Takashi Minato

Development of an android robot for studying human-robot interaction

One of the difficulties of using Artificial Neural Networks (ANNs) to estimate atmospheric temperature is the large number of potential input variables available. In this study, four different feature extraction methods were used to reduce the input vector to train four networks to estimate temperature at different atmospheric levels. The four techniques used were: genetic algorithms (GA), coefficient of determination (CoD), mutual information (MI) and simple neural analysis (SNA). The results demonstrate that of the four methods used for this data set, mutual information and simple neural analysis can generate networks that have a smaller input parameter set, while still maintaining a high degree of accuracy.

Generating natural motion in an android by mapping human motion

One of the main aims of humanoid robotics is to develop robots that are capable of interacting naturally with people. However, to understand the essence of human interaction, it is crucial to investigate the contribution of behavior and appearance. Our groups research explores these relationships by developing androids that closely resemble human beings in both aspects. If humanlike appearance causes us to evaluate an androids behavior from a human standard, we are more likely to be cognizant of deviations from human norms. Therefore, the androids motions must closely match human performance to avoid looking strange, including such autonomic responses as the shoulder movements involved in breathing. This paper proposes a method to implement motions that look human by mapping their three-dimensional appearance from a human performer to the android and then evaluating the verisimilitude of the visible motions using a motion capture system. This approach has several advantages over current research, which has focused on copying a persons moving joint angles to a robot: (1) in an android robot with many degrees of freedom and kinematics that differs from that of a human being, it is difficult to calculate which joint angles would make the robots posture appear similar to the human performer; and (2) the motion that we perceive is at the robots surface, not necessarily at its joints, which are often hidden from view.

CB2: A child robot with biomimetic body for cognitive developmental robotics

This paper presents a new research platform, CB2, a child robot with biomimetic body for cognitive developmental robotics developed by the Socially-Synergistic Intelligence (Hereafter, Socio-SI) group of JST ERATO Asada Project. The Socio-SI group has focused on the design principles of communicative and intelligent machines and human social development through building a humanoid robot that has physical and perceptual structures close to us, that enables safe and close interactions with humans. For this purpose, CB2 was designed, especially in order to establish and maintain a long-term social interaction between human and robot. The most significant features of CB2 are a whole-body soft skin (silicon surface with many tactile sensors underneath) and flexible joints (51 pneumatic actuators). The fundamental capabilities and the preliminary experiments are shown, and the future work is discussed.

Physical Human-Robot Interaction: Mutual Learning and Adaptation

Close physical interaction between robots and humans is a particularly challenging aspect of robot development. For successful interaction and cooperation, the robot must have the ability to adapt its behavior to the human counterpart. Based on our earlier work, we present and evaluate a computationally efficient machine learning algorithm that is well suited for such close-contact interaction scenarios. We show that this algorithm helps to improve the quality of the interaction between a robot and a human caregiver. To this end, we present two human-in-the-loop learning scenarios that are inspired by human parenting behavior, namely, an assisted standing-up task and an assisted walking task.

Does Gaze Reveal the Human Likeness of an Android

The development of androids that closely resemble human beings enables as to investigate many phenomena related to human interaction that could not otherwise be investigated with mechanical-looking robots. This is because more humanlike devices are in a better position to elicit the kinds of responses that people direct toward each other. In particular, we cannot ignore the role of appearance in giving us a subjective impression of human presence or intelligence. However, this impression is influenced by behavior and the complex relationship between appearance and behavior. We propose a hypothesis about how appearance and behavior are related and map out a plan for android research to investigate the hypothesis. We then examine a study that evaluates the behavior of androids according to the patterns of gaze fixations they elicit. Studies such as these, which integrate the development of androids with the investigation of human behavior, constitute a new research area that fuses engineering and science

Evaluating the human likeness of an android by comparing gaze behaviors elicited by the android and a person

Our research goal is to discover the principles underlying natural communication among individuals and to establish a methodology for the development of expressive humanoid robots. For this purpose we have developed androids that closely resemble human beings. The androids enable us to investigate a number of phenomena related to human interaction that could not otherwise be investigated with mechanical-looking robots. This is because more human-like devices are in a better position to elicit the kinds of responses that people direct toward each other. Moreover, we cannot ignore the role of appearance in giving us a subjective impression of human presence or intelligence. However, this impression is influenced by behavior and the complex relationship between appearance and behavior. This paper proposes a hypothesis about how appearance and behavior are related, and maps out a plan for android research to investigate this hypothesis. We then examine a study that evaluates the human likeness of androids according to the gaze behavior they elicit. Studies such as these, which integrate the development of androids with the investigation of human behavior, constitute a new research area that fuses engineering and science.

Development of an android system integrated with sensor networks

In order to develop a robot that has a human-like presence, the robot must be given a very human-like appearance and behavior, and a sense of perception that enables it to communicate with humans. We have developed an android robot called ldquoRepliee Q2rdquo that closely resembles a human being; however, the sensors mounted on its body are not sufficient to allow human-like communication due to factors such as sensing range and spatial resolution. To overcome this problem, we endowed the environment surrounding the android with perceptive capabilities by embedding a variety of sensors into it. This sensor network provides the android with human-like perception by constantly and extensively monitoring human activities in a less obvious manner. This paper reports on an android system that is integrated with a sensor network system embedded in the environment. A human-android interaction experiment shows that the integrated system provides relatively human-like interaction.

Visual attention by saliency leads cross-modal body representation

One of the most fundamental issues for physical agents (humans, primates, and robots) in performing various kinds of tasks is body representation. Especially during tool-use by monkeys, neurophysiological evidence shows that the representation can be dynamically reconstructed by spatio-temporal integration of different sensor modalities so that it can be adaptive to environmental changes. However, to construct such a representation, an issue to be resolved is how to associate which information among various sensory data. This paper presents a method that constructs cross-modal body representation from vision, touch, and proprioception. Tactile sensation, when the robot touches something, triggers the construction process of the visual receptive field for body parts that can be found by visual attention based on a saliency map and consequently regarded as the end effector. Simultaneously, proprioceptive information is associated with this visual receptive field to achieve the cross-modal body representation. The proposed model is applied to a real robot and results comparable to the activities of parietal neurons observed in monkeys are shown.

Environmental change adaptation for mobile robot navigation

Most of existing robot learning methods have considered the environment where their robots work unchanged, therefore, the robots have to learn from scratch if they encounter new environments. This paper proposes a method which adapts robots to environmental changes by efficiently transferring a learned policy in the previous environments into a new one and effectively modifying it to cope with these changes. The resultant policy (a part of state transition map) does not seem optimal in each individual environment, but may absorb the differences between multiple environments. We apply the method to a mobile robot navigation problem of which task is to reach the target avoiding obstacles based on uninterpreted sonar and visual information. Experimental results show the validity of the method and discussion is given.

Personality distortion in communication through teleoperated robots

Recent research has focused on such physical communication media as teleoperated robots, which provide a feeling of being with people in remote places. Recent invented media resemble cute animals or imaginary creatures that quickly attract attention. However, such appearances could distort tele-communications because they are different from human beings. This paper studies the effect on the speakers personality that is transmitted through physical media by regarding appearances as a function that transmits the speakers information. Although communication medias capability to transmit information reportedly influences conversations in many aspects, the effect of appearances remains unclear. To reveal the effect of appearance, we compared three appearances of communication media: stuffed-bear teleoperated robot, human-like teleoperated robot, and video chat. Our results show that communication media whose appearance greatly differs from that of the speaker distorts the personality perceived by interlocutors. This paper suggests that the design of the appearance of physical communication media needs to be carefully selected.