In many cases of human-human communication, humans interact with others while assuming their emotions and impressions based on not only verbal information but also non-verbal information. Similarly, during the human-robot interaction, predicting the impressions that a person has of the robot is important for the robot to change the behavior and realize good interaction. In this work, we try to use gaze and gesture annotation data in human-robot interaction from AICO-Corpus and show LSTM approach has the potential for the prediction about impressions of interaction with a robot. We also analyzed the types of nonverbal information that influence the impressions towards the robot in English and Japanese respectively.

Eating with others enriches our lives and has many positive effects. However, numerous people are forced to eat alone in the current COVID-19 pandemic situation. We think that robots that exist with bodies and can be interacted with in real time can be good mealtime partners. In this study, we developed a meal partner robot platform called Mamoru’21, which can share eating behavior. We experimented to evaluate Mamoru’21. The results showed that Mamoru’21 could make eating more enjoyable than a conventional communication robot. We also investigated the preferable appearance of a meal partner robot and confirmed that Mamoru’21 met the requirements.

Speech is an intuitive way to interact with social robots: spoken language dialogues can help users to express their intents in a natural and flexible manner. In recent years, there has been remarkable progress in artificial intelligence related to spoken dialogue technology, including speech recognition and natural language processing. In this paper, we present the integration of the open source speech recognition, natural language processing, and dialogue management components into a robot software platform, and also report on a preliminary experiment of the integrated system using real users. Gesturing of the robot, which is also important in human-robot interaction, is combined with the spoken content of the robot utterance and included in the dialogue management component. As the dialogue domain we chose mealtime discussions on food and recipes, since spoken communication with a companion robot in such scenarios is considered natural and useful.

Due to the recent lifestyle changes, instances of people eating alone have been increasing. We think robots can be good meal partners without having to risk disease transmission. Furthermore, people are able to eat with robots without worrying about mealtimes. In this study, we determine who are more likely to accept robots as eating partners and compare eating with a single robot to eating with multiple robots. The results revealed that people who have vast experience in interacting with robots and those who have relatively few opportunities to eat alone felt better about eating with robots, whereas those who have numerous opportunities to eat alone enjoyed eating with multiple robots.

Eating with others enhances our dining experience, improves socialization, and has some health benefits. Although many people do not want to eat alone, there is an increase in the number of people who eat alone in Japan due to difficulty in matching mealtimes and places with others.In this paper, we develop a mixed reality (MR) system for coeating with a robot. In this system, a robot and a MR headset are connected enabling users to observe a robot putting food image into its mouth, as if eating. We conducted an experiment to evaluate the developed system with users that are at least 13 years old. Experimental results show that the users enjoyed their meal and felt more delicious when the robot ate with them than when the robot only talked without eating. Furthermore, they eat more when a robot eats, suggesting that a robot could influence people's eating behavior.

Importance of the real-time data analysis even in the HPC area rapidly increase in the recent data intensive science. Once the real-time data analysis becomes available, the interactive feedback to the data source will be happening to make thing improve. In order to realize such an environment for scientific simulation, the framework for interactive supercomputing has been developed so far. However, user interaction of that framework was limited to a certain closed environment. In this paper, web-based ubiquitous interface that allows simultaneous sharing of on-going simulation among multiple users is proposed.

Tendon-driven musculoskeletal humanoids have many benefits in terms of the flexible spine, multiple degrees of freedom, and variable stiffness. At the same time, because of its body complexity, there are problems in controllability. First, due to the large difference between the actual robot and its geometric model, it cannot move as intended and large internal muscle tension may emerge. Second, movements which do not appear as changes in muscle lengths may emerge, because of the muscle route changes caused by softness of body tissue. To solve these problems, we construct two models: ideal joint-muscle model and muscle-route change model, using a neural network. We initialize these models by a man-made geometric model and update them online using the sensor information of the actual robot. We validate that the tendon-driven musculoskeletal humanoid Kengoro is able to obtain a correct self-body image through several experiments.

Human hands can not only grasp objects of various shape and size and manipulate them in hands but also exert such a large gripping force that they can support the body in the situations such as dangling a bar and climbing a ladder. On the other hand, it is difficult for most robot hands to manage both. Therefore in this paper we developed the hand which can grasp various objects and exert large gripping force. To develop such hand, we focused on the thumb CM joint with wide range of motion and the MP joints of four fingers with the DOF of abduction and adduction. Based on the hand with large gripping force and flexibility using machined spring, we applied above mentioned joint mechanism to the hand. The thumb CM joint has wide range of motion because of the combination of three machined springs and MP joints of four fingers have variable rigidity mechanism instead of driving each joint independently in order to move joint in limited space and by limited actuators. Using the developed hand, we achieved the grasping of various objects, supporting a large load and several motions with an arm.