Recently, the importance of community-centric systems is increasing in the human society. Human-centric systems can enhance the accessibility and usability of systems and devices, and they can... Show More

Recently, the importance of community-centric systems is increasing in the human society. Human-centric systems can enhance the accessibility and usability of systems and devices, and they can improve the quality of life in many areas such as supporting human activities, communication and interactions in healthcare, and welfare. However, there is a need to shift from human-centric systems to community-centric systems and improve the quality of community in social networks and communities. This paper provides a survey of human-centric and community-centric systems. In the case of human-centric systems the acquisition of human data including sensing, monitoring and gathering data for life log are discussed. Constructing user models and applying the models for health care support are also proposed. In the case of community-centric systems, the community detection on the Web is presented. Various visualization systems for community detection on the Web are introduced. Emergency support systems as an important application of community-centric systems are discussed as well.

This paper presents a health promotion system with robot partner for elderly care. Aging society in Japan has been a big serious problem. The number of caregivers is not enough in the current... Show More

This paper presents a health promotion system with robot partner for elderly care. Aging society in Japan has been a big serious problem. The number of caregivers is not enough in the current situation and is not expected to substantially increase in future. Hence, comprehensive care and health promotion should be provided to heighten awareness about health. In this study, we built a daily exercise support system with a robot partner utilized as an exercise instructor. Moreover, we propose a human-robot communication model based on self-serving bias. In the experiment, we conduct a demonstration experiment and interview survey to discuss the validity of the communication model.

This paper discusses the direct perception of an unknown object and the action decision to grasp an unknown object using depth sensor for social robots. Conventional methods estimate the accurate... Show More

This paper discusses the direct perception of an unknown object and the action decision to grasp an unknown object using depth sensor for social robots. Conventional methods estimate the accurate physical parameters when a robot wants to grasp an unknown object. Therefore, we propose a perceptual system based on an invariant concept in ecological psychology, which perceives the information relevant to the action of the robot. Firstly, we proposed the plane detection based approach for perceiving an unknown object. In this paper, we propose the sensation of grasping which is expressed by using inertia tensor, and applied with fuzzy inference using the relation between principle moment of inertia. The sensation of grasping encourages the decision for the grasping action directly without inferring from physical value such as size, posture and shape. As experimental results, we show that the sensation of grasping expresses the relative position and posture between the robot and the object, and the embodiment of the robot arm by one parameter. And, we verify the validity of the action decision from the sensation of grasping.

When a robot considers an action-decision based on a future prediction, it is necessary to know the property of disturbance signals from the outside environment. On the other hand, the properties of... Show More

When a robot considers an action-decision based on a future prediction, it is necessary to know the property of disturbance signals from the outside environment. On the other hand, the properties of disturbance signals cannot be described simply, such as non-periodic function, nonlinear time-varying function nor almost-periodic function. In case of a robot control, sampling rate for control will be affected description of disturbance signals such as frequency or amplitude. If the sampling rate for acquiring a disturbance signal is not correct, the action will be taken far from its actual property. In general, future prediction using machine learning is based on the tendency obtained through past training or learning. In this case, an optimal action will be determined uniquely based on a property of disturbance. However, in this type of situation, the learning time increases in proportional to the amount of training data, either, the tendency may not be found using prediction, in the worst case. In this paper, we focus on prediction for almost-periodic disturbance. In particular, we consider the situation where almost-periodic disturbance signals occur. From this perspective, we propose a method that identifies the frequency of an almost- periodic function based on the frequency of the disturbance using Fourier transform, nearest-neighbor one-step-ahead forecasts and Nyquist-Shannon sampling theorem.

In a real-world environment, a social robot is constantly required to make many critical decisions in an ambiguous and demanding (stressful) environment. Hence, a biological stress response system... Show More

In a real-world environment, a social robot is constantly required to make many critical decisions in an ambiguous and demanding (stressful) environment. Hence, a biological stress response system model is a good gauge indicator to judge when the robot should react to such environment and adapt itself towards the environment changes. This work is to implement the Smerek's reflective processing model into human-robot communication application where reflective processing is triggered during such situations where the best action is not known. The authors want to investigate how to address better the human-robot communication problems with the focus on reflective processing model in the perspectives of working memory, Spiking Neural Network (SNN) and stress response system. The authors had applied their proposed Spiking Reflective Processing model for the human-robot communication application in a university population. The initial experimental results showed the positive attitude changes before and after the human-robot interaction experiment.