• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2433-2435
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• 2002

The purpose of this paper is to introduce a case study of developing a miniature biped robot. The biped robot has a total of twenty-one degrees of freedom(DOF) ; There are two legs which have six DOF each, two arms which have three DOF each and a waist which has three DOF. RC servo-motors were used as actuators. We have developed motor controller, sensor controller and ISA-interface card. Motor controller, PWM generator, can control eight motors Sensor controller is connected to eight FSR(Force Sensing Resistors). For high level controller communicate with low level controller, ISA-interface card has developed. For the stable walking, CMAC(Cerebellar Model Articulation Controller) neural network algorithm is applied to our system CMAC is robust at noise.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.141-147
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• 2007

In this paper, we define the multi-states exponential cell resident time mobility model for describing the mobility characteristics of mobile user and analyzed the total cost of the hybrid method using multi-states cell resident time. Generally, the mobile user has three states for its movement, such as staying, walking and driving. This multi-states cell resident time based hybrid method reflects the movement characteristics of mobile user and adapts the location update period according to the states of mobility speed. As a results of the performance analysis, we can get the optimum parameters of the hybrid method for multi-states based mobile users.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.329-330
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• 2007

지능형 로봇에서 환경인식과 이러한 환경에 따른 행동 결정능력은 로봇이 필수적으로 갖추어야 할 기능이다. 본 논문은 이족로봇 플랫폼에서 비전기반 환경인식과 이를 통한 안정적인 보행 제어시스템을 제안한다. 비전기반 환경인식 시스템은 움직임 모델을 이용한 로봇 자체 움직임 보정 모듈, Adaboost를 이용한 장애물 영역 추출, PCA를 이용한 장애물 특징 추출, Hierarchical SVM을 이용한 장애물 인식 모듈로 구성되어 있으며, 이러한 환경 인식 시스템으로부터 보행 제어 시스템은 상황에 맞는 안정적이 보행 궤적을 생성한다. 보행 제어 시스템은 neural network을 이용하여 보행 궤적 생성 모듈과 보행 오차를 보정하기 위한 fuzzy 제어기 모듈로 구성되어 있다. 본 시스템을 제작한 로봇에 적용한 결과 보다 안정적인 보행을 할 수 있었다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.325-326
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• 2007

인간형 로봇(Humanoid)은 인간과 유사한 구조를 갖고 있는 로봇으로, 이족 보행이 가능하고 양 손이 자유롭기 때문에 인간 생활 환경에 적용이 가능하다. 인간형 로봇은 이족 보행 로봇의 형태를 지니며 보통 20 자유도(DOF : Degree of freedom) 이상의 높은 자유도와 직렬형 링크 구조로 인해 로봇의 안정도를 해석하고 움직임을 제어하기가 어렵다. 이러한 이유로 이족 보행 로봇 동작의 안정도를 증가시키기 위해 로봇의 최적화된 동작 패턴 생성과 자세 제어 등이 연구 되고 있다. 본 논문에서는 범용 근사자의 특징을 갖는 신경망을 이용하여 이족 보행 로봇의 동작 패턴 생성 방법에 대하여 제안하였다. 실제로 계획된 동작을 토대로 6가지의 동작 패턴을 생성하였으며 컴퓨터 모의실험과 상용 이족 보행 로봇을 이용하여 생성된 동작 패턴의 안정도를 확인해보고 제안된 방법에 타당성을 검증하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.750-752
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• 2010

MANET has some interest as a wireless mobile network supporting node mobility and having no additional infrastructure. Speed of mobile node on MANET is various from just slow speed of human's walk to vehicle's moving speed. In this study, VoIP performance of MANET is evaluated in the view of speed of mobile node. VoIP performance is studied on walking speed, vehicle speed and higher speed on MANET. PDR(Packet Delivery Ratio), MOS(Mean Opinion Score) are used as performance parameters.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.435-437
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• 2022

보행 보조 로봇의 효과적인 보조를 위해서는 사용자의 보행 유형을 인식하는 것이 중요하다. 본 논문에서는 end-to-end 분류 네트워크 기반 보행 환경 인식 방법을 사용하여 사용자의 보행 유형을 강인하게 추정한다. 실외 보행 환경을 오르막길, 평지, 내리막길 3 가지로 분류하는 딥러닝 모델을 학습시켰으며, 엣지 디바이스에서 이를 사용하기 위해 네트워크 경량화를 진행하였다. 경량화 후 추론 속도는 약 47FPS 수준으로 실시간으로 보행 보조 로봇에 적용 가능한 것을 검증했으며, 정확도 측면에서도 97% 이상의 성능을 얻을 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.389-395
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• 2006

This paper proposes the controller for biped robot using intelligent control algorithm. In order to simplify the complexity of biped robot control, manipulator of biped robot is divided into four modules. These modules are controlled by intelligent algorithm with Hierarchical Mixture of Experts(HME) using neural network. Also neural network having direct control method learns the inverse dynamics of biped robot. The HME, which is a network of tree structure, reallocates the input domain for the output by learning pattern of input and output. In this paper, as a result of learning HME repeatedly with EM algorithm, the controller for biped robot operating safety walking is designed by modelling dynamics of biped robot and generating virtual error of HME.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.86-94
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• 2011

In recent years, there has been a rise in epidemiological evidence suggesting the health benefits of a physically active lifestyle. However, it is not always easy for individuals to personally recognize the optimal conditions for exercise and physical activity. Wearable acceleration-based pedometers have become widely used in estimating the amount of physical activity, and to a limited extent, providing information regarding exercise intensity, but they have never been used to assess adaptation to exercise. In order to realize simultaneous activity monitoring for multiple users exercising outdoors, we developed a prototype wireless local area network (WLAN) based system. In our system, a WLAN is deployed outside, and a user wearing a smart phone and monitoring device exercises freely within the coverage area of the wireless network. By doing so, the developed system is able to monitor the activity of each user andmeasures various parameters including those related to exercise adaptation. In a demonstration experiment, the developed system was evaluated and used to monitor users enjoying a Nordic walk, after which users were immediately able to receive their exercise report. In this paper, we discuss the requirements and issues in developing an activity monitoring system and report the findings we obtained through the demonstration experiment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.147-154
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• 2008

A variety of activity happens around the sidewalk in the city. Particularly, a large variety of activity happens in shopping area, but it causes an obstruction of economical revitalization since the pedestrians require time and cost to find what they want. So, this study will develop the path searching method to minimize the economical loss of shoppers by providing the significant path and supporting the walking movement. Firstly, consider existing network expression techniques and approach three points which are physical and environmental factor, the recognition of the pedestrians' space when changing the direction, and the recognition of restriction of vision and accessibility. Try to design the network DB and simulate the algorithm. As a result, it is now possible to do the path searching that considers variety of recognition factors and show the method how to make the path-searching algorithm for pedestrian.