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.

When an automatic wheelchair or a self-carrying robot moves along with human agents, prediction for the next possible actions by the participating agents, play an important role in realization of successful cooperation among them. In this paper, we mounted a robot to a wheelchair body so that it provides embodied projective signals to the human agents, indicating the next possible action to be performed by the wheelchair. We have analyzed how human participants, particularly when they are in a multiparty interaction, would respond to such a system in experiments. We designed two settings for the robot's projective behavior. The first design allows the robot to face towards the human agents (Face-to-Face model), and the other allows it to face forward as the human agents do, then turn around to the human agents when it indicates where the wheelchair will move to (Body-Torque model). The analysis examined reactions by the human agents to the wheelchair, his/her accompanying human agent, and others who pass by them in the experiment's setting. The results show that the Body-Torque model seems more effective in enhancing cooperative behavior among the human participants than the Face-to-Face model when they are moving to a forward direction together.

In this research, we aim to reveal the difference between robot mediated multi-party human interaction and human mediated multi-party human interaction. We do this by examining and comparing the multi-party participants' interactions towards the robot human mediators in regard to the mediator's questions. From this experiment, we found that the participants engaged in interaction among each other more when the questioner was the robot. This paper suggests a concept and a design of robots, which enhances social interaction among humans because of its intervention.

In this article, we discuss our findings from an ethnographic study at an elderly care center where we observed the utilization of two different functions of human gaze to convey service order (i.e., “who is served first and who is served next”). In one case, when an elderly person requested assistance, the gaze of the care worker communicated that he/she would serve that client next in turn. In the other case, the gaze conveyed a request to the service seeker to wait until the care worker finished attending the current client. Each gaze function depended on the care worker's current engagement and other behaviors. We sought to integrate these findings into the development of a robot that might function more effectively in multiple human-robot party settings. We focused on the multiple functions of gaze and bodily actions, implementing those functions into our robot. We conducted three experiments to gauge a combination of gestures and gazes performed by our robot. This article demonstrates that the employment of gaze is an important consideration when developing robots that can interact effectively in multiple human-robot party settings.

In order to reduce the burden of caregivers facing an increased demand for care, particularly for the elderly, we developed a system whereby multiple robotic wheelchairs can automatically move alongside a companion. This enables a small number of people to assist a substantially larger number of wheelchair users effectively. This system utilizes an environmental map and an estimation of position to accurately identify the positional relations among the caregiver (or a companion) and each wheelchair. The wheelchairs are consequently able to follow along even if the caregiver cannot be directly recognized. Moreover, the system is able to establish and maintain appropriate positional relations.

We have been conducting research on ways to contribute to reducing the workload of caregivers. We developed a wheelchair capable of following a single accompanying caregiver in a parallel position. However, observations in actual care facilities revealed that people often move as a group: for instance, two caregivers each pushed a wheelchair together. Therefore, we now aim to develop a robotic wheelchair system that allows multiple wheelchairs and accompanying caregivers to coordinate their movement together. However, such a situation necessitates a complex system. Making such a system practical represents an enormous challenge. Therefore, as a first step we decided to break down this complex “multiple-multiple” situation by isolating particular instances with multiple wheelchairs and/or multiple caregivers. In this paper, we focus on the “single-multiple” situation; i.e., a situation where a single wheelchair user is accompanied by multiple accompanies. We propose a robotic wheelchair system that facilitates coordinated movement between the wheelchair and the caregivers. In other words, the wheelchair system will track multiple people in the vicinity using GPGPU, and distinguish the accompanying caregivers from among other passersby based on the trajectory of the individuals' movement.

Although it is desirable for wheelchair users to move alone by operating wheelchairs themselves, they are often pushed or accompanied by caregivers, especially in elderly care facilities. In designing robotic wheelchairs, therefore, it is important to consider how to reduce the caregiver's load and support their activities. We particularly focus on communication among wheelchair users and caregivers because face-to-face communication is known to be effective in ameliorating elderly mental health issues. Hence, we propose a maneuverable robotic wheelchair that can move autonomously towards a goal while considering the situation of the accompanying caregiver. Our robotic wheelchair starts to move autonomously towards the goal as soon as the caregiver sets the goal position, such as a bathroom, by utilizing its touch panel interface. While moving towards the goal, the robotic wheelchair autonomously controls its speed and direction of movement to facilitate natural communication between the wheelchair user and the caregiver, by observing the situation of the accompanying caregiver.

Museum guide robots should observe visitors in order to identify those who may desire a guide, and then initiate conversation with them. This paper presents a model for such robot behavior. Initiation of conversation is an important concern for social service robots such as museum guide robots. When people enter into a social interaction, they tend to situate themselves in a spatial-orientational arrangement such that each is facing inward around a space to which each has immediate access. When this kind of particular spatial formation occurs, they can feel that they are participating in the conversation; once they perceive their participation, they will subsequently try to maintain this spatial formation. We developed a model that describes the constraints and expected behaviors in initiation of conversation. Experimental results demonstrate that our model significantly improves a robot's performance in initiating conversation.

From our ethnographic studies on various kinds of museums, we discovered that guides routinely propose questions to visitors in order to draw their attention towards both his/her explanation and the exhibit. The guides' question sequences tend to begin with a pre-question which serves to not only monitor visitors' behavior and responses, but to also alert visitors that a primary question would follow. We implemented this questioning-strategy with our robot system and investigated whether this strategy would also work in human-robot interaction. We developed a vision system that enables the robot to choose an appropriate visitor by monitoring a visitor's response from the initiation of a pre-question to the following pause. Results indicate that this questioning-strategy works effectively in human-robot interaction. In this experiment, the robot asked visitors about a photograph. At the pre-question, the robot delivered a rather easy question followed by a more challenging question (Figure 1). More participants turned their head away from the exhibition when they were not sure about their answer to the question. They either faced away from the robot, or smiled wryly at the robot or at each other. These types of behaviors index participants' states of knowledge, which we could utilize to develop a system by which the robot could choose an appropriate candidate by computational recognition.

In this paper, we present our work designing a robot that explains an exhibit to multiple visitors in a museum setting, based on ethnographic analysis of interactions between expert human guides and visitors. During the ethnographic analysis, we discovered that expert human guides employ some identical strategies and practices in their explanations. In particular, one of these is to involve all visitors by posing a question to an appropriate visitor among them, which we call the "creating a puzzle" sequence. This is done in order to draw visitors' attention towards not only the exhibit and but also the guide's explanation. While creating a puzzle, the human guide can monitor visitors' responses and choose an "appropriate" visitor (i.e. one who is likely to provide an answer). Based on these findings, sociologists and engineers together developed a guide robot that coordinates verbal and non-verbal actions in posing a question or "a puzzle" that will draw visitors' attention, and then explain the exhibit for multiple visitors. During the explanation, the robot chooses an "appropriate" visitor. We tested the robot at an actual museum. The results show that our robot increases visitors' engagement and interaction with the guide, as well as interaction and engagement among visitors.

A mobile museum guide robot is expected to establish a proper spatial formation with the visitors. After observing the videotaped scenes of human guide-visitors interaction at actual museum galleries, we have developed a mobile robot that can guide multiple visitors inside the gallery from one exhibit to another. The mobile guide robot is capable of establishing spatial formation known as "F-formation" at the beginning of explanation. It can also use a systematic procedure known as "pause and restart" depending on the situation through which a framework of mutual orientation between the speaker (robot) and visitors is achieved. The effectiveness of our method has been confirmed through experiments.

This paper presents our ongoing work developing service robots that provide assisted-care, such as serving tea to the elderly in care facilities. In multi-party settings, a robot is required to be able to deal with requests from multiple individuals simultaneously. In particular, when the service robot is concentrating on taking care of a specific person, other people who want to initiate interaction may feel frustrated with the robot. To a considerable extent this may be caused by the robot's behavior, which does not indicate any response to subsequent requests while preoccupied with the first. Therefore, we developed a robot that can display acknowledgement, in a socially acceptable manner, to each person who wants to initiate interaction. In this paper we focus on the task of tea-serving, and introduce a robot able to bring tea to multiple users while accepting multiple requests. The robot can detect a person's request (raising their hand) and move around people using its localization system. When the robot detects a person's request while serving tea to another person, it displays its acknowledgement by indicating "Please wait" through a nonverbal action. Because it can indicate its acknowledgement of their requests socially, people will likely feel more satisfied with the robot even when it cannot immediately address their needs.

This video presents our ongoing work developing a robotic wheelchair that can move automatically alongside a caregiver. Recently, several robotic/intelligent wheelchairs possessing autonomous functions for reaching a goal and/or user-friendly interfaces have been proposed. Although ideally wheelchair users may wish to go out alone, they are often accompanied by caregivers. Therefore, it is important to consider how to reduce the caregivers' load and support their activities and facilitate communication between the wheelchair user and caregiver. Moreover, a sociologist pointed out that when a wheelchair user is accompanied by a companion, the latter is inevitably seen as a caregiver [1]. In other words, the equality of the relationship is publicly undermined when the wheelchair is pushed by a companion. Hence, we propose a robotic wheelchair which can move alongside a caregiver or companion, and facilitate easy communication between them and the wheelchair user. However, it is not always desirable for a caregiver to be alongside a wheelchair. For instance, a caregiver may step in front of the wheelchair to open a door, and pedestrians may be encumbered by the wheelchair and companion if they move along side-by-side in a narrow corridor. To cope with these problems, our robotic wheelchair can move alongside a caregiver collaboratively depending on the circumstances. A laser range sensor is employed to track the caregiver and observe the environment around the wheelchair [2]. When obstacles are detected in the wheelchair's path of motion, it adjusts its position accordingly. In the video we demonstrate these functions of our robotic wheelchair. We are now conducting experiments to confirm the effectiveness of our wheelchair at an elderly care center in Japan.

This paper introduces a service robot that provides assisted-care, such as serving tea to the elderly in care facilities. In multi-party settings, a robot is required to be able to deal with requests from multiple individuals simultaneously. In particular, when the service robot is concentrating on taking care of a specific person, other people who want to initiate interaction may feel frustrated with the robot. To a considerable extent this may be caused by the robot's behavior, which does not indicate any response to subsequent requests while preoccupied with the first. Therefore, we developed a robot that can project the order of service in a socially acceptable manner to each person who wishes to initiate interaction. In this paper we focus on the task of tea-serving, and introduce a robot able to bring tea to multiple users while accepting multiple requests. The robot can detect a person raising their hand to make a request, and move around people using its mobile functions while avoiding obstacles. When the robot detects a person's request while already serving tea to another person, it projects that it has received the order by indicating “you are next” through a nonverbal action, such as turning its gaze to the person. Because it can project the order of service and indicate its acknowledgement of their requests socially, people will likely feel more satisfied with the robot even when it cannot immediately address their needs. We confirmed the effectiveness of this capability through an experiment in which the robot distributed snacks to participants.

This paper presents a method of selecting the answerer from audiences for a museum guide robot. We performed the preliminary experiments that a robot distributed its gaze towards visitors to select an answerer and analyzed visitors' responses. From these experiments, we have found that the visitors who are asked questions by the robot feel embarrassed when they have no prior knowledge about the question and the visitor's gaze during the question plays an important role to avoid being asked question. Based on these findings we developed functions for a guide robot to select the answerer by observing behaviors of multiple visitors. Multiple visitors' head motions are tracked and recognized by using an omni-directional camera and a laser range sensor. The robot detects the visitors' positive and negative responses by observing their head motions while asking questions. We confirmed the effectiveness of our method by experiments.

An information-presenting robot is expected to establish an appropriate spatial relationship with people. Drawing upon sociological studies of spatial relationships involving "F-formation" and "body torque," we examined the effect of a robot rotating its body on the reconfiguration of the F-formation arrangement. The results showed that a robot can change the position of a visitor by rotating its body. We also confirmed that to reconfigure the F-formation arrangement, it is more effective to rotate the whole body of the robot than only its head.

This paper presents a method in a museum guide robot to choose an appropriate answerer among multiple visitors. First, we observed and videotaped scenes of gallery talk when human guides ask visitors questions. Based on an analysis of this video, we have found that the guides selects an answerer by distributing his or her gaze towards multiple visitors and observing the visitors' gaze responses during the question. Then, we performed experiments on a robot that distributes its gaze towards multiple visitors, and analyzed visitors' responses. From these experiments, we found that visitors who are asked questions by the robot felt embarrassed when he or she had no prior knowledge about the questions, and that visitor gaze during the questions plays an important role in avoiding being asked questions. Based on these findings, we have developed a function in a guide robot that observes visitor gaze response and selects an appropriate answerer based on these responses. Gaze responses are tracked and recognized using an omnidirectional camera and a laser range sensor. The effectiveness of our method was confirmed through experiments.

Designing technologies that support the explanation of museum exhibits is a challenging domain. In this paper we develop an innovative approach - providing a robot guide with resources to engage visitors in an interaction about an art exhibit. We draw upon ethnographical fieldwork in an art museum, focusing on how tour guides interrelate talk and visual conduct, specifically how they ask questions of different kinds to engage and involve visitors in lengthy explanations of an exhibit. From this analysis we have developed a robot guide that can coordinate its utterances and body movement to monitor the responses of visitors to these. Detailed analysis of the interaction between the robot and visitors in an art museum suggests that such simple devices derived from the study of human interaction might be useful in engaging visitors in explanations of complex artifacts.

As research over the last several decades has shown that non-verbal actions such as face and head movement play a crucial role in human interaction, such resources are also likely to play an important role in human-robot interaction. In developing a robotic system that employs embodied resources such as face and head movement, we cannot simply program the robot to move at random but rather we need to consider the ways these actions may be timed to specific points in the talk. This paper discusses our work in developing a museum guide robot that moves its head at interactionally significant points during its explanation of an exhibit. In order to proceed, we first examined the coordination of verbal and non-verbal actions in human guide-visitor interaction. Based on this analysis, we developed a robot that moves its head at interactionally significant points in its talk. We then conducted several experiments to examine human participant non-verbal responses to the robot's head and gaze turns. Our results show that participants are likely to display non-verbal actions, and do so with precision timing, when the robot turns its head and gaze at interactionally significant points than when the robot turns its head at not interactionally significant points. Based on these findings, we propose several suggestions for the design of a guide robot.

In this paper we consider the development of a museum guide robot that has both autonomous and remotely controlled features. We focus on the capabilities such a robot could have to help focus the attention of a visitor on an object or artefact. Inspired by studies of social interaction, which investigate whether the robot could deploy "restarts" and "pauses" at certain moments in its talk to first elicit the visitor's attention/gaze towards the robot. We report an experiment where we deployed such a robot to interact with real visitors to a science museum. These experiments show that such a strategy does seem to have a significant impact on obtaining the visitor's gaze.

We are currently working on a museum guide robot with an emphasis on "friendly" human-robot interaction displayed through nonverbal behaviors. In this paper, we focus on head gestures during explanations of exhibits. The outline of our research is as follows. We first examined human head gestures through an experimental, sociological approach. From this research, we have discovered how human guides coordinate their head movement along with their talk when explaining exhibits. Second, we developed a robot system based on these findings. Third, we evaluated human-robot interaction, again using an experimental, sociological approach, and then modified the robot based on the results. Our experimental results suggest that robot head turning may lead to heightened engagement of museum visitors with the robot. Based on our preliminary findings, we will describe a museum guide robot that first works autonomously and, if necessary, can turn into remote-control mode operated by a human to engage in more complex interaction with visitors.

We are currently working on a museum guide robot with an emphasis on "friendly" human-robot interaction as displayed through nonverbal behaviors. In this paper, we focus on head gestures during explanations of exhibits. The outline of our research is as follows. We first examined human head gestures through an experimental, sociological approach, and have discovered the ways human guides coordinate their head movement along with their talk when explaining exhibits. Second, we developed a robot system based on these findings. Third, we evaluated human-robot interaction, again using an experimental, sociological approach, and then modified the robot based on the results. Our experimental results suggest that robot head turning may lead to heightened engagement of museum visitors.

Recently a number of researchers have uncovered various ways in which paper documents support everyday work practice and have suggested how these may be reflected in the design of new technologies. In this paper we consider how activities on and around paper documents may be supported when participants are remote from each other. When we consider the uses of an experimental system that provides a number of resources for supporting work over documents, it becomes apparent how critical it is to support apparently simple pointing and referencing, and how complex such conduct can be. This suggests some considerations both for developers of enhanced media spaces and analysts of everyday conduct.Clarified descriptions of technology and fragments including changes to figures. Added points concerning the scope of the technology the conception of sequence and calrified the requirement regarding redundancy. Revised descriptions of fragments in an atempt to make thsee less dense Corrected several typographic errors including those mentioned by the reviewers' gesture.

Face or head movement plays an important role in human communication. This paper presents a museum guide robot that moves its head to communicate smoothly with humans. We have analyzed the behavior of human guides when they explain exhibits to visitors. Then, we have developed a robot system that can recognize the human's face movement using vision. The robot turns its head depending on the human's face direction and the contents of utterances. We use the analysis results of human behavior to control the head movements. Experimental results show that it is effective for the guide robot to turn its head while explaining exhibits

The aim of our study is to investigate systems for supporting remote instruction via a mobile robot. In the real world, instructions are typically given through words and body orientations such as head movements, which make it possible to project others' actions. Projectability is an important resource in organizing multiple actions among multiple participants in co-ordination with one another. It can likewise be said that in the case of robot-human collaboration, it is necessary to design a robot's head so that a local participant can project the robot's (and remote person's) actions. GestureMan is a robot that is designed to support such projectability properties. It is argued that a remote controlled mobile robot, designed as a communication medium, makes relevant dual ecologies: ecology at a remote (robot operator's) site and at a local participant's (robot's) site. In order to design a robot as a viable communication medium, it is essential to consider how these ecologies can be mediated and supported.

In this paper we investigated systems for supporting remote collaboration using mobile robots as communication media. It is argued that the use of a remote-controlled robot as a device to support communication involves two distinct ecologies: an ecology at the remote (instructor's) site and an ecology at the operator's (robot) site. In designing a robot as a viable communication medium, it is essential to consider how these ecologies can be mediated and supported. In this paper, we propose design guidelines to overcome the problems inherent in dual ecologies, and describe the development of a robot named GestureMan-3 based on these guidelines. Our experiments with GestureMan-3 showed that the system supports sequential aspects of the organization of communication.

It is increasingly recognized that social interaction and collaboration rely on the participants' abilities to access and use a range of resources including objects and artifacts from within the immediate environment. In recent years, system support for remote collaboration has begun to address this issue, and we have witnessed the emergence of a number of technologies designed to provide remote participants with access to (features of) each others' environment. In this article we examine the use of one such system, an innovative mixed media environment designed to enable participants to refer to and point at objects and artifacts within each other's remote environment. The article addresses the ways in which participants use the system to undertake various collaborative activities and discusses the problems and issues that emerge, for the participants' themselves, in coordinating action with and through objects. We then consider these issues with regard to interaction and collaboration in more conventional environments such as work settings, and we discuss the ways in which the interpretation and production of action are inextricably embedded within the immediate environment, an environment of action that is inadvertently fractured in even this more sophisticated media space.

Drawing on studies of experimental systems and everyday settings we explore the relationship between social interaction and its environment. We show how interaction is inextricably embedded within its environment and discuss the ways in which innovative systems designed to support remote collaboration inadvertently fracture conduct from its setting, and undermine the participants abilities to produce, interpret and coordinate activities. We discuss the implications of these issues for the design of future systems, and, more critically, for studies of work and collaboration. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

When designing systems that support remote instruction on physical tasks, one must consider four requirements: 1) participants should be able to use non-verbal expressions, 2) they must be able to take an appropriate body arrangement to see and show gestures, 3) the instructor should be able to monitor operators and objects, 4) they must be able to organize the arrangement of bodies and tools and gestural expression sequentially and interactively. GestureMan was developed to satisfy these four requirements by using a mobile robot that embodies a remote instructors actions. The mobile robot mounts a camera and a remote control laser pointer on it. Based on the experiments with the system we discuss the advantage and disadvantage of the current implementation. Also, some implications to improve the system are described.

No abstract available.

A system which supports remote instruction for physical tasks in the real world should support following requirements: 1) flexibility of the body arrangement; 2) awareness of each other's orientations; and 3) communication of gestural information. To satisfy these requirements, we developed a system named "GestureMan". GestureMan is a mobile robot mounted with three cameras and a remotely controlled laser pointer on it. An instructor controls the robot remotely with a joystick and gives instruction to an operator. Two preliminary experiments using a low-speed Satellite link and high-speed ATM network respectively show that GestureMan has an ability to support the remote instruction. Furthermore, gigabit network enabled the natural interaction between the instructor and the operator by alleviating limitations such as time delay and narrow field of view.