This study investigates the impact of active listening and mirroring behaviors on intimacy and trust in human-robot interaction. Based on the principles of effective human communication, active listening and mirroring were adapted for robotic systems to enhance relationship dynamics like intimacy, negative attitudes, and trust. The experimental setup involved a social robot to exhibit non-verbal cues that aligned with active listening and mirroring during interactions in the cooking scenario. The participants experienced two conditions: active listening and active listening with mirroring. The results indicated that the combination of active listening with mirroring significantly enhances intimacy and perceived trust compared to active listening only, while there is no significant difference in reducing negative attitudes. These findings suggest that incorporating non-verbal cues can substantially improve engagement in human-robot interactions, making robots more relatable and trustworthy companions.

This paper presents an active, model-based FTC (fault tolerant control) method for the dynamic positioning of underwater vehicles with thruster redundancy. Unlike conventional appraoches that rely heavily on state and parameter estimation, the proposed scheme directly utilizes the vehicle’s motion control error (MCE) to construct a residual for detecting thruster faults and failures during the steady state operation of the control system. One of the primary challenges in thruster fault identification is the unavailability of the actual control input under fault conditions. However, by conducting a detailed and rigorous analysis of the MCE variation trends associated with thruster faults, valuable information about this unknown control input can be extracted. This insight forms the foundation of the proposed FTC strategy. As for control reconfiguration, it’s straightforward since the thrust losses can be directly estimated through the fault identification process. Numerical studies with the real world vehicle model are carried out to validate the effectiveness of the proposed method.

As the number of docent robots in museums has increased, robot personalization services have become important. A survey-based experiment was conducted to catch the difference in perceptions of personalized service for exhibition visitors. As a result, it was found that the background knowledge of the visitors listening to the explanation had an effect on the perception of the personalized service. The finding gives us a set of design criteria for personalized museum guide robot services.

This study aims to investigate the effects of information delivery types on users' perception toward the robot. We executed two experiments to explore appropriate information delivery types in each situation. In the first study, we compared which type of information delivery is suitable to the situation that the robot conveys environment states. In the second study, we examined a proper information delivery type in the situation that the robot conveys its internal states. We conducted a 3(information delivery types: speech vs. reflexive cue vs. none) within-participants experiment (N=24) both in the first study and in the second study. The results of the study showed that participants perceived a robot with the reflexive cue as more anthropomorphic and animate than one with speech and one without response. In addition, participants evaluated the service of the robot with the reflexive cue more positively than the robot with speech and the robot without the response in the both studies.

In this article, we present two robot design types: human-like and product-like robot. A human-like robot is designed to be similar to humans in the appearance or behavior. A product-like robot is designed to maximize the functionality of a product. As well as the comparison between the human-like robot and product-like robot, cultural differences between Korea and Japan on perceived intellectual capability, robot-likeness, usefulness, overall impression and purchase intention were investigated. People evaluated the intellectual capability, usefulness and overall impression of the robots differently depending on their nationalities. The human-like robot was considered to be more robot-like than the product-like robot whereas there was no difference between the robots in both cultures on purchase intention. Implications for the robot design between Korea and Japan are discussed.

One of Autism Spectrum Disorder (ASD)' major characteristics is the lack of social communication and interaction with other people. Recently, some research studies have examined robot-based interventions for children with ASD. In line with those studies, the present paper introduces our ongoing research on robot-mediated imitation training for children with ASD. In this paper, we focus on designing human-robot interaction for autism intervention whereas previous studies largely focused on developing robots for intervention. Several human-robot interaction scenarios for robot-mediated imitation training were developed with emphasis on facilitating communication between a child and a therapist. Two main concepts (triadic interaction and reciprocal imitation training) were adopted and modified to increase the efficacy of the intervention. The developed interaction scenarios described how a robot can be integrated into the clinical sessions and the requirements for a robot. The field trials for examining the efficacy of robot-mediated imitation training will be carried out.

In the field of HRI, to take advantage of people’s innate ability of communication, researchers have thus far concentrated on facial expression in facilitating human robot communication. However, for the robot to express emotional intensity, other modalities such as gestures, movement, sound, and color are also needed. This paper suggests that the intensity of emotion can be expressed with color and blinking, which are applicable on robots via LED. Although color and emotion have certain relations, it is difficult to implement the findings of previous research in this area due to a lack of quantitative data. In this paper, we determined RGB values of color and blinking period to effectively express intensities of six basic emotions based on quantitative data. Color and blinking are implemented on an avatar and the intensities of emotions are evaluated through surveys with the avatar. It was found that color and blinking helped the avatar express emotional intensity of surprise, happiness, disgust, and anger. For fear, and sadness, the color and blinking did not play a significant role.

Recently, in the field of HRI, multimodal expression has been an issue. Synchronizing modalities and determining what modality to use are important aspect of multimodal expression. For example, when robots express emotional states, they may use only facial expressions or facial expressions with gestures, neck motions, sounds, etc. In this paper, emotional boundaries are proposed for multimodal expression in a three-dimensional affect space. The simultaneous expression of facial expression and gestures was demonstrated using proposed emotional boundaries on a simulator.