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이동로봇의 동시적 위치추정 및 지도작성을 위한 초음파 데이터의 효과적 활용
이세진,이경민 한국기계기술학회 2012 한국기계기술학회지 Vol.14 No.1
This paper shows how effectively sonar data can be worked with approaches suggested for the indoor SLAM (Simultaneous Localization And Mapping). A sonar sensor occasionally provides wrong distance range due to the wide beam width and the specular reflection phenomenon. To overcome weak points enough to use for the SLAM, several approaches are proposed. First, distance ranges acquired from the same object have been stored by using the FPA (Footprint-association) model, which associates two sonar footprints into a hypothesized circle frame. Using the Least Squares method, a line feature is extracted from the data stored through the FPA model. By using raw sonar data together with the extracted features as observations, the visibility for landmarks can be improved, and the SLAM performance can be stabilized. Additionally, the SP (Symmetries and Perturbations) model, a representation of uncertain geometric information that combines the probability theory and the theory of symmetries, is applied in this paper. The proposed methods have been tested in a real home environment with a mobile robot.
ORB-SLAM의 재지역화 성능 개선을 위한 전문적인 시각적 어휘 활용
조현우(Hyunwoo Cho),서영건(Yeong Geon Seo),이수원(Suwon Lee) 한국디지털콘텐츠학회 2021 한국디지털콘텐츠학회논문지 Vol.22 No.11
ORB-SLAM is widely used in real-time applications since it enables real-time localization and mapping. ORB-SLAM tries to relocalize when tracking fails, and the relocalization performance varies greatly depending on which visual vocabulary is used. Since visual vocabulary has to be prepared before ORB-SLAM is executed, it is usually trained in advance using local features extracted from general images. However, the visual vocabulary was not created considering the environment in which ORB-SLAM is performed. If the environment in which ORB-SLAM is performed can be known in advance, using the visual vocabulary most appropriate for the environment will lead to the best relocalization performance. This paper proposes a specialized visual vocabulary and shows that using the specialized visual vocabulary for the environment can improve the relocalization performance of ORB-SLAM through experiments.
이동로봇을 위한 Sonar Salient 형상과 선 형상을 이용한 EKF 기반의 SLAM
허영진(Young-Jin Heo),임종환(Jong-Hwan Lim),이세진(Se-Jin Lee) Korean Society for Precision Engineering 2011 한국정밀공학회지 Vol.28 No.10
Not all line or point features capable of being extracted by sonar sensors from cluttered home environments are useful for simultaneous localization and mapping (SLAM) due to their ambiguity because it is difficult to determine the correspondence of line or point features with previously registered feature. Confused line and point features in cluttered environments leads to poor SLAM performance. We introduce a sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The reliable line feature is expressed by its end points and engaged togather in EKF SLAM to overcome the geometric limits and maintain the map consistency. Experimental results demonstrate the validity and robustness of the proposed method.