This study explores an unexplored area in robot-robot interaction: human perception of robots when multiple robots interact. The authors developed cart-type and tabletop robots that communicates using unintelligible audio. The authors hypothesized that auditory interaction, similar to dialogue influences human impressions. In a preliminary online survey, participants viewed videos of the robots in the dialog condition (the cart-type robot responding to the tabletop robot's vocalizations) or non-dialog condition (the cart-type robot acting alone). Preliminary survey showed that the dialog condition was rated higher, especially the perception of robot purposefulness and the perception of relationships between robots. These results suggest that auditory interactions can have an impact on human impressions and foster a sense of intentionality and relational understanding between robots.

Abstract This paper describes research into the development of an artificial intelligence (AI) based music therapist (AI music therapist) for elderly people with dementia. Music therapy is expected to be effective for the ‘behavioural and psychological symptoms’ of dementia and thus contribute to reducing the burden of caregiving. However, the number of music therapists in Japan is very small compared to the number of elderly people with dementia, and not all elderly people with dementia in Japan have easy access to music therapy. Therefore, in order to enable elderly people with dementia to receive music therapy anytime, anywhere and as many times as possible, we are developing a virtual music therapist (AI music therapist) called ‘Satsuki-san’, who appears on a computer screen. In this paper, we report on the latest version of ‘Satsuki-san’ and collect opinions from caregivers actually engaged in the care of elderly people with dementia and music therapists with extensive clinical practice experience with elderly people with dementia. The opinions of the caregivers and music therapists showed a high level of expectation for the AI music therapist, but they also pointed out a number of problems, for example about Satsuki’s speech, such as the need for more intonation. The music therapists also pointed out a number of areas for improvement with regard to singing accompaniment. In the future, we would like to collect a variety of data from the subjects of music therapy through the use of the AI music therapists and establish a music digital therapeutics that can objectively evaluate the subjects’ condition and predict the progression of dementia.

The purpose of our study is to investigate human teaching behavior and robot learning behavior when a human teaches a robot. Agents for learning support need to build a pedagogical relationship, in which a teacher agent and a student agent change their behaviors as they recognize the other's characteristic behaviors. In order to investigate how a robot that behaves as a student should respond to humans' teaching behaviors in a pedagogical relationship between human and robot, we conducted a case study using a game played on a tablet with a robot. In the case study, we analyzed how humans changed their teaching behaviors when the humanoid robot failed to understand what they taught. From the results of this case study, we observed that some subjects carefully taught the robot in each trial in order to allow the robot to understand the subjects. Moreover, we also observed that subjects' teaching behavior changed when the subject received feedback from the robot about the teaching.

In this paper, we propose an electric power management system for delivering power to home appliances with mobile robots. With our system, the user places an appliance without power cables freely within the home, and a robot provides the appliance with the electric power required for its operation. In addition to providing explanations of a usage scenario and a theoretical analysis, we demonstrate a prototype implementation. The robot of the prototype autonomously locates the target appliance, transfers its battery power to the appliance, and returns to the home position to recharge its battery. The validation study showed our proof-of-concept prototype worked as expected by the theory.

The style in which a robot moves, expressed through its gait or locomotion, can convey effective messages to people. For example, a robot could move aggressively in reaction to a person's actions, or alternatively react using a set of careful, submissive movements. Designing, implementing and programming robotic interfaces that react to users' actions with properly styled movements can be a difficult, daunting, and time consuming technical task. On the other hand, most people can easily perform such stylistic tasks and movements, for example, through acting them out.

Unpredictable user behaviors in a physical process represent one of the fundamental obstacles to the realization of a Cyber-Physical System. In this paper, we propose the use of social cues such as body shape, expressions, and verbal timing to control user behaviors in the physical world. Social cues can control user behaviors in both their spatial and temporal aspects. As a result, user actions become more predictable in a CPS. We consider how social cues restrict user behaviors by referring to a number of psychological, cognitive, and human-robot interaction studies, and we propose a model of restriction based on social cues. Using this model, we created hardware and software in order to realize attachable social cues, and we seek to demonstrate the effect of social cues using the example of home appliances.

This paper proposes a physical user interface for a user to teach a robot to navigate a home environment. The user places small devices containing infrared based communication functionality as landmarks in the environment. The robot follows these landmarks to navigate to a goal landmark. Active landmarks communicate with each other to map their spatial relationships. Our method allows the user to start using the system immediately after placing the landmarks without installing any global position sensing system or prior mapping by the robot.

Robots are poised to enter our everyday environments such as our homes and offices, contexts that present unique questions such as the style of the robot's actions. Style-oriented characteristics are difficult to define programmatically, a problem that is particularly prominent for a robot's interactive behaviors, those that must react accordingly to dynamic actions of people. In this paper, we present a technique for programming the style of how a robot should follow a person by demonstration, such that non-technical designers and users can directly create the style of following using their existing skill sets. We envision that simple physical interfaces like ours can be used by non-technical people to design the style of a wide range of robotic behaviors.

We propose a simple drag-and-drop interface on a touch screen to give instructions to an object-delivery robot. The user uses a finger to drag a target object and drop it to a target location on the screen that shows an image of the floor provided by a ceiling camera. The system then autonomously executes a delivery task without continuous control by the user. We employ user-guided computer vision methods to identify and track an object in a scene without prior registration. We conducted a user study, which showed that the participants completed separate tasks more successfully when using our method than when using a remote controller.

Typical Human Robot Interaction (HRI) assumes that the user explicitly interacts with robots. However, explicit control with robots can be unnecessary or even undesirable in certain cases, such as dealing with domestic services (or housework). In this paper, we propose an alternative strategy of interaction: the user implicitly controls a robot by issuing commands on corresponding real world objects and the environment. Robots then discover these commands and complete them in the background. We implemented a paper-tag-based interface to support such implicit robot control in a sensor-augmented home environment. Our initial user studies indicated that the paper-tag-based interface is particularly simple to use and provides users with flexibility in planning and controlling their housework tasks in a simulated home environment.

This paper proposes a robot communication strategy that enables a human's context to be incorporated into a robot's context. The strategy's fundamental principle is that a robot will show awareness of a human's context. In our pilot study, many participants did not actually start interacting with the robot, but tested its functionality. According to the results of that pilot study, we implemented a robot with behaviors that showed awareness of such peculiar human's behaviors. We conducted a field experiment to verify the effectiveness of the robot's behaviors for showing awareness. The results indicated that showing awareness can be a method for involving humans in an interaction with a robot.

This paper investigates a communication model which explains what behaviors make humans think that they share information with a robot. We focus on the motion of a robot’s gaze which is synchronized with a human’s gesture and a gaze direction, and propose a communication model for a robot to share real world information with a human. We have conducted a psychological experiment and reveals the effect of the simultaneous behaviors. The result indicated that the simultaneous behaviors give actuality to the robot’s utterance when it refers to physical world information.

This paper proposes a new task selection method for multi-task communication robots. As robot technology improves, communication robots are being used in public places. These communication robots are meant to perform patrol, promotion, or guidance activities in place of humans. When a communication robot is implemented for multiple purposes, it is important that the robot be able to appropriately select its own tasks. In this paper, we propose a collaborative task casting method to support communication robots when they are selecting a task. We also describe the implementation of a task management system based on the proposing method. This system takes into account global task achievement and balances task occupation to ensure that adequate robot resources are directed towards each task.