• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.89-95
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• 2023

In recent decades, human action recognition (HAR) has demonstrated potential applications in sports analysis, human-robot interaction, and large-scale signage content. In this paper, spatial temporal attention graph convolutional network (STAGCN)-based HAR system is proposed. Spatioal-temmporal features of skeleton sequences are assigned different weights by STAGCN, enabling the consideration of key joints and viewpoints. From simulation results, it has been shown that the performance of the proposed model can be improved in terms of classification accuracy in the NTU RGB+D dataset.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.106-111
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• 2011

Video-based detection and tracking of moving objects has been widely used in real-time monitoring systems and a videoconferencing. Also, because object motion tracking can be expanded to Human-computer interface and Human-robot interface, Moving object tracking technology is one of the important key technologies. If we can track a specified object in an environment of multiple moving objects, then there will be a variety of applications. In this paper, we introduce a specified object motion tracking using particle filter. The results of experiments show that particle filter can achieve good performance in single object motion tracking and a specified object motion tracking in an environment of multiple moving objects.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.590-601
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• 2021

The current study explored how robot's persuasive intent and its' physical distance affect consumers' evaluaton on the robot and the product that the robot advertises. This study administered a 2 (level of pursasion intent: low vs. high) × 2 (physical distance: normal vs. close) between-subjects factorial design experiment. The findings revealed that consumers evaluated the robot' expertise and trustworthiness more negatively and reported lower intentions to buy the produce when they perceived robot's persasive intent saliently high. Consumers were also found to show more negative attitude toward the robot and lower intentions to buy the produce when the robot approached to their personal space more closely. The theoretical and practical implications about human-robot interaction in marketing context were discussed.

• Korean Journal of Child Studies
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• v.32 no.4
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• pp.1-14
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• 2011

The purpose of this study was to investigate young children's perceptions of a teacher assistant robot, IrobiQ. in a kindergarten classroom. The subjects of this study were 23 6-year-olds attending to G kindergarten located in E city, Korea, where the teacher assistant robot had been in operation since Oct. 2008. Each child responded to questions assessing the child's perceptions of IrobiQ's identity regarding four domains : it's biological, intellectual, emotional and social identity. Some questions asked the child to affirm or deny some characteristics pertaining to the robot and the other questions asked the reasons for the answer given. The results indicated that while majority of children considered an IrobiQ not as a biological entity, but as a machine, they thought it could have an emotion and be their playmate. The implications of these results are two folds : firstly, they force us to reconsider the traditional ontological categories regarding intelligent service robots to understand human-robot interaction and secondly, they open up an ecological perspective on the design of teacher assistant robots for use with young children in early childhood education settings.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.96-104
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• 2013

Study of human-robot Interaction gets more and more attention to expand the robot application for tasks difficult by robot alone. Developed countries are preparing for a new market by introducing the concept of 'Co-Robot' model of human-robot Interaction. Our research of direct teaching is a way to instruct robot's trajectory by human's handling of its end device. This method is more intuitive than other existing methods. The benefit of this approach includes easy and fast teaching even by non-professional workers. And it can enhance utilization of robots in small and medium-sized enterprises for small quantity batch production. In this study, we developed the algorithms for creating accurate trajectory from repeated inaccurate direct teaching and GUI for the direct teaching. We also propose the basic framework for direct teaching.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.22-30
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• 2019

For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot's understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.165-175
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• 2008

For an advanced intelligent service, the need of HRI technology has recently been increasing and the technology has been also improved. However, HRI components have been evaluated under stable and controlled laboratory environments and there are no evaluation results of performance in real environments. Therefore, robot service providers and users have not been getting sufficient information on the level of current HRI technology. In this paper, we provide the evaluation results of the performance of the HRI components on the robot platforms providing actual services in pilot service sites. For the evaluation, we select face detection component, speaker gender classification component and sound localization component as representative HRI components closing to the commercialization. The goal of this paper is to provide valuable information and reference performance on appling the HRI components to real robot environments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1096-1101
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• 2009

In this paper, an embedded system has been designed for force control application to interact between a robot arm and a human operator. Force induced by the human operator is converted to the desired position information for the robot to follow. For smooth operations, the impedance force control algorithm is utilized to represent interaction between the robot and the human operator by filtering the force. To improve the performance of position control of the robot arm, a velocity term has been obtained and tested by several filters. A PD controller for position control has been implemented on an FPGA as well. Experimental studies are conducted with the ROBOKER to test the functionality of the designed hardware.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1813-1814
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• 2008

본 논문에서는 생물학적 운동 메카니즘을 유사하게 구현하기 위해 신경 진동자를 이용한 로봇 팔 제어 시스템을 제안한다. 인간 및 동물의 주기적인 자율 운동을 관장하는 Central Pattern Generator (CPG)를 수학적으로 모델링한 신경 진동자는 그 중요 특성의 하나인 entrainment 효과를 보여준다. 일반적으로 우리는 이 기능을 이용하여 미지의 외부 환경 변화와 같은 외란에 적절히 상호 작용할 수 있는 운동을 생성해 낼 수 있다. 이러한 결과를 보이기 위해, 각 관절에 가상의 신경 진동자 모델을 결합하였고 외부 환경의 변화나 외란의 감지를 위한 F/T센서를 팔의 말단에 부착하여 시스템을 구현하였다. 신경 진동자 모델을 결합한 2축 링크 로봇 팔 시스템(real time)은 주어진 목적운동을 (원 운동) 수행함과 동시에 미지의 외부 환경의 변화(임의의 벽)를 인지하여 적절한 모션을 생성하는 지를 살펴본다.