• 조명전기설비학회논문지
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• 제25권8호
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• pp.122-131
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• 2011

In this paper, the design and analysis of a reconfigurable modular structure, which reforms itself according to the change of the environment and realize appropriate forms and motions, are dealt with. This modular is a free structure from the restrictions with constraints about fixed environment and has various forms and motions by combining units. The form of this unit has a shape of a square with 7 centimeters side each, and has a structure which can be combined in a chain-shape or a lattice-shape. Additionally, The structure has a mobility by being equipped with wheels so that it can be combined for itself. In this paper, all the wireless controllers, sensor system, and communicating method between modules according to module structures were suggested and transformation method to be transformed to shape of snakes, caterpillars were presented. Moreover, simulations for each method were performed to show the validity of the motions including motor torque analysis. All the motions suggested were realized and experimented, whereby the availability of the designed mechanism and algorithm was verified with the result of experiments.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.410-415
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• 2004

Employing knowledge of adaptive possibilities of agents in multi-agents system, we have explored new aspects of distributed modular systems for building ubiquitous heterogeneous robotic systems using intelligent building blocks (I-BLOCKS) [1] as reconfigurable modules. This paper describes early technological approaches related to technical design, experimental developments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop modular robotic systems. The processing technology presented in this paper is embedded inside each $DUPLO^1$ brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Block in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can easily do 'programming by building' and thereby create specific functionalities of a modular robotic structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modern artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing modular robotic system with different types of morphology, functionality and behavior. To assess these potential I-BLOCKS possibilities, the paper presents a limited range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular robots. The paper also reports briefly about earlier experiments of I-BLOCKS created on users' natural inspiration by a just defined concept of modular artefacts.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.421-426
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• 2004

Analyzing adaptive possibilities of agents in multi-agents system, we have discovered new aspects of ambient intelligence in distributed modular systems using intelligent building blocks (I-BLOCKS) [1]. This paper describes early scientific researches related to technical design, applicable experiments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop ambient intelligence applications. The processing technology presented in this paper is embedded inside each DUPLO1 brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Blocks in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can do 'programming by building' and thereby create specific functionalities of a modular structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modem artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing applications in ambient intelligence (AmI) environments. To illustrate these possibilities, the paper presents a range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular systems. The paper also reports briefly about earlier experiments of I-BLOCKS in different research fields, allowing users to construct AmI applications by a just defined concept of modular artefacts [3].

• 전기전자학회논문지
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• 제18권4호
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• pp.572-580
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• 2014

본 연구에서는 교육 및 놀이를 통해 창의력 증진이 가능한 재구성 모듈러 로봇에 대하여 다루고 있다. 보통 모듈러 로봇은 각각 셀들의 조합으로 변형 재구성하고 다양한 형태의 구조를 만드는데 적합한 로봇으로 설계되어 있지만 이를 이용하여 교육과 놀이를 주제로 한 연구는 국외에 소수 있으며 국내에는 전무하다. 제안하는 형태는 기존 모듈러 로봇과 같이 같은 동작만 반복하는 모듈이 아니라 소리를 내는 소리모듈, 바퀴가 달린 바퀴모듈, 시각적 표현을 위한 LED모듈, 전원공급을 위한 전원모듈, 통신을 위한 블루투스모듈, 움직이는 동작을 구현 가능하도록 하는 관절모듈이 있는 구조로 설계되어 있다. 이와 같은 다른 능력이 부여된 각 모듈의 다양한 결합을 이용하여 창의적 활동이 가능하도록 하고, 아이들이 쉽게 사용 할 수 있도록 한다. 본 연구에서는 모듈별 각기 다른 능력을 부여하여 교육과 놀이가 가능하도록 하는 방식의 모듈러 로봇의 설계 및 동작을 다루고 있다. 그리고 연구된 동작은 실제 제작 및 실험을 통해 동작의 유용성을 보였다.

• 전자공학회논문지CI
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• 제40권6호
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• pp.56-68
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• 2003

범용 신경망 연산기를 디지털 회로로 구현함에 있어 가장 까다로운 문제들 중 하나는 시냅스의 확장과 해당 네트워크에 맞게 뉴런들을 재배치하는 재구성 문제일 것이다. 본 논문에서는 이러한 문제들을 해결하기 위한 새로운 하드웨어 구조를 제안한다. 제안된 구조는 시냅스의 확장과 네트워크 구조의 변경을 위해 오리지날 디자인의 변경이 필요치 않으며, 모듈러 프로세싱 유니트의 확장을 통한 뉴런의 개수 및 레이어의 확장이 가능하다. 이 구조의 범용성 및 확장성에 대한 검증을 위해 다양한 종류의 다층 퍼셉트론 및 코호넨 네트워크를 구성하여 HDL 시뮬레이터를 통한 결과와 C 언어로 작성된 소프트웨어 시뮬레이터 결과를 비교하였으며 그 결과 성능이 거의 일치함을 확인하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권12호
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• pp.804-810
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• 2004

There are two important things for the general purpose neural network processor. The first is a capability to build various structures of neural network, and the second is to be able to support suitable learning method for that neural network. Some way to process various learning algorithms is required for on-chip learning, because the more neural network types are to be handled, the more learning methods need to be built into. In this paper, an improved hardware structure is proposed to compute various kinds of learning algorithms flexibly. The hardware structure is based on the existing modular neural network structure. It doesn't need to add a new circuit or a new program for the learning process. It is shown that rearrangements of the existing processing elements can produce several neural network learning modules. The performance and utilization of this module are analyzed by comparing with other neural network chips.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1263-1266
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• 2003

One of the hardest problems in implementation of digital neural network are extension of synapses and programmability for relocating neurons. This paper Proposes a new hardware structure to solve these problems. The proposed structure can reconfigure network connections without alteration of basic design, and extend number of synapses attached to one neuron. Also, it is possible to extend the number of neurons and layers by connecting many MPUs(Modular Processing Unit). Generality and extensibility are verified by composing various kinds of Perceptorn and Kohonen networks using the architecture proposed in this paper and the verification performances compares well with HDL simulation results as well as the results of C modelling.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.178.3-178
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• 2001

This paper is concerned with designing a neural network based navigator that is optimized in a user-defined sense for a mobile robot using ultrasonic sensors to travel to a goal position safely and efficiently without any prior map of the environment. The neural network has a dynamically reconfigurable structure that not only can optimize the weights but also the input sensory connectivity in order to meet any user-defined objective. Therefore, in this research, we can select an optimal subset of sensory inputs that results in the best performance related to both navigation and structural complexity. Further, this research uses the manually trained initial population and the modular neural network to alleviate ...