• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1776-1780
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• 2004

In this paper, we propose the new emotion model and the robot behavior decision model based on proposed emotion model. As like in human, emotions are hierarchicalized in four levels (momentary emotions, mood, attitude, and personality) and are determined from the robot behavior and human responses. They are combined with motivation (which is determined from the external stimuli) to determine the robot behavior.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.79-86
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• 2012

The purpose of this study is to improve creative personality of elementary school students with integrated subject study program based STEAM education. On this study, I analyzed integrated subject study and STEAM, developed contents using educational robot applied integrated subject study program model. And analyzed result after applied to elementary school students. After dividing two groups-experimental group, comparison group-for this study, tested t-test. Finally I got a meaningful result statistically. There was an postive effect to improving elementary school students' creative personality by appling STEAM-based integrated subject study program.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.7-12
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• 2008

In human and robot interaction, the role of emotion becomes more important Therefore, robots need the emotion expression mechanism similar to human. In this paper, we suggest a new emotion expression system based on the psychological studies and it consists of five affective elements, i.e., the emotion, the mood, the personality, the tendency, and the machine rhythm. Each element has somewhat peculiar influence on the emotion expression pattern change according to their characteristics. As a result, although robots were exposed to the same external stimuli, each robot can show a different emotion expression pattern. The proposed system may contribute to make a rather natural and human-friendly human-robot interaction and to promote more intimate relationships between people and robots.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.95-98
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• 2007

본 논문은 한국생산기술연구원에서 개발된 안드로이드 로봇(EveR Series) 플랫폼에 적용된 감성 시스템에 관한 내용을 제시한다. EveR 플랫폼은 얼굴 표정, 제스처, 음성합성을 수행 할 수 있는 플랫폼으로써 감성 시스템을 적용하여 인간 친화적인 상호작용을 원활하게 한다. 감성 시스템은 로봇에 동기를 부여하는 동기 모듈(Motivation Module), 다양한 감정들을 가지고 있는 감정 모듈(Emotion Module), 감정들, 제스처, 음성에 영향을 미치는 성격 모듈(Personality Module), 입력 받은 자극들과 상황들에 가중치를 결정하는 기억 모듈(Memory Module)로 구성되어 있다. 감성 시스템은 입력으로 음성, 텍스트, 비전, 촉각 및 상황 정보가 들어오고 감정의 선택과 가중치, 행동, 제스처를 출력하여 인간과의 대화에 있어서 자연스러움을 유도한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.155-157
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• 2011

본 논문에서는 초등학생의 창의 인성 발달을 위한 교육용 로봇 활용방안을 제안한다. 미래사회는 '집어넣는 교육'이 아니라 '끄집어 내는 교육'이 중심이 되어야 하며, 그 핵심에 '창의성'과 '인성'이 존재한다. 그래서 창의 인성을 기르기 위해 교육용 로봇을 활용하여 지도하는 방법을 모색하고자 한다. 구체물을 사용하여 조작하는 것은 초등학생의 인지발달단계와도 맞물려 있으므로 흥미있게 주제에 접근하는 좋은 방법이 될 것이다. 하지만 이에 대한 관련 연구가 부족하여 앞으로 관련 교육과정 개발 및 교재 연구가 절실히 필요하다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.217-224
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• 2019

The intelligent robot industry is a complex which encompasses all fields of science and technology, and its marketability and industrial impact are remarkable. Major countries in the world have been strengthening their policies to foster the intelligent robot industry, but discussions on liability issues and legal actions that are accompanied by the related big or small accidents are still insufficient. In this study, therefore, the patent law by artificial intelligence robots and the legislation for relevant legal actions at the criminal law level are presented. Patent law legislation by artificial intelligence robots should comply with the followings. First, the electronic human being other than humans ought to be given legal personality, which is the subject of patent infringement. Even if artificial intelligence has legal personality, legal responsibility will be varied depending on the judgment of whether the accident has occurred due to the malfunction of the artificial intelligence itself or due to the human intervention with malicious intention. Second, artificial intelligence as a subject of actors and responsibility should be distinguished strictly; in other words, the injunction is the responsibility of the intelligent robot itself, but the financial repayment is the responsibility of the owner. In the criminal law legislation, regulations for legal punishment of intelligent robot manufacturing companies and manufacturers should be prepared promptly in case of legal violation, by amending the scope of application of Article 47 (Penal Provisions) of the Intelligent Robots Development and Distribution Promotion Act. In this way, joint penal provisions, which can clearly distinguish the responsibilities of the related parties, should be established to contribute to the development of the fourth industrial revolution.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.210-217
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• 2009

This paper introduces a design of multi-dimensional complex emotional model for various complex emotional expression. It is a novel approach to design an emotional model by comparison with conventional emotional model which used a three-dimensional emotional space with some problems; the discontinuity of emotions, the simple emotional expression, and the necessity of re-designing the emotional model for each robot. To solve these problems, we have designed an emotional model. It uses a multi-dimensional emotional space for the continuity of emotion. A linear model design is used for reusability of the emotional model. It has the personality for various emotional results although it gets same inputs. To demonstrate the effectiveness of our model, we have tested with a human friendly robot.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.295-300
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• 2017

The study evaluates exploration of social robot's role which can emotionally communicate with human as an alternative to heal psychological isolation for single-person households. At first, I conduct a study on literatured to understand the definition and characteristics of social robot then analyze the current situation and future prospects. Based on this, I organized the requirements of social robot in aspect of user experience through in-depth interview of twenties single-person households living in the metropolitan area who could be potential customers. As a result every subject require social robot specialized to them through accumulated interaction. On the other hand, degree of attachment with social robot is different from subjects. Hear by I realize every subject require social robot to different and various functions according to their lifestyle and personality. Therefore I could draw conclusions and implications from this study that technical development in aspect of personalized user experience is necessary for social robot to settle in to human's life in the future.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.276-278
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• 2006

인간의 감성은 의사결정과 의사소통에 있어서 중요한 역할을 한다. 감성의 생성과 표현은 성격에 의해 영향을 받는다. 이와 같은 감성과 성격을 반영한 로봇은 보다 자연스러운 표현과 효율적인 의사소통을 할 수 있다. 본 논문은 상태방정식과 출력 방정식으로 구성된 성격을 고려한 감성 시스템을 제안한다. 상태방정식은 외부자극으로부터 감정을 생성하고, 출력방정식은 성격과 환경을 반영하여 감정의 표현 강도를 결정한다. 감성시스템에서 성격은 입력된 자극을 통한 성격 5요인이론에 언급된 5요인의 값을 변화시킴으로써 학습된다. 또한 고전적 학습방법으로 자극을 학습하여 감정의 형성에 영향을 주는 자극의 수를 증가시킨다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.