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곽기성,이효연,이준규,염도준,유재은,한영희,박병준,Kwak, K.S.,Lee, H.Y.,Rhee, J.K.,Youm, D.,Yoo, J.,Han, Y.H.,Park, B.J. The Korean Superconductivity Society 2012 Progress in superconductivity Vol.13 No.3
In this paper, we used E-J constitutive law and H-formulation to calculate magnetic field profile, current density, and magnetization of high temperature superconductor (HTS) placed in time varying applied magnetic field. Finite element method (FEM)-based software, Comsol Multiphysics 3.5a, was employed to simulate 2-dimensional model of a superconducting thin strip. The numerical results based on Kim's critical state model were compared with the case of strip in a perpendicular field in the Brandt's paper as well as experimental data observed by Scanning Hall Probe and SQUID.
곽기성(GiSung Gwak),염승재(SeungJae Yum),황성호(Sung-Ho Hwang) 대한기계학회 2014 대한기계학회 춘추학술대회 Vol.2014 No.11
This paper proposes an algorithm to detect the lane on the road using line and lane width information captured by front and AVM camera. First, we perform inverse perspective mapping about image captured by front camera, and then combine front camera image with AVM image. Lastly, we extend region of interest from the front camera image to AVM image to detects the lane because the closer to the vehicle, the higher probability of lane. Experimental results show that the proposed algorithm successfully improved lane detection.
곽기성(Gisung Gwak),임준영(Junyoung Lim),박찬호(Chanho Park),유동연(Dongyeon Yu),황성호(Sung-Ho Hwang) 대한기계학회 2018 대한기계학회 춘추학술대회 Vol.2018 No.12
Recently, with the rapid development of autonomous driving technology, autonomous driving system has already been commercialized at Level 2. However, existing lane detection technology in Level 2 systems is based on a relatively ideal situation in which the lane is clear as the highway and the curvature is moderate. Therefore, it is difficult to apply and commercialize to complex lane environments such as large curvature roads or off-ramp roads. In this paper, we propose a lane detection algorithm using hough transform algorithm for straight lane detection and RANSAC(Random sample consensus) algorithm. First, the road image is preprocessed using the feature of the road rules of the lane, and then the second order curve fitting is performed by applying the algorithm. Then, in order to detect the correct driving lane in the environment such as off-ramp roads, the information of a global path like navigation information is used. Finally, this algorithm is verified to detect the lane robustly in complex lane environments.
도심 주행을 위한 AVM 영상과 RTK GPS를 이용한 차량의 정밀 위치 추정
곽기성(Gisung Gwak),김동규(DongGyu Kim),황성호(Sung-Ho Hwang) 유공압건설기계학회 2020 드라이브·컨트롤 Vol.17 No.4
To ensure the safety of Advanced Driver Assistance Systems (ADAS) or autonomous vehicles, it is important to recognize the vehicle position, and specifically, the increased accuracy of the lateral position of the vehicle is required. In recent years, the quality of GPS signals has improved a lot and the price has decreased significantly, but extreme urban environments such as tunnels still pose a critical challenge. In this study, we proposed stable and precise lane recognition and tracking methods to solve these two issues via fusion of AVM images and vehicle sensor data using an extended Kalman filter. In addition, the vehicle"s lateral position recognition and the abnormal state of RTK GPS were determined using this approach. The proposed method was validated via actual vehicle experiments in urban areas reporting multipath and signal disconnections.