Educational robots prove effective in children’s learning, but designing robots that support parent-child dialogue during home learning remains unclear. This study proposes a semi-autonomous para-operated robot that parents partially control while engaging with their child. We hypothesized that unlike autonomous robots which may reduce parental engagement [1], this approach would increase parental involvement through active operation. We conducted an experiment with parent-child pairs comparing no robot, autonomous robot, and the proposed semi-autonomous robot conditions. Results showed the proposed robot significantly increased parental utterances without increasing parental burden, demonstrating its effectiveness in facilitating parent-child home learning dialogue.

Teleoperated customer service robots have attracted attention to improve customer service efficiency. However, operators experience boredom during long-duration operation due to monotony and idle time, leading to decreased task motivation. This study proposes and evaluates a method to reduce operator boredom through dialogue with the robot to be operated. Field experiments demonstrated that operator-robot dialogue significantly reduced boredom and contributed to maintaining task engagement during long-duration operation.

Various customer service robots’ teleoperation interfaces (I/Fs) have been developed for human-robot collaboration. However, a previous study has indicated a lack of operator enjoyment. This study aims to design an I/F that elicits operator enjoyment and identifies the factors that contribute to this enjoyment. We developed two I/Fs: a high degree of freedom I/F and a gradual flexibility degree of freedom I/F based on gamification to elicit operator enjoyment. Using these I/Fs, we conducted a field study in a real shopping mall to investigate the operators’ experiences. As a result, the operators in this experiment greatly enjoyed using our I/Fs. The results showed that our I/Fs could elicit operator enjoyment with the following three I/F factors suggested as potentially important design guidelines: ease of use through anonymity, moderate restriction of freedom, and sharing experiences with a group of operators.

Mobile robots are increasingly being utilized as guides in various settings. Ensuring efficient and hospitable interactions between robots and individuals is crucial for their successful implementation. However, there is a lack of understanding regarding the specific robot behaviors that can effectively guide individuals to their destinations while providing a sense of hospitality. In this study, we investigate two robot behaviors: “vertical oscillation motion” and “looking back motion,” with the objective of identifying behaviors that can optimize efficiency and hospitality in a guide robot. The vertical oscillation motion replicates the natural up-and-down movement of the human body during walking, while the looking back motion establishes eye contact and conveys a sense of hospitality. To evaluate the effectiveness of these behaviors, we conducted experiments with actual visitors at a shopping mall. Participants were exposed to the robot's behaviors and their responses were analyzed through questionnaires and interviews. The results revealed that the looking back motion successfully conveyed the robot's hospitality, while the vertical oscillation motion instilled a sense of urgency in individuals. However, it was found that only the looking back motion effectively motivated individuals to promptly commence walking towards the robot. These findings highlight the significance of incorporating specific robot behaviors to enhance both efficiency and hospitality in guiding individuals to their destinations. By understanding the impact of these behaviors, we can develop guide robots that accommodate a larger number of individuals while increasing their satisfaction. Future research endeavors should focus on evaluating the effectiveness of these behaviors in real-world environments, ensuring their practical applicability.

Humanlike robots interact with people in daily situations, and various studies concerning such robots have been conducted. However, robots are easily ignored due to their lack of social presence, with their customer service behavior and sales strategies not working well in many situations. In this paper, we aim to improve the social presence of a sales robot by enabling shared attention with visitors. In an actual shop, we investigated whether a robot could improve its social presence by indicating that it could understand the gaze direction of visitors. We found that the robot's statements regarding the direction of the visitor's gaze information and the timing of such statements with the visitor's gaze change improved the robot's social presence, leading to an increase in the number of groups that looked at the robot for a longer period. This paper reveals that enabling shared attention between humans and robots can strengthen a robot's social presence and its ability to work effectively in a real-world environment.

Robotic salespersons have been adopted by many shops. However, due to the weakness of their social presence, they are easily ignored by visitors. Thus, we focused on such robots' behaviors that can strengthen their social presence in a real-world shop. In this research, our goal is to develop a model that can obtain visitors' replies to the robot's utterances. For this reason, we conducted a laboratory experiment and two field experiments. In the laboratory experiment, we found that the robot's ability to express that it can understand the degree of visitors' attention to the robot is important for improving its social presence. Afterward, we developed an engagement estimation model (EEM) based on the findings obtained from the laboratory experiment. We defined visitors' engagement as the probability that the visitors will reply to the robot's utterances. The EEM estimates the engagement from the visitors' real-time nonverbal data. In a laboratory experiment, the situation of being in the laboratory can make the interaction between the participants and the robot unnatural. Therefore, we developed a model based on data of visitors' nonverbal cues in the field experiment and examined whether the model works effectively in the real-world environment. As a result, the automatic greeting mode based on the EEM facilitated the participant's reply to the robot. Thus, we considered that this is because the automatic greeting mode could make a decision of the robot's next behavior precisely. It can be considered that the visitors may feel as if the robot could understand their degree of attention to the robot when the robot greets the visitors based on the automatic greeting mode. Therefore, the automatic greeting mode based on the EEM worked effectively in a real-world environment and could strengthen its social presence.

In recent years, robotic salespersons have been rapidly deployed in various shops especially in Japan. However, it is still unclear what kind of action is effective for sales, and robotic salespersons are often ignored by customers. In this paper, we analyzed the multimodal conversations between a robotic salesperson and visitors by conducting a field experiment. We aim to investigate the actions of the robot that lead to interactive conversations. The results of the experiment showed that in order to conduct an interactive conversation, it is necessary to a give short speech that is easy to answer. The most important finding obtained from this research is that the impression of a robot is strongly influenced by the beginning of the interaction. When a robot gives a short speech that is easy to answer at the beginning of the interaction, an interactive conversation can start because the customers treat the robot similar to a salesperson which is capable of humanlike interaction.