Robot therapy for elderly residents in a care house has been conducted since June 2005. Two therapeutic seal robots were introduced and activated for over 9 hours every day to interact with the residents. This paper presents a progress report of this experiment. In order to investigate the psychological and social effects of the robots, each subject was interviewed by using the free pile sort method, and their social interaction was analysed. In addition, their hormones in urine: 17 -Ketosteroid sulfate (17-KS-S) and 17hydroxycorticosteroids (17-OHCS) were obtained and analysed. The results showed that the robots encouraged them to communicate with each other and then strengthened their social ties over the two months. Furthermore, urine tests showed that the reactions of the subjects' vital organs to stress were improved after the introduction of the robots.
Abstract-We are developing an interactive service robot which provides personal greetings to customers, using a machine-learning approach based on observations of a customer's appearance or behavior from on-board or environmental sensors. For each visit, several features are recorded, such as "time of day" or "number of people in group." A set of classifiers trained by human coders compare the current features with the person's individual history, to determine an appropriate feature for a robot to speak about. This system enables the robot to make context-appropriate comments such as "good morning, you're here very early today." We present the design of our system and an encouraging set of preliminary prediction results based on one month of data taken from real customers at a shopping mall.
IndexTerms-Human-robot interaction, long-term interaction
The development of humanlike service robots which interact socially raises a new question: how can we create good interaction content for such robots? Domain experts specializing in the target service have the knowledge for making such content. Yet, while they can easily engage in good face-to-face interactions, we found it difficult for them to prepare conversational content for a robot in written form. Instead, we propose involving experts as teleoperators in a short-cycle iterative development process in which the expert develops content, teleoperates a robot using that content, and then revises the content based on that interaction. We propose a software system and design guidelines to enable such an iterative design process. To validate these solutions, we conducted a comparison experiment in the field, with a teleoperated robot acting as a guide at a tourist information center in Nara, Japan. The results showed that our system and guidelines enabled domain experts with no robotics background to create better interaction content and conduct better interactions than domain experts without our system.
This paper presents a design of the previous proposed behavior decision system with storage in mobile robots. An index, that is, the functional called tension level with two or more emotions and fuzzy similarity level are noticed as important factors. The former is memorized with another data in a storage module and is used in a reproduction module and a behavior decision module. The latter is used in a matching processing between memory and current status.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.