Exploring Factors Influencing Hospitality in Mobile Robot Guidance: A W izard-of- O z Study with a Teleoperated Humanoid Robot (2025)

Abstract: Developing mobile robots that can provide guidance with high hospitality remains challenging, as it requires the coordination of spoken interaction, physical navigation, and user engagement. To gain insights that contribute to the development of such robots, we conducted a Wizard-of-Oz (WOZ) study using Teleco, a teleoperated humanoid robot, to explore the factors influencing hospitality in mobile robot guidance. Specifically, we enrolled 30 participants as visitors and two trained operators, who teleoperated the Teleco robot to provide mobile guidance to the participants. A total of 120 dialogue sessions were collected, along with evaluations from both the participants and the operators regarding the hospitality of each interaction. To identify the factors that influence hospitality in mobile guidance, we analyzed the collected dialogues from two perspectives: linguistic usage and multimodal robot behaviors. We first clustered system utterances and analyzed the frequency of categories in high- and low-satisfaction dialogues. The results showed that short responses appeared more frequently in high-satisfaction dialogues. Moreover, we observed a general increase in participant satisfaction over successive sessions, along with shifts in linguistic usage, suggesting a mutual adaptation effect between operators and participants. We also conducted a time-series analysis of multimodal robot behaviors to explore behavioral patterns potentially linked to hospitable interactions.

## introduction recent advancements in mobile robotics and human-robot interaction have enabled the deployment of robots for mobile guidance tasks in various environments @xcite @xcite . for example, vásquez and matía (2020) and @xcite developed mobile robots capable of object detection, environmental sensing, and emotion expression. despite these advances, developing mobile robots that can provide guidance with high hospitality remains challenging, as it requires the consideration of spoken interaction, physical navigation, and user engagement. to address these challenges, we conducted a wizard-of-oz (woz) study using teleco, a teleoperated humanoid robot, to explore the factors influencing hospitality in mobile robot guidance. specifically, we enrolled 30 participants as visitors to an experimental exhibition space simulating an aquarium-like environment and two trained operators, who teleoperated teleco to provide mobile guidance to the participants, as shown in fig. 1 . a total of 120 dialogue sessions spanning over ten hours of interaction were collected, along with evaluations from both participants and operators regarding the hospitality of each interaction. note that, in this study, we define hospitality as the overall quality of the guidance experience, including how welcoming, engaging, and informative the interaction felt. we analyzed the collected dialogue data from two perspectives: linguistic usage and multimodal robot behaviors. we first clustered system utterances and analyzed the frequency of categories in high-and low-satisfaction dialogues. the results showed that short responses appeared more fre-quently in high-satisfaction dialogues. moreover, we observed a general increase in participant satisfaction over successive sessions, along with shifts in linguistic usage, suggesting a mutual adaptation effect between operators and participants. we also conducted time-series analysis of multimodal behaviors and found that sessions with active engagement from both users and operators, through both speech and nonverbal actions, were associated with higher hospitality compared to sessions dominated by one-sided interactions. ## related work mobile robots have been used in a variety of human-interaction scenarios, especially for guiding visitors in museums, aquariums, and other public spaces @xcite @xcite . early work such as minerva @xcite and rhino @xcite has demonstrated the capability of robots for museum tour guidance using probabilistic navigation methods. honda's asimo @xcite further advanced robot mobility, enabling autonomous walking and utilization in receptionist and information guidance roles. the recently developed pepper robot is equipped with capabilities for emotional expression and wheeled navigation, targeting customer service @xcite . vásquez and matía (2020) developed doris, a tour guide robot capable of autonomously navigating predefined waypoints and conveying emotional expressions through dialogue templates. similarly, @xcite incorporated environmental recognition, enabling autonomous navigation by detecting objects and surroundings in indoor environments. iio et al. (2020) while these studies have advanced the technical and functional capabilities of mobile guidance robots, little attention has been paid to hospitality in the context of mobile robot interaction. to address this gap, this study investigates factors influencing perceived hospitality during mobile robot guidance through a woz experiment. ## wizard-of-oz data collection for mobile robot guidance to investigate the interaction factors that influence the perception of hospitality, we conducted a woz experiment using teleco foot_0 , a humanoid mobile robot equipped with an oled display and wheeled mobility, as shown in fig. 1 . the experiment was conducted in an indoor space designed to simulate an aquarium-like exhibition environment, where the robot guided participants by introducing animal figures and providing related explanations. during the experiment, we collected multimodal data and questionnaire responses from both participants and operators to analyze how different interaction factors affected perceived hospitality. the study was approved by our institute's ethics committee and was conducted in accordance with ethical guidelines. ## results and analysis to identify factors that influence perceived hospitality in mobile robot guidance, we conducted a multi-perspective analysis focusing on both linguistic usage and multimodal robot behaviors. our approach was informed by prior studies demonstrating the impact of language patterns on subjective perceptions in human-robot interaction @xcite , as well as the use of time-series analysis to uncover behavioral dynamics in interaction settings @xcite . we first examined the participant questionnaire results to evaluate the overall level of perceived hospitality and identify general trends across sessions. we then analyzed the robot's linguistic patterns using embedding-based clustering to identify language features associated with higher hospitality ratings. we further explored multimodal behavioral patterns using time-series clustering of robot behaviors to uncover interaction dynamics linked to high perceptions of hospitality. ## conclusion and future work in this study, we explored factors contributing to perceived hospitality in mobile robot guidance through a woz experiment with a teleoperated teleco robot. we analyzed 120 dialogue sessions from both linguistic and multimodal behavioral perspectives. the linguistic analysis revealed that short responses, which reflected a casual and empathetic communication style, were associated with higher hospitality ratings. we also observed a general increase in participant satisfaction over successive sessions, accompanied by shifts in operators' linguistic usage. furthermore, the multimodal behavior analysis identified distinct behavioral patterns, demonstrating that fostering mutual engagement between users and operators, rather than relying on one-sided interactions, played a critical role in enhancing perceptions of hospitality. this research has several limitations that should be addressed in future work. first, the current categorization of utterances may lack sufficient granularity, as question types were not clearly differen-tiated between yes/no and open-ended questions. a more detailed categorization of utterance types can be used for analysis. second, additional analysis methods should be applied, such as sentiment analysis @xcite and turn-taking analysis @xcite , to provide a more comprehensive understanding of the interactive nature in mobile robot guidance. third, as the current study relied primarily on utterances, a wider range of multimodal data should be incorporated into the analysis, including user-robot spatial positioning, movement patterns during guidance, and fluctuations in participants' ecg signals, to obtain deeper insights into factors influencing perceived hospitality. fourth, since our experiments were conducted in a controlled environment simulating an aquarium-like setting, future experiments should be extended to real-world settings, such as an actual aquarium, to further validate our findings. finally, as the woz approach may limit the exploration of the robot's true capabilities in mobile guidance, we plan to gradually incorporate automatic functions (e.g., utterance generation, gesture and facial expression generation, and autonomous movement control) into future experiments. we also aim to embed the identified influential factors into the autonomous mobile robot systems to evaluate their practical effectiveness in enhancing hospitality during realworld interactions.