• 제어로봇시스템학회논문지
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• 제19권3호
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• pp.227-232
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• 2013

BCI (Brain Computer Interface) is technology to control external devices by measuring the brain activity, such as electroencephalogram (EEG), so that handicapped people communicate with environment physically using the technology. Among them, EEG is widely used in various fields, especially robot agent control by using several signal response characteristics, such as P300, SSVEP (Steady-State Visually Evoked Potential) and motor imagery. However, in order to control the robot agent without any constraint and precisely, it should take advantage of not only a signal response characteristic, but also combination. In this paper, we try to use the fusion of motor imagery and P300 from EEG for practical use of robot control in BCI environment. The results of experiments are confirmed that the recognition rate decreases compared with the case of using one kind of features, whereas it is able to classify each both characteristics and the practical use technology based on mobile robot and wireless BCI measurement system is implemented.

• 한국디자인학회:학술대회논문집
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• 한국디자인학회 1999년도 추계 학술발표대회 논문집
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• pp.50-51
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• 1999

웹 디자인 과정에 있어서 기존의 웹사이트들의 컨텐츠 정보뿐만 아니라 인터페이스를 기능적으로 이루고 있는 구조요소들에 관한 데이터 수집의 필요성이 요구된다. 그럼에도 불구하고 홈페이지 디자인에 있어 specification 수립을 위한 참고자료로써 또는 사용성 평가를 위한 자료로써 이런 종류의 데이터 베이스는 방대한 양의 인터넷 정보에 비해 미미한 편이다. (중략)

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.896-902
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• 2004

The purpose of the study of multi-robot system is to realize multi-robot system easy for the control of robot system in case robot is adapted in the complicated environment of task structure. The purpose of the study of multi-robot system is to realize multi-robot system easy for the control of robot system in case robot is adapted in the complicated environment of task structure. To make real time control possible by making effective use of recognized information in this dynamic environment, suitable distribution of tasks should be made in consideration of function and role of each performing robots. In this paper, IHMA (Intelligent Hybrid Modular Architecture) of Intelligent combined control architecture which utilizes the merits of deliberative and reactive controllers will be suggested and its efficiency will be evaluated through the adaptation of control architecture to representative multi-robot system.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.435-441
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• 2013

A swarm robot system consists of with multiple mobile robots, each of which is called an agent. Each agent interacts with others and cooperates for a given task and a given environment. For the swarm robotic system, the loss of the entire work capability by malfunction or damage to a single robot is relatively small and replacement and repair of the robot is less costly. So, it is suitable to perform more complex tasks. The essential component for a swarm robotic system is an inter-robot collaboration strategy for teamwork. Recently, the swarm intelligence theory is applied to robotic system domain as a new framework of collective robotic system design. In this paper, FA (Firefly Algorithm) which is based on firefly's reaction to the lights of other fireflies and their social behavior is employed to optimize the group behavior of multiple robots. The main application of the firefly algorithm is performed on path planning of swarm mobile robots and its effectiveness is verified by simulations under various conditions.

• Industrial Engineering and Management Systems
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• 제8권3호
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• pp.181-193
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• 2009

This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1105-1108
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• 2003

The micro robot soccer playing system is introduced. Studying and learning, evolving in artificial agents are very difficult problem, but on the other hand we think more powerfully challenging task. In our laboratory, this soccer-system studies mainly centered on single agent learning problem. The construction of such experimental system has involved lots of kinds of challenges such as robot designing, vision processing, motion controlling. At last we will give some results showing that the proposed approach is feasible to guide the design of common agents system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.92.4-92
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• 2002

In this paper, as an ideal test bed for studies on multi-agent system, the multiple micro robot soccer playing system is introduced at first. The construction of such experimental system has involved lots of kinds of challenges such as sensors fusing, robot designing, vision processing, motion controlling, and especially the cooperation planning of those robots. So in this paper we want to stress emphasis on how to evolve the system automatically based on the model of behavior-based learning in multi-agent domain. At first we present such model in common sense and then apply it to the realistic experimental system . At last we will give some results showing that the proposed approach is feasi...

• 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.

• 품질경영학회지
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• 제31권3호
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• pp.114-125
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• 2003

In this paper, we deal with the problem of modeling of agent-based robot manufacturing cell. Its role is becoming increasingly important in automated manufacturing systems. For Object Oriented & Queueing Petri Nets (OO&QPNs), an extended formalism for the combined quantitative and qualitative analysis of different systems is used for structure and performance analysis of mobile robotic cell. In the case study, the OO&QPN model of a mobile robotic cell is represented and analyzed, considering multi-class parts, non-preemptive priority and alternative routing. Finally, the comparison of performance values between Shortest Process Time (SPT) rule and First Come First Serve (FCFS) rule is suggested. In general, SPT rule is most suitable for parts that have shorter processing time than others.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.353-356
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• 2007

로봇 시스템에서 지적 활동의 중심적 자료구조가 될 공유 메모리를 이용하여 로봇을 이루는 여러 Component Agent가 수집한 Context들과 산출된 Data들을 모아 Mental State를 구축한다. 로봇 Agent를 이루는 모든 컴포넌트들 간의 Data 교류는 Mental State를 통하여 일어나고, Reactive Layer와 Deliberative Layer로 구분 된 로봇을 구성하는 Agent들은 상황에 다라 변화된 context와 data값을 실시간으로 Mental State에 기록, 갱신한다. 이를 통하여 실시간 미션 수행 로봇이 효과적으로 목표를 수행할 수 있는 시스템 구조를 제시하고자 한다. 또한, 이러한 구조를 적용한 자가위치탐지 자율주행 로봇의 구현을 통해 본고에서 제시한 시스템 구조의 실현 가능성을 보이고자 한다.