• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.692-697
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• 2011

There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid mobile robot that can dock with the other robot and transforms between wheeled robot and legged robot is proposed. The hybrid mobile robot platform has docking device with a peg and a cup module. In addition, the robot is possible to walk and drive according to condition of the road. A navigation algorithm of the hybrid mobile robot is proposed to improve the mobility of robots using docking algorithm based on image processing on the broken road and uneven terrain. The proposed method recognizes road condition through PSD sensor attached in front and bottom of the robot and selects an appropriate navigation method according to terrain surface. The proposed docking and navigation methods are verified through experiments using hybrid mobile robots.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.1009-1018
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• 2019

This paper describes the design and implementation of a rehabilitation medical device based on a EMG measurement. Rehabilitation systems are controlled using BLDC motors and motor drives. The BLDC motor drive controls the operation and the speed controls the drive through the external servo motor. In addition, potentiometer coupled to the outside of the motor transmits information about the position of the load being rotated by the motor. The rehabilitation algorithm is controlled by limiting the maximum angle of 0 to 120 by utilizing the motor according to the user setting stage during the rehabilitation exercise. The walking algorithm compensates motor control for the low leg of the signal using the difference value of the signal obtained with the surface denser attached to both inner muscles. The motor and surface denser are utilized for the walk motion to control the maximum angle of 0 to 80.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.941-947
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• 2018

Station transfers for smart card based railway networks refer to transfer pedestrian movements that occur at the origin and destination nodes rather than at a middle station. To calculate the optimum path for the railway network, a penalty for transfer pedestrian movement must be included in addition to the cost of within-car transit time. However, the existing link label-based path searching method is constructed so that the station transfer penalty between two links is detected. As such, station transfer penalties that appear at the origin and destination stations are not adequately reflected, limiting the effectiveness of the model. A ghost node may be introduced to expand the network, to make up for the station transfer penalty, but has a pitfall in that the link label-based path algorithm will not hold up effectively. This research proposes an optimal path search algorithm to reflect station transfer penalties without resorting to enlargement of the existing network. To achieve this, a method for applying a directline transfer penalty by comparing Ticket Gate ID and the line of the link is proposed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.269-275
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• 2013

Recently, importance of pedestrian road network is getting emphasized as it is possible to provide mobile device users with both route guidance services and surrounding spatial information. However, it costs a tremendous amount of budget for generating and renovating pedestrian road network nationally, which hinder further advances of these services. Hence, algorithms extracting pedestrian road network automatically based on raster data are needed. On the other hand, road dataset generated from raster data usually has unnecessary vertices which lead to maintenance disutility such as excessive turns and increase in data memory. Therefore, this study proposed a method of selecting a proper threshold automatically for separate road entity using not only Douglas-Peucker algorithm but also road attribute data of digital map in order to remove redundant vertices, which maximizes line simplification efficiency and minimizes distortion of shape of roads simultaneously. As a result of the test, proposed method was suitable for automatic line simplification in terms of reduction ratio of vertices and accuracy of position.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.2
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• pp.115-124
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• 2017

This study was to develop the balance insole system for detecting and improving the muscle imbalance of left and right side in lower limbs. We were to verify the validation of balance insole system by analyzing the strategy of muscular activities and foot pressure according to sound feedback. We developed the balance insole based FSR sensor modules for estimating the muscle imbalance using detecting foot pressure. The insole system was FPCB have 8-spot FSR sensor with sensitivity range of 64-level. The participants were twenty peoples who have muscle strength differences in left and right legs over 20%. We measured the muscular activity and foot pressure of left and right side of lower limbs in various gait environment for verifying the improvement effect of muscle imbalance according to sound feedback. They performed gait in slope at 0, 5, 10, 15% and velocity at 3, 4, 5km/h. The result showed that the level of muscle imbalance reduced within 30% for sound feedback of balance insole system contrast to high level of muscle imbalance at 169.9~246.8% during normal gait for increasing slope and velocity. This study found the validation of balance insole system with sound feedback stimulus. Also, we thought that it is necessary to research on the sensitivity of foot area, detection of muscle imbalance and processing algorithm of correction threshold spot.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.41-47
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• 2019

In this study, a smart assistive device is designed to recognize pedestrian signal and to provide audio instructions for visually impaired people in crossing streets safely. Walking alone is one of the biggest challenges to the visually impaired and it deteriorates their life quality. The proposed device has a camera attached on a pair of glasses which can detect traffic lights, recognize pedestrian signals in real-time using a machine learning algorithm on GPU board and provide audio instructions to the user. For the portability, the dimension of the device is designed to be compact and light but with sufficient battery life. The embedded processor of device is wired to the small camera which is attached on a pair of glasses. Also, on inner part of the leg of the glasses, a bone-conduction speaker is installed which can give audio instructions without blocking external sounds for safety reason. The performance of the proposed device was validated with experiments and it showed 87.0% recall and 100% precision for detecting pedestrian green light, and 94.4% recall and 97.1% precision for detecting pedestrian red light.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.233-235
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• 2012

해저보행로봇 CR200은 여러 개의 관절로 이루어진 6개의 다리를 이용하여 해저면에서 보행으로 이동하며 해저 정밀탐사 및 작업을 수행하는 로봇으로, 케이블로 연결된 선상제어실에서 원격 제어된다. CR200 시스템에서는 16개의 카메라가 장착될 예정이며, 취득된 카메라의 영상은 선상제어실의 비디오 컴퓨터로 전송되어 모니터링 및 녹화된다. 설계된 비디오 시스템에서 영상 전송은 전자기 간섭에 의한 화질 열화를 최소화하기 위하여 기가비트의 대역폭을 가진 이더넷과 광케이블을 통하여 디지털 형태로 전송되며, 아날로그 카메라의 영상은 비디오 인코더를 사용하여 디지털 영상으로 변환된 후에 전송된다. 본 논문에서는 CR200의 비디오 시스템의 설계를 소개하고, 실제로 제작하기 전에 설계된 비디오 시스템을 검증하기 위하여 테스트베드를 사용한 통합 테스트 결과를 제시한다. 아직 준비되지 않은 카메라에 대해서는 아이패드의 아날로그 영상 출력을 비디오 인코더의 입력으로 전달하여, 설계된 모든 카메라들이 동작하는 상황을 테스트베드로 실험하였다. 16개 카메라의 영상이 모니터링 및 녹화되는 상황을 테스트베드로 실험한 결과에 따르면, 압축률 10%의 H.264 동영상 압축 알고리즘을 사용할 경우에 30fps 영상의 모니터링 및 녹화에 각각 60Mbps의 전송량으로 비디오 시스템이 정상적으로 동작하는 것을 확인할 수 있었다. 비디오 데이터의 전송은 센서 및 제어 데이터의 전송과 같은 네트워크를 사용하지만, 비디오 데이터의 기가비트 네트워크 사용률은 평균 12%이기 때문에 비디오 데이터 전송으로 인하여 데이터 통신은 거의 영향을 받지 않는다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.77-85
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• 2011

In this paper, we propose an region segmentation and texture based feature extraction method which split the pavement and roadway from the camera which equipped to the visually impaired person during a walk. We perform the hough transformation method for detect the boundary between pavement and roadway, and devide the segmented region into 3-level according to perspective. Next step, split into pavement and roadway according to the extracted texture feature of segmented regions. Our walking assistance system use rotation-invariant LBP and GLCM texture features for compare the characteristic of pavement block with various pattern and uniformity roadway. Our proposed method show that can segment two regions with illumination invariant in day and night image, and split there regions rotation and occlution invariant in complexed outdoor image.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.315-321
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• 2017

This paper is a study on the design and realization of Pedestrian navigation service system for the visually impaired. As it is an user interface considering visually impaired, voice recognition functioned smartphone was used as the input tool and the Osteoacusis headset, which can vocally guide directions while recognizing the surrounding environment sound, was used as the output tool. Unlike the pre-existing pedestrian navigation smartphone apps, the developed system guides walking direction by the scale of the left and right stereo sound of the headset wearing, and the voice guidance about the forked or curved path is given several meters before according to the speed of the user, and the user is immediately warned of walking opposite direction or proceeding off the path. The system can acquire stable and reliable directional information using the motion tracker with the dynamic heading accuracy of 1.5 degrees. In order to overcome GPS position error, we proposed a robust trajectory planning algorithm for position error. Experimental results for the developed system show that the average directional angle error is 6.82 degrees (standard deviation: 5.98) in the experimental path, which can be stated that it stably navigated the user relatively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.249-256
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• 2016

Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.