• 한국수학교육학회지시리즈C:초등수학교육
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• 제27권1호
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• pp.19-38
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• 2024

본 연구는 로봇을 활용한 수학 융합 인공지능교육 프로그램을 개발하고 적용하여 인공지능 및 수학적 개념에 대한 학생의 이해 특성을 분석하는 것을 목적으로 한다. 이를 위해 초등 인공지능교육 내용 기준을 분석하여 인공지능의 개념 요소를 추출하고, 이를 효과적으로 융합할 수 있는 수학과 성취기준을 파악하였다. 특히 로봇의 움직임을 활용하기에 적합한 각도 단원과 사각형 단원을 선택하여 그 성취기준을 인공지능교육 내용 요소와 융합하기 위해 수업을 재구성함으로써 5회기(총 15차시) 분량의 프로그램을 개발하였다. 이를 초등학교 4학년 1개 학급 22명을 대상으로 5개월에 걸쳐 적용하고 적용시 드러난 학생들의 이해를 인공지능 내용 주제별로 분석한 결과, 로봇을 활용한 수학 융합 인공지능교육 프로그램은 인공지능 원리 및 수학적 개념 이해에 도움이 되는 것으로 나타났다. 또한 로봇의 활용은 실행 과정 및 결과 도출까지 일련의 절차를 시각적으로 확인하도록 함으로써 학생들의 인공지능과 수학적 이해뿐만 아니라 수업 참여도를 제고하는 것으로 확인되었다.

• 디지털융복합연구
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• 제19권8호
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• pp.225-234
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• 2021

팬데믹으로 인해 생활의 중심이 집으로 이동함에 따라 집을 다양한 활동에 최적화된 공간으로 만들어줄 수 있는 가정용 로봇의 개발이 활발하다. 이 연구는 로봇이 작업을 수행하는 상황에 따라 피드백을 하기 위한 접근 또는 회피 움직임이 사용자 경험에 미치는 효과를 확인하고자 하였다. 작업 수행 상황과 움직임 조건에 따라 6가지 시나리오를 구성하여, 각 조건에 따른 호감도, 인지된 지능, 친밀감, 부정적 태도, 행동 예측가능성을 측정하였다. 실험 결과, 작업 수행 상황에서는 인지된 지능과 친밀감, 행동 예측가능성에서 주효과가 나타났고, 움직임 조건에서는 호감도, 인지된 지능, 친밀감에서 주효과가 나타났다. 상호작용 효과는 호감도와 인지된 지능에서만 나타났다. 결론적으로 로봇의 움직임에도 접근-회피 경험을 적용할 수 있고, 회피에 따른 부정적 효과를 확인할 수 있었다.

• IEIE Transactions on Smart Processing and Computing
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• 제5권6호
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• pp.375-382
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• 2016

This paper realizes control of the motion of a swimming robot fish in order to implement an underwater robot fish aquarium. And it implements positional control of a two-axis trajectory path of the robot fish in the aquarium. The performance of the robot was verified though certified field tests. It provided excellent performance in driving force, durability, and water resistance in experimental results. It can control robot motion, that is, it recognizes an object by using an optical flow object-detecting algorithm, which uses a video camera rather than image-detecting sensors inside the robot fish. It is possible to find the robot's position and control the motion of the robot fish using a radio frequency (RF) modem controlled via personal computer. This paper proposes realization of robot fish motion-tracking control using the optical flow object-detecting algorithm. It was verified via performance tests of lead-lag action control of robot fish in the aquarium.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권1호
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• pp.1-11
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• 2015

A concept of Deep Level Situation Understanding is proposed to realize human-like natural communication (called casual communication) among multi-agent (e.g., humans and robots/machines), where the deep level situation understanding consists of surface level understanding (such as gesture/posture understanding, facial expression understanding, speech/voice understanding), emotion understanding, intention understanding, and atmosphere understanding by applying customized knowledge of each agent and by taking considerations of thoughtfulness. The proposal aims to reduce burden of humans in humans-robots interaction, so as to realize harmonious communication by excluding unnecessary troubles or misunderstandings among agents, and finally helps to create a peaceful, happy, and prosperous humans-robots society. A simulated experiment is carried out to validate the deep level situation understanding system on a scenario where meeting-room reservation is done between a human employee and a secretary-robot. The proposed deep level situation understanding system aims to be applied in service robot systems for smoothing the communication and avoiding misunderstanding among agents.

• Journal of Information Technology Applications and Management
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• 제20권2호
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• pp.147-160
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• 2013

Today, the management environments of intelligence firm are changing the way of production planning and logistics management, and are changing the process of supply chain management system. This paper shows the development of information system software for intelligence enterprises is used in supply chain management for robot engineering industry. Specifically, supply chain management system in this paper has been developed to analyze the impact of multi plant and multi distribution environment, showing the process analysis and system development of hierarchical assembly manufacturing industry. In this paper we consider a production planning and distribution management system of intelligence firm in the supply chain. We focus on a capacitated production resource and distribution volume allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using a genetic algorithm to solve it efficiently. This method makes it possible for the population to reach the feasible approximate solution easily. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solution converge to the feasible approximate solution quickly.

• 한국멀티미디어학회논문지
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• 제25권8호
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• pp.1049-1058
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• 2022

HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권11호
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• pp.522-531
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• 2001

Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.

• 전자통신동향분석
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• 제39권1호
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• pp.95-105
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• 2024

In natural language processing, large language models such as GPT-4 have recently been in the spotlight. The performance of natural language processing has advanced dramatically driven by an increase in the number of model parameters related to the number of acceptable input tokens and model size. Research on multimodal models that can simultaneously process natural language and image data is being actively conducted. Moreover, natural-language and image-based reasoning capabilities of large language models is being explored in robot artificial intelligence technology. We discuss research and related patent trends in robot task planning and code generation for robot control using large language models.

• 로봇학회논문지
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• 제17권2호
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• pp.103-109
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• 2022

The purpose of this study is to ethical review on the development and service with care assistance robot. An integrative review concept analysis method was used. We analyzed the classification and role of service robots, the concept of the robot ethic and the care ethic. And there were derived the development and service about care assistance robot in ethical viewpoint. For improving current care problem, government had support to developing four types care assistance robots. But there were provided carefully care service due to the limitations of robot technology and lack of overall social awareness with care robot. In addition, in order to be successfully application in the field, care assistance robots were developed to provide high-quality care service that can consider to personal culture and living environment with the development of artificial intelligence and robot technology, as well as ethical care service.

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.