consider nonstandard ways of completing the respective tasks. A multi-method approach revealed that most participants favored speech and interfaces like switches and screens to communicate with the intelligent robotics apartment. However, they required instructions to use the interfaces in order to perceive them as competent targets for human-machine interaction. Hence, first important steps were taken to investigate how to design an intelligent robotics apartment in a user-centered and user-friendly manner.

Hand in Hand with Robots: Differences Between Experienced and Naive Users in Human-Robot Handover Scenarios

Service robots are expected to closely interact with humans in the near future. Their tasks often include delivering and taking objects. Thus, handover scenarios play an important role in human-robot-interaction. A lot of work in this field of research focuses on speed, accuracy and predictability of the robot’s movement during object handover. Those robots need to closely interact with naive users and not only experts. In order to evaluate handover interaction performance between human and robot a force measurement based approach was implemented on the humanoid robot Floka. Different gestures with the second arm were added to analyze the influence on synchronization, predictability, and human acceptance. In this paper we present a study where users with different levels of experience were asked to help the robot to learn new objects. We evaluated the impact of previous knowledge with robots on handover interactions. Disparities in timing, distance, and applied force during handover could be observed. We present an automated annotation pipeline for human-robot-interaction that will be used in future studies. While the commonly used force measurement based approach proved to be a valid starting point, our results show that naive user interaction could benefit from better anticipation.

The Influence of Body Proportions on Perceived Gender of Robots in Latin America

Subtle aspects of a robot’s appearance may create biased expectations of the robot’s abilities, which may influence user acceptance. The present research investigated the perception of gender in robot design, focusing specifically on the proportion between chest, waist, and hips to indicate robot gender. We did so by conducting an online survey in Latin American context. The results highlight the importance of chest-to-hip ratio and waist-to-hip ratio in gender attribution and mind attribution to robots.

Let the User Decide! User Preferences Regarding Functions, Apps, and Interfaces of a Smart Home and a Service Robot

In an online survey, we studied user expectations and preferences for functions and apps in the context of a smart apartment. Furthermore, we explored which type of interface users would choose for an interaction with the smart apartment. Equally important, we investigated users’ acceptance of a service robot in the smart home. Results showed high levels of acceptance for both, the smart apartment and the robot, although the preferred interface for the apartment was context dependent. We discuss implications of the current survey and highlight key aspects to be taken into consideration when developing innovation technology for the home context.