ATR Intelligent Robotics and Communication Laboratories

Kyoto, Japan

ATR Intelligent Robotics and Communication Laboratories

Kyoto, Japan
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Moriguchi Y.,University of Tokyo | Kanda T.,ATR Intelligent Robotics and Communication Laboratories | Ishiguro H.,Osaka University | Itakura S.,Kyoto University
Developmental Science | Year: 2010

Previous research has shown that young children commit perseverative errors from their observation of another person's actions. The present study examined how social observation would lead children to perseverative tendencies, using a robot. In Experiment 1, preschoolers watched either a human model or a robot sorting cards according to one dimension (e.g. shape), after which they were asked to sort according to a different dimension (e.g. colour). The results showed that children's behaviours in the task were significantly influenced by the human model's actions but not by the robot's actions. Experiment 2 excluded the possibility that children's behaviours were not affected by the robot's actions because they did not observe its actions. We concluded that children's perseverative errors from social observation resulted, in part, from their socio-cognitive ability. © 2009 Blackwell Publishing Ltd.

Chibani A.,University Paris Est Creteil | Amirat Y.,University Paris Est Creteil | Mohammed S.,University Paris Est Creteil | Matson E.,Purdue University | And 4 more authors.
Robotics and Autonomous Systems | Year: 2013

Ambient intelligence, ubiquitous and networked robots, and cloud robotics are new research hot topics that have started to gain popularity among the robotics community. They enable robots to acquire richer functionalities and open the way for the composition of a variety of robotic services with three functions: semantic perception, reasoning and actuation. Ubiquitous robots (ubirobots) overcome the limitations of stand-alone robots by integrating them with web services and ambient intelligence technologies. The overlap that exists now between ubirobots and ambient intelligence makes their integration worthwhile. It targets to create a hybrid physical-digital space rich with a myriad of proactive intelligent services that enhance the quality and the way of our living and working. Furthermore, the emergence of cloud computing initiates the massive use of a new generation of ubirobots that enrich their cognitive capabilities and share their knowledge by connecting themselves to cloud infrastructures. The future of ubirobots will certainly be open to an unlimited space of applications such as physical and virtual companions assisting people in their daily living, ubirobots that are able to co-work alongside people and cooperate with them in the same environment, and physical and virtual autonomic guards that are able to protect people, monitor their security and safety, and rescue them in indoor and outdoor spaces. This paper introduces the recent challenges and future trends on these topics. © 2013 Elsevier B.V. All rights reserved.

Okada M.,University of Shizuoka | Tada M.,ATR Intelligent Robotics and Communication Laboratories
ACM International Conference Proceeding Series | Year: 2014

Real-world learning in a field is an important educational area for experience-based activities. Formative assessment by constant monitoring of the intellectual achievement of real-world learners is essential for adaptive learning support, but no assessment methodology has yet been developed. We consider a method to systematically integrate heterogeneous factors of real-world learning: learners' internal situations, their external situations, and their learning field. Then, we propose a method for formatively assessing the situation of real-world learning. The method enables us to recognize the sequence of characteristic stay behavior and the associated body posture of a learner, and to estimate the 3D location of his/her interest. The method enables the estimation of not only the learning topic that a learner is currently examining in a field but also the prospective topics that he/she should learn. Our assessment method is the basis for context-aware support to promote the emergence of new knowledge from intellectual collaboration in the world. Copyright © 2014 by the Association for Computing Machinery, Inc.

Okada M.,University of Shizuoka | Tada M.,ATR Intelligent Robotics and Communication Laboratories
Proceedings 2012 17th IEEE International Conference on Wireless, Mobile and Ubiquitous Technology in Education, WMUTE 2012 | Year: 2012

Real-world learning is important because it encourages learners to obtain knowledge through various experiences. To increase the learning effects, it is necessary to analyze the diverse learning activities that occur in real-world learning and to develop workable strategies for learning support. Our viewpoint is that a real-world learning field is the key to promoting diverse learning interactions. Using the technologies of multimodal sensing and knowledge externalization, we propose a method to capture the time-series occurrence of real-world learning and to analyze the spatial characteristics of a learning field that draws out diverse intellectual interactions. Our data analysis found that each region in a learning field draws out different real-world learning. The analysis also showed that real-world knowledge is ubiquitously but unevenly distributed. Our method contributes toward discovering knowledge useful for learning support. © 2012 IEEE.

News Article | August 7, 2015

After the hitchhiking robot named hitchBOT met its demise after someone smashed the machine when it arrived in Philadelphia, it's easy to lose faith in humanity when it comes to us peacefully living alongside this technology. Now, a recent experiment conducted in Japan showed that children too can become bullies when coming in contact with a robot. Researchers from the ATR Intelligent Robotics and Communication Laboratories, Osaka University, Ryukoku University and Tokai University wanted to see how unsupervised children would react when encountering a so-called social robot. The researchers programmed the child-sized robot Robovie II to politely ask the humans it encountered to move aside and open the way so it could pass, letting it wander around a shopping mall in Osaka, Japan. Of course, the robot would catch the attention of people passing by, especially children. Robovie II was also programmed during simulations to predict children's behavior and assess the probability of abuse it could receive. The robot would stay close when a child with an adult walked close to it. When a single child approached it, the probability of abuse would increase, but in most cases, the child would move aside. However, it was programmed to have the probability for abuse rise the highest when it crossed paths with a group of children, and it would then escape from the pack of kids by changing direction. The researchers found that, in some cases, when Robovie II came in contact with a group of kids, they would ignore the robot's polite request, block its path and occasionally become violent toward it by kicking and hitting it. The researchers published a follow-up study that explored why children abuse robots, linking curiosity and the lack of empathy as the reasons. Robovie II is just one example of the social robots that may continue to be integrated into our everyday lives. These robots could be used as hotel receptionists or a friend for the home. Robovie II has also been used to help the elderly complete everyday tasks such as shopping.

Nomura T.,Ryukoku University | Takagi S.,ATR Intelligent Robotics and Communication Laboratories
Proceedings - 2011 International Conference on User Science and Engineering, i-USEr 2011 | Year: 2011

Recent Human-Robot Interaction (HRI) research has focused on human factors. To deepen the exploration of human factors in HRI, research has also investigated humans' educational backgrounds and gender, and the gender assignment of robots. In a psychological experiment, robot gender was assigned only by the name of the robot and a brief verbal instruction by the experimenters. The results showed that subjects with educational backgrounds of natural science and technology had stronger impressions toward the robot than did those of a social science background. Additionally, the perceived robot femininity and one of the impressions positively influenced the recall task scores of the robot's utterances, in particular in male samples. © 2011 IEEE.

Nomura T.,Ryukoku University | Kanda T.,ATR Intelligent Robotics and Communication Laboratories
International Journal of Social Robotics | Year: 2016

As interaction with robots grows, humans are expected to develop greater rapport with them. Assuming that such further interaction will fuel developmental research, we developed a psychological scale for measuring rapport called the Rapport–Expectation with a Robot Scale (RERS). From a controlled experiment where human participants interacted with a robot with/without behaviors based on relational strategies, our validation process found the following: (1) our RERS scale had sufficient internal consistency; (2) the robot behaviors, which were based on relational strategies, increased the participants’ RERS scores; and (3) participants who treated the robot as a human—like conversation partner had higher RERS scores than those who did not. © 2015, Springer Science+Business Media Dordrecht.

Nomura T.,Ryukoku University | Nomura T.,ATR Intelligent Robotics and Communication Laboratories
Proceedings - IEEE International Workshop on Robot and Human Interactive Communication | Year: 2015

In order to investigate what type of experiences of robots influences negative attitudes toward them, an online survey (N = 1,200) was conducted in Japan, by using the Negative Attitudes toward Robots Scale (NARS). The results suggested that (1) there were almost no strong relationships between types of robot experiences and gender, and age, (2) the correlations between negative attitudes toward robots and age were low, (3) experiences of robots in real situations decreased negative attitudes toward interaction with and social influences of robots in comparison with experiences via media, and (4) negative attitudes toward emotional interaction with robots were not affected by these experiences. © 2014 IEEE.

Nomura T.,Ryukoku University | Kanda T.,ATR Intelligent Robotics and Communication Laboratories
International Journal of Social Robotics | Year: 2015

To investigate influences of evaluation from robots, gazes from the robots, and humans’ fear of negative evaluation (FNE) into the humans’ preferences of the robots, we conducted an experiment in which a human-sized robot is used for an advisory role, providing suggestion in foreign-language education. There were three independent variables controlled: evaluation from robot (evaluative vs. non-evaluative robot), users’ FNE (low FNE vs. high FNE), and gaze from robot (refrained gazes vs. normal gazes), and dependent variables were participants’ preferences of the robot as subjective measures and amount of utterances as an objective measure. The experimental results suggested that when the robot evaluated participants with a lower FNE, they preferred to use the robot with normal gaze behavior more than those with a higher FNE. While the effect of refrained gaze is not clear for people with higher FNE, for people with lower FNE, refrained gaze reduced their intention to participate when the robot evaluated them. Moreover, the experimental results suggested that persons having higher FNE tend to trust the robot more, and participants spoke more when the robot did not evaluate them and when it used the normal gaze. This paper discusses the implications for applications with potential evaluation capability, e.g. for healthcare and education. © 2014, Springer Science+Business Media Dordrecht.

Nomura T.,Ryukoku University | Nomura T.,ATR Intelligent Robotics and Communication Laboratories | Nakao A.,Ryukoku University
International Journal of Social Robotics | Year: 2010

Expressive behaviors based on body motions are one of the useful methods that social robots present their emotional states toward users. On the other hand, some psychological research found age dependence on emotion identification in human facial expressions. In order to investigate this dependence in affective body expressions of robots, a psychological experiment was conducted in Japan, by using a small-sized humanoid robot on which three types of affective motion expression (anger, sadness, and pleasure) were implemented. The results of the experiment, which consisted of seventeen university student subjects and fifteen elder subjects, showed differences between younger and elder subjects on emotion identification, body parts paid attention to, and impressions of motion speed and magnitude for these affective body motions of the robot. Moreover, the results suggested correlations between the accuracy of emotion identification and cognitive bias to the robot's specific body motion parts. Based on these results, the paper discusses about some implications in human-robot interaction research. © Springer Science & Business Media BV 2010.

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