본 연구는 인공지능 기술과 메신저용 챗봇의 인터페이스 융합을 통해 의사소통능력 개발을 위한 외국어 학습의 효과를 검증하는 목적으로 수행되었다. 이를 위해 첫째, 자체 학습이 가능한 로봇 기반과 인공지능 기술과 디지털 융합기술을 적용한 학습시스템을 설계하여 학습 성취도에 미치는 영향을 조사하였다. 둘째, 휴머노이드 로봇의 인간과의 상호작용 구현 능력을 검증하고 인터페이스 프로그램을 자기학습의 알고리즘으로 의사소통 능력 학습에 적용하여 그 효과를 검증하고자 하였다. 셋째, 아이팟, 아이폰, 아이패드, 매킨토시PC, iTV 등 모든 기기에 아이튠즈와 앱스토어를 탑재하고 있는 클라우드 앱과 페이스북 메신저 챗봇의 다양한 콘텐츠를 학습시스템에 활용하였다. 연구 대상은 충남 천안시 대학에서 재학 중인 학생 120명이었다. 실험집단과 통제집단의 사전 시험, 사후 시험, 학습 활동에 대한 평가를 통한 성취도를 분석하고 또한 실험집단의 설문 조사를 통하여 통계분석을 하였다. 연구결과는 다음과 같다. 첫째, 로봇은 학생과 같은 콘텐츠 사용자, 교사 같은 콘텐츠 제작자, 실제 자료 콘텐츠 간의 상호작용을 강화할 수 있어 외국어교육에 있어 매우 효과적이다. 둘째, 교육용 로봇 기반 학습시스템은 학습자에게 자기 주도학습의 동기를 부여하였다. 셋째, 사전 테스트와 사후 테스트 결과는 제안된 학습시스템이 로봇과 인공지능 앱을 기반으로 한 학습시스템이 학생들의 성취도 향상에 효과적이었다.

Recently, education game contents with advanced mobile and Web technology have been widely researched. However, considering of interaction involved for children, it is necessary user friendly interfaces and interesting interactions. In addition, it is important to design to encourage the user’s learning motivation as a way to the effect of educational game contents. Therefore, in this study, we designed and implemented the educational game contents system using inter-working between KINECT camera, PC, and android platform based humanoid robot. The designed system consisted of KINECT system for capturing hand gestures, game contents system for playing games, and android humanoid robot system for interacting with users. This system can lead to interests and willingness of users through handy interaction such as hand gestures and interesting quiz game contents. To improve effectiveness and userability, we plant to advance designed educational game contents system that can be operated on a smart TV system including a built-in camera as a further study.

최근 국내에서는 로봇에 대한 일반인들의 관심이 높아지고 있다. 로봇은 사람과 유사한 모습과 기능을 가진 기계, 또는 무엇인가 스스로 작업하는 능력을 가진 기계를 말한다. 본 논문에서는 지능형 휴머노이드 로봇을 이용한 보드게임을 설계 개발 하고자 한다. 제안하는 주사위 게임은 휴머노이드 로봇에서 주사위를 던지는 모션을 마이컴 임베디드 시스템에서 랜덤한 동작으로 제어하는 프로그램을 작성 하여 실행 시켜 보았다. 주사위 게임의 모션은 왼쪽던지기, 오른쪽던지기, 정면던지기 동작으로 구성한다. 이를 통하여 로봇 게임을 통한 유아 및 노인들의 인지 훈련에 도움을 주고자 한다.

Robot ALICE@ERICA is a service robot developed to receive donations and to provide information services. ALICE@ERICA stands for Artificial Learning Intelligence robot for Culture and Entertainment at ERICA. In order to achieve the specific purpose of receiving donations, proper appearance design, appropriate movement and good communication skills are required in terms of HRI. In this paper, we introduce three strategies for developing robots to receive donations effectively. The first is to design a robot that makes people feel intimacy, the second is to approach only one of several people as a donor, and finally the donor communicates with video contents and voice recognition. A survey was conducted on the person who showed the reaction after the robot donated money in public places. Based on the survey results, it is proved that the method presented in this study effectively contributed to fund raising. If robots can perform actions that require high level of HRI, such as donation, robots can contribute more to human society. We hope that this study contributes to the improvement of human happiness.

정보통신기술의 발달과 함께 학습자에게 재미와 흥미를 통한 즐거운 교육환경을 제공하고자 다양한 방법이 시도 되고 있다. 에듀테인먼트와 게임기반학습 등에서 게임이나 로봇과 같은 기술을 교육에 활용하는 것은 좋은 예이다. 본 연구에서는 휴머노이드 로봇의 율동 생성을 위한 사용자 데이터 수집과 분석을 통한 지능형 율동 교육 시스템을 제안한다. 이를 위하여 사용자는 음악을 선택하고, 선택한 음악에 따라 율동 정보를 입력한다. 이러한 사용자의 로봇 활용 데이터는 분석을 통하여 지능화된 서비스를 위한 패턴의 역할을 한다. 분석 결과는 빈도에 기반을 두며, 과거 정보가 부족한 경우 FFT 유사도 비교 방법을 적용하였다. 제안하는 방법은 유치원 아이들을 대상으로 하는 실험을 통하여 유효함을 확인하였다.

In this paper, we describe a case of using robot technology in child studies to examine children’s judgement and reasoning of the life phenomenon on boundary objects. In order to control the effects of the appearance of the robot, which children observe or interact directly with, on the children's judgement and reasoning of the life phenomenon, we developed a robot similar to human. Unit experimental scenarios representing biological and psychological properties were implemented based on control of robot's motion, speech, and facial expressions. Experimenters could combine these multiple unit scenarios in a cascade to implement various scenarios of the human-robot interaction. Considering that the experimenters are researchers of child studies, there was a need to develop a remote operation console that can be easily used by non-experts in the robot field. Using the developed robot platform, researchers of child studies could implement various scenarios by manipulating the biological and psychological properties of the robot based on their research hypothesis. As a result, we could clearly see the effects of robot's properties on children’s understanding about boundary object like robots.

This paper proposes combination of a cognitive agent architecture named Soar (State, operator, and result) and ROS (Robot Operating System), which can be a basic framework for a robot agent to interact and cope with its environment more intelligently and appropriately. The proposed Soar-ROS human-robot interaction (HRI) agent understands a set of human’s commands by voice recognition and chooses to properly react to the command according to the symbol detected by image recognition, implemented on a humanoid robot. The robotic agent is allowed to refuse to follow an inappropriate command like “go” after it has seen the symbol ‘X’ which represents that an abnormal or immoral situation has occurred. This simple but meaningful HRI task is successfully experimented on the proposed Soar-ROS platform with a small humanoid robot, which implies that extending the present hybrid platform to artificial moral agent is possible.

The main goal of e-learning systems is just-in-time knowledge acquisition. Rule-based elearning systems, however, suffer from the mesa effect and the cold start problem, which both result in low user acceptance. E-learning systems suffer a further drawback in rendering the implementation of a natural interface in humanoids difficult. To address these concerns, even exceptional questions of the learner must be answerable. This paper aims to propose a method that can understand the learner’s verbal cues and then intelligently explore additional domains of knowledge based on crowd data sources such as Wikipedia and social media, ultimately allowing for better answers in real-time. A prototype system was implemented using the NAO platform.

In this study, we have developed the humanoid joint modules which provide a variety of service while living with people in the future home life. The most important requirement is ensuring the safety for humans of the robot system for collaboration with people and providing physical service in dynamic changing environment. Therefore we should construct the mechanism and control system that each joint of the robot should response sensitively and rapidly to fulfill that. In this study, we have analyzed the characteristic of the joint which based on the target constituting the humanoid motion, developed the optimal actuator system which can be controlled based on each joint characteristic, and developed the control system which can control an multi-joint system at a high speed. In particular, in the design of the joint, we have defined back-drivability at the safety perspective and developed an actuator unit to maximize. Therefore we establish a foundation element technology for future commercialization of intelligent service robots.

This study aims to look into students' and teachers' recognition about learning with a humanoid robot and seek for a policy implication for the direction of education using humanoid robot. To achieve this goal, a survey with elementary school students and teachers was used as the method of analysis. The main results are as follows: There was a difference in the recognition of the teachers and the students regarding the most effective subject through the use of humanoid robot. While the students consider Physical Education as the major subject, the teachers consider Science as the one. The students recognize that the use of humanoid is most effective in helping their learning while the teachers recognize that it is most effective in helping their teaching. As an expected positive effect, both of them choose an increase in interest in learning as the main effect of the use of humanoid robot, but the students, unlike the teachers, consider the improvement of their academic achievement as its main effect as well. These results show differences in the recognition of the use of humanoid between the teachers and the students, and in addition, confirm the difference between them depending on their background.

Humanoid robot is the most intimate robot platform suitable for human interaction and services. Biped walking is its basic locomotion method, which is performed with combination of joint actuator’s rotations in the lower extremity. The present work employs humanoid robot simulator and numerical optimization method to generate optimal joint trajectories for biped walking. The simulator is developed with Matlab based on the robot structure constructed with the Denavit-Hartenberg (DH) convention. Particle swarm optimization method minimizes the cost function for biped walking associated with performance index such as altitude trajectory of clearance foot and stability index concerning zero moment point (ZMP) trajectory. In this paper, instead of checking whether ZMP’s position is inside the stable region or not, reference ZMP trajectory is approximately configured with feature points by which piece-wise linear trajectory can be drawn, and difference of reference ZMP and actual one at each sampling time is added to the cost function. The optimized joint trajectories realize three phases of stable gait including initial, periodic, and final steps. For validation of the proposed approach, a small-sized humanoid robot named DARwIn-OP is commanded to walk with the optimized joint trajectories, and the walking result is successful.

A humanoid robot hand with one thumb and two fingers has been developed. Each finger has the specially designed compact joints, called "MEC Joint", which convert the rotation of a motor to the swing motion of a pendulum. The robot hand with the MEC Joints is compact and relatively light but strong enough to grasp objects in the same manner as human being does in daily activities. In this paper the kinematic model and the torque characteristics of the MEC Joint are presented and compared with the results of the dynamic simulation and the dynamometer test. The dynamic behavior of the thumb and two fingers with MEC Joints are also presented by computer simulation.

People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

This paper describes a network framework that support network based humanoid. The framework utilizes middleware such as CORBA (ACE/TAO) that provides PnP capability for network based humanoid. The network framework transfers data gathered from a network based humanoid to a processing group that is distributed on a network. The data types are video stream, audio stream and control data. Also, the network framework transfers service data produced by the processing group to the network based humanoid. By using this network framework, the network based humanoid can provide high quality of intelligent services to user.

Nowadays, research on human-robot interaction has been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report a speaker localization system with six microphones for a humanoid robot called MAHRU from KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. The proposed method, using the TDOA-based feature matrix and its algorithm based on MSAE, effortlessly localizes a sound source without any requirement for calculating approximate nonlinear equations. To verify the solid performance of our speaker localization system for a humanoid robot, we present various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

In this paper, control software architecture is designed to enable a heterogeneous multiple humanoid robot demonstration executing tasks cooperating with each other. In the heterogeneous humanoid robot team, one large humanoid robot and two small humanoid robots are included. For the efficient and reliable information sharing between many software components for humanoid control, sensing and planning, CORBA based software framework is applied. The humanoid tasks are given in terms of finite state diagram based human-robot interface, which is interpreted into the XML based languages defining the details of the humanoid mission. A state transition is triggered based on the event which is described in terms of conditions on the sensor measurements such as robot locations and the external vision system. In the demonstration of the heterogeneous humanoid team, the task of multiple humanoid cleaning the table is given to the humanoid robots and successfully executed based on the given state diagram.

Abstract Many researchers are studying on humanoid robots in all over the world. However the humanoid robots are still limited in doing works like picking up objects on the ground or moving rapidly. In this study, a humanoid robot based on the wheel-driving was developed. It can operate with a human working area keeping the stability. Also, the developed robot can take up the object on the floor since it has knee(1DoF) and waist(3DoF), and do service quickly and steadily. The hardware and software structure and algorithms of the developed robot, SEROPI are introduced in this paper.

We present the synergy effect of humanoid robot walking down on a slope and support vector machines in this paper. The biped robot architecture is highly suitable for the working in the human environment due to its advantages in obstacle avoidance and ability to be employed as human substitutes. But the complex dynamics in the robot and ground makes robot control difficult. The trajectory of the zero moment point (ZMP) in a biped walking robot is an important criterion used for the balance of the walking robots. The ZMP trajectory as dynamic stability of motion will be handled by support vector machines (SVM). Three kinds of kernels are also employed, and each result from these kernels is compared to one another.

During the communication and interaction with a human using motions or gestures, a humanoid robot needs not only to look like a human but also to behave like a human to make sure the meanings of the motions or gestures. Among various human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle which is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, Response Surface Method (RSM). Then a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate humanlike arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of its hand. The example motion was performed using the KIST humanoid robot, MAHRU.