• 전자공학회논문지 IE
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• 제47권2호
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• pp.66-72
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• 2010

자율적인 다중이동 로봇환경에서는 현시점에서 목표점까지 장애물과 충돌없이 연결하는 최적 경로를 설정하는 것은 필수불가결하며 매우 중요하다. 실제 많은 이동로봇은 주위 장애물에 대하여 주어진 정보 없이 미지의 환경에서 자율적 이동이 가능해야 한다. 따라서 본 논문에서는 다중이동 로봇환경에 적합한 새로운 형태의 충돌회피 최적경로에 대한 방법을 연구한다. 잘 알려진 포텐셜필드 방법을 이용하여 다중이동 로봇의 전역경로를 계획하고, 퍼지로직 시스템을 이용하여 각 로봇에 근접하는 혹은 경로를 가로막는 장애물과의 충돌을 피하기 위한 지역경로를 계획한다. 제안된 방법의 성능 및 정확성을 검증하기 위해 다양한 모의실험을 진행하여 결과를 검증하고 이의 결과를 토의한다.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.41-46
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• 2006

Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2731-2736
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• 2003

In highly informative, perception-rich environments that we call Omniscient Spaces, robots interact with physical objects which in turn afford robots the information showing how the objects should be manipulated. Object manipulation is commonly believed one of the most basic tasks in robot applications. However, no approaches including visual servoing seem satisfactory in unstructured environments such as our everyday life. Thus, in Omniscient Spaces, the features of the environments embed themselves in every entity, allowing robots to easily identify and manipulate unknown objects. To achieve this end, we propose a new paradigm of the interaction through Radio Frequency Identification (RFID). The aim of this paper is to learn about RFID and investigate how it works in object manipulation. Specifically, as an innovative trial for autonomous, real-time manipulation, a likely mobile robot equipped with an RFID system is developed. Details on the experiments are described together with some preliminary results.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.187-193
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• 2021

Our final goal is to implement nursing robots that can recognize patient's faces and their medicine on prescription. They can help patients to take medicine on time and prevent its abuse for recovering their health soon. As the first step, we proposed a medicine classifier with a low computational network that is able to run on embedded PCs without GPU in order to be applied to universal nursing robots. We confirm that our proposed model called MedicineNet achieves an 99.99% accuracy performance for classifying 15 kinds of medicines and background images. Moreover, we realize that the calculation time of our MedicineNet is about 8 times faster than EfficientNet-B0 which is well known as ImageNet classification with the high performance and the best computational efficiency.

• 한국지능시스템학회논문지
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• 제22권4호
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• pp.435-440
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• 2012

최근 산업 현장에서 자율주행 시스템에 관한 관심이 날로 증대되고 있다. 자율이동 로봇을 포함한 자율주행 시스템은 인간의 지속적인 도움 없이 거칠고 변화하며 구조화되지 않으면서도 불확실한 주변 환경에서 원하는 작업을 수행할 수 있는 능력을 지녀야 한다. 이를 위해서 근거리 무선통신 네트워크로 로봇 간 서로 교신을 하여 위치 및 상태 등의 정보를 공유를 통해 원만한 자율 주행을 할 수 있는 시스템의 설계가 요구된다. 본 논문에서는 센서 네트워크 및 무선네트워크에 기반한 자율주행 시스템을 개발하고 실험을 통하여 개발된 시스템의 성능을 검증한다.

• 한국지능시스템학회논문지
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• 제18권5호
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• pp.599-604
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• 2008

최근 외부 개입 없이 스스로 주변 환경을 파악하고 목적지까지의 이동경로를 생성하여 자율 주행하는 지능형 시스템에 관한 연구가 활발히 진행되고 있다. 이러한 자율 주행 시스템은 기본적으로 운행 중에 사고가 발생하지 않고 안전하게 목표점까지 이동해야 한다. 본 논문에서는 레이저 변위 센서를 이용하여 노면의 왜곡(훼손된 노면, 비포장 도로, 장애물 등)을 검출하고, 영상 이진화 기법을 적용하여 위험 요소를 검출, 판단하여 주행 시스템의 안정적 운항이 가능한 경로를 생성하는 기법을 제안한다. 제안 기법의 타당성은 임의로 제작된 국부영역의 지도 데이터에 기반한 모의실험을 통하여 보인다.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권9호
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• pp.539-546
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• 2005

This paper describes a method of building the probability grid map for an autonomous mobile robot using the ultrasonic DAF(data association filter). The DAF, which evaluates the association of each data with the rest and removes the data affected by the specular reflection effect, can improve the reliability of the data for the Probability grid map. This method is based on the evaluation of possibility that the acquired data are all from the same object. Namely, the data from specular reflection have very few possibilities of detecting the same object, so that they are excluded from the data cluster during the process of the DAF. Therefore, the uncertain data corrupted by the specular reflection and/or multi-path effect, are not used to update the probability map, and hence building a good quality of a grid map is possible even in a specular environment. In order to verify the effectiveness of the DAF, it was applied to the Bayesian model and the orientation probability model which are the typical ones of a grid map. We demonstrate the experimental results using a real mobile robot in the real world.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.124-132
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• 2001

Autonomous of welding process in shipyard is ultimately necessary., since welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding robot that can navigate autonomously within the enclosure needs to be developed. To achieve the welding ra나, the robotic welding systems needs a sensor system for the recognition of the working environments and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with work environmental map. At the same time a strategy for environment recognition for welding mobile robot is proposed in order to recognize the work environment efficiently. The design of the sensor system, the algorithm for sensing the structured environment, and the recognition strategy and tactics for sensing the work environment are described and dis-cussed in detail.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2024-2029
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• 2005

In this paper, it is shown how a mobile robot can navigate with high speed in dynamic real environment. In order to achieve high speed and safe navigation, a robot collects environmental information. A robot empirically memorizes locations of high risk due to the abrupt appearance of dynamic obstacles. After collecting sufficient data, a robot navigates in high speed in safe regions. This fact implies that the robot accumulates location dependent environmental information and the robot exploits its experiences in order to improve its navigation performance. This paper proposes a computational scheme how a robot can distinguish regions of high risk. Then, we focus on velocity control in order to achieve high speed navigation. The proposed scheme is experimentally tested in real office building. The experimental results clearly show that the proposed scheme is useful for improving a performance of autonomous navigation. Although the scope of this paper is limited to the velocity control in order to deal with unexpected obstacles, this paper points out a new direction towards the intelligent behavior control of autonomous robots based on the robot's experience.