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실외 이동로봇의 고도지도 기반 위치인식을 위한 고도관성모멘트 추출 및 정합
권태범(Tae-Bum Kwon),송재복(Jae-Bok Song),강신천(Sin-Cheon Kang) 제어로봇시스템학회 2009 제어·로봇·시스템학회 논문지 Vol.15 No.2
The problem of outdoor localization can be practically solved by GPS. However, GPS is not perfect and some areas of outdoor navigation should consider other solutions. This research deals with outdoor localization using an elevation map without GPS. This paper proposes a novel feature, elevation moment of inertia (EMOI), which represents the distribution of elevation as a function of distance from a robot in the elevation map. Each cell of an elevation map has its own EMOI, and outdoor localization can be performed by matching EMOIs obtained from the robot and the pre-given elevation map. The experiments and simulations show that the proposed EMOI can be usefully exploited for outdoor localization with an elevation map and this feature can be easily applied to other probabilistic approaches such as Markov localization method.
Immunoglobulin G4 비관련 특발성 경화성 장간막염
권태형 ( Tae Hyung Kwon ),조광범 ( Kwang Bum Cho ),이현직 ( Hyun Jik Lee ),권선영 ( Sun Young Kwon ),이윤석 ( Yoon Suk Lee ) 대한소화기학회 2019 대한소화기학회지 Vol.73 No.1
Sclerosing mesenteritis is a rare benign disease with a prevalence of 0.16-3.4% and is characterized by chronic nonspecific inflammation and extensive fibrosis in the adipose tissue of the mesentery although the exact pathogenesis is still elusive. A 65-year-old woman was referred with suspicion of an abdominal mass and biliary stones on abdominal ultrasonography and CT. Bile duct stones were confirmed by endoscopic ultrasonography and successfully treated by endoscopic retrograde cholangiography with stone removal. Furthermore, a 4.7 cm conglomerated mass on small intestinal mesentery was suspected as sclerosing mesenteritis based on the features on abdominal MRI. However, because it could not be differentiated from malignancy without histologic examination, laparoscopic excisional biopsy was performed; it showed only inflammatory cells with extensive fibrosis. Therefore, the abdominal mass was confirmed as sclerosing fibrosis and the patient was followed-up without any treatments because no mass-related symptoms accompanied the findings. Six months later, abdominal CT showed no significant change in the mass. Herein, we report a rare case of incidentally found idiopathic sclerosing mesenteritis. (Korean J Gastroenterol 2019;73:50-55)
토폴로지컬 정보를 이용한 그레디언트 방법에서의 검색영역 축소
함종규(Jong-Gyu Ham),권태범(Tae-Bum Kwon),송재복(Jae-Bok Song),정우진(Woojin Chung) 대한기계학회 2005 대한기계학회 춘추학술대회 Vol.2005 No.5
Path planning is a key element in navigation of a mobile robot. Several algorithms such as the gradient method have been successfully implemented so far. Although the gradient method can provide the global optimal path, it computes the navigation function over the whole environment at all times, this resulting in long computation time. This paper proposes modified gradient method in which the search space for the computation of navigation function can be significantly reduced using the topological information which approximately coincides with the path. The computing time of the gradient method can therefore be significantly decreased without loosing the global optimality.
무인차량의 강인한 경유점 주행을 위한 베지어 곡선 기반 경로 계획
이상훈(Sanghoon Lee),전창묵(Changmook Chun),권태범(Tae-Bum Kwon),강성철(Sungchul Kang) 제어로봇시스템학회 2011 제어·로봇·시스템학회 논문지 Vol.17 No.5
This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.