• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.196-204
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• 2007

In this paper, we are looking for requirements of software, hardware and application for use in network-based robots and also directions in building standardization and research activities by reviewing technical status of the robot industries developing robots. The questions are including awareness of RUPI(Robot Unifies Platform Initiative) activities, target market and applications, hardware specifications, software development technologies, and HRI(Human Robot Interaction). The RUPI committee creates standard and drives implementation software for network-based robots through industrial requirements as like of the results. Many robots have been developed and launched services based on RUPI 1.0 standards. Based on this achievement we are expanding RUPI standard to include thin and thick client robots. The results also show that which one is important and urgent technology in the sense of industrial robotic business.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.75-81
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• 2013

This research would investigate deeply the operation of an omni-directional mobile robot that is able to move with high acceleration. For the high acceleration performance, the vehicle utilizes the structure of Active Split Offset Casters (ASOCs). This paper is mainly focused on inverse kinematics of the structure, hardware design to secure durability and preserve the wheels' contact to the ground during high acceleration, and localization for the real time position control.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.13-16
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• 2017

제스처 인식은 HCI(Human-Computer Interaction) 및 HRI(Human-Robot Interaction) 분야에서 활발히 연구되고 있는 기술이며, 제스처 데이터의 특징을 추출해내고 그에 따른 분류를 통하여 사용자의 제스처를 정확히 판별하는 것이 중요한 과제로 자리 잡았다. 본 논문에서는 EMG(Electromyography) 센서로 측정한 사용자의 손 제스처 데이터를 분석하는 방안에 대하여 서술한다. 수집된 데이터의 노이즈를 제거하고 데이터의 특징을 극대화시키기 위하여 연속적인 데이터로 변환하는 전처리 과정을 거쳐 이를 머신 러닝 알고리즘을 사용하여 분류하였다. 이 때, 기존의 raw 데이터와 전처리 과정을 거친 데이터의 성능을 decision-tree 알고리즘을 통하여 비교하였다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.425-438
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• 2017

기술혁신으로 인간과 로봇의 문자 음성형 대화가 가능한 사회가 도래하고 있다. 인간이 로봇에 정서적 반응을 나타낸다는 선행연구 결과는 로봇이 도구적 장치에서 벗어나 친밀감을 맺을 수 있는 대상이 될 수 있음을 시사하였다. 이러한 흐름을 반영하여 본 연구는 심리학에서 연구되어온 애착이론이 인간과 로봇의 관계에도 적용되는지를 분석하였다. 먼저 인간이 기계를 의인화한다는 기존의 인간-로봇 상호작용 연구를 검토하고, 인간이 타인과 관계를 맺는 방식에 대한 애착이론을 고찰하였다. 또한 인간이 기계와 정서적 관계를 맺을 수 있으나 타인과는 다른 방식으로 형성함을 선행연구를 통해 살펴보았다. 그런 다음, 애착이론을 토대로 인간과 로봇의 가능한 사회적 관계양상을 그려보았다. 마지막으로 로봇과의 소통이 일상적으로 이루어질 가까운 미래사회에 인간과 로봇의 건전한 관계형성을 위한 후속연구 주제들을 제안하였다. 본 연구는 최신 기술흐름을 반영하여 대화가 가능한 로봇을 대상으로 연구했다는 점에서 의의가 있다. 또한 인간이 타인과 관계를 맺는 방식을 바탕으로 인간이 로봇의 관계양상을 심층적으로 모색해 보았다는 점에서 함의를 지닌다.

• Journal of the Korean housing association
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• v.10 no.3
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• pp.221-229
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• 1999

The purpose of this study is to investigate the housing affordability of multi-family dwelling in Seoul and to systemize the housing expenditure patterns and housing affordability according to household and housing characteristics. Housing expenditures are basically composed of the payments of four major items. including utilities. home alteration and interior furnishing. home mortgage debt. and monthly rent. Housing affordability index as operationally defined in this study is Housing Expenditure-to-Income Ratio (HEIR). The ratios were computed for each of the four housing expenditure items. Data for 465 multi-family dwellers were gathered from the structured questionnaire. The results showed the differences between household and housing characteristics on housing expenditure levels and HEIR. In addition. this differences had influence on future housing choice behavior. The analysis on the variables of housing choice behavior showed the result that user cost considering capital gains were less important. comparing those of early 1990's.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.108.1-108.1
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• 2012

Previously we introduced ray-tracing based 3D optical earth system model for specular and scattering properties of all components of the system (i.e. clear-sky atmosphere, land surfaces and an ocean surface). In this study, we enhanced 3-dimensional atmospheric structure with vertical atmospheric profiles for multiple layer and cloud layers using Lambertian and Mie theory. Then the phase dependent disk averaged spectra are calculated. The main results, simulated phase dependent disk averaged spectra and light curves, are compared with the 7 bands(300~1000nm) light curves data of the Earth obtained from High Resolution Instrument(HRI) in Deep Impact spacecraft during Earth flyby in 2008. We note that the results are comparable with the observation.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.102-106
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• 2006

지능형 서비스 로봇은 인공지능 및 센서인터페이스 등의 다양한 기능과 IT기술의 접목으로 우리의 생활을 윤택하게 해줄 수 있는 인간 지향적인 성격으로 발전하고 있다. 또한 많은 분야에서 새로운 서비스 개발을 통해서 좀더 인간의 생활에 가까이 접근되어 지고 있다. 한편 국내 초등학교에서 초등교사는 학생 수의 과다로 능동적이기 보다는 수동적인 수업을 하고 있어서 학습 효율성이나 능률성이 떨어지고 있다. 이에 본 연구에서는 발전하고 있는 서비스 로봇 기술로 능동적인 수업형태와 자율적이고 창의적인 학습 및 교육서비스를 제공할 수 있는 교사도우미 로봇을 개발하였다. 본 연구에서 개발된 로봇은 기존의 지능형 서비스 로봇과 ICT(Information & Communication Technology) 교육을 접목할 수 있는 로봇의 제반 환경의 구성과 더불어 교육 현장에 알맞도록 HRI 및 시나리오를 기반으로 개발되었고, 로봇의 주요기능은 교사지원, 학습보조, 수업지원 등으로 사전 설문조사를 통하여 필요성이 높은 기능을 중심으로 설정되었다. 개발된 초등학교 지원 로봇은 2006년 10월부터 대전지능로봇산업화센터에서 초등학교 학생을 대상으로 시범수업을 준비하고 있고, 2007년도 중반에는 초등학교에서 시범사업을 추진할 예정이다.

• FLOWER RESEARCH JOURNAL
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• v.16 no.1
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• pp.36-43
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• 2008

This purpose of this study was to examine the effect of planting density, growing medium and strength of a nutrient solution (National Horticultural Research Institute's nutrient solution: HRI's) on the growth and development of Oriental hybrid lily 'Le Reve' in a box cultivation. The planting density with 14, 18 and 22 bulbs had sprouting one day earlier than other treatments. Planting density of 22 bulbs flowered first, while six bulbs flowered the last, indicating that higher planting densities led earlier flowering. The increasing planting density increased stem length of cut flowers. On the other hand, cut flower quality was improved when the planting density was lower. The incidence of physiological disorders such as blasting was more frequent in planting density of 22, 18, and 14, indicating that higher planting densities caused higher incidences of physiological disorders. All planting densities except 22 bulbs displayed superior results in width, weight, number, and scale weight of the bulbs. Greater planting densities led to inferior bulb enlargement and an increased decomposition rate. pH decreased in all treatments after the bulb enlargement and decreased more as the planting density increased. Contents of P, K, Ca, and Mg increased, while contents of K and Ca decreased, as the planting density increased. The rice hull+coir (1:1, v/v) treatment was better than others, but did not show that much of a difference. Moreover, in bulbs enlargement after cut flower harvest, lily medium and perlite+peat moss treatments showed superior results, and decomposition rate was the greatest in the rice hull+coir (1:1, v/v) treatment. In the HRI's solution strength treatment from the period of flower bud emergence to flower harvest, higher solution strengths gave better cut flower quality in terns of length, weight, and number of flowers. The non-treated control and one third strength of a HRI's solution hastened flowering, indicating that lower strengths led to earlier flowering. According to the results of leaf analysis as affected by solution strength during the flower harvest, absorption rates of N and K were greater when the strength was higher, and Ca and Mg showed the same tendency. On the other hand, the absorption rate of P was the lowest in all treatments.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.