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자율이동로봇의 국부 초음파지도를 이용한 길잡이지도 선택 방법
강승균,임종환 濟州大學校 産業技術硏究所 1999 산업기술연구소논문집 Vol.10 No.1
Conventional position estimation has been performed by placing landmarks or giving the entire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orientation probability model using sonar sensors is applied to construct a local map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. The usefulness of all these approaches are illustrated with the results produced by a real robot equipped with ultrasonic sensors.
강승균,임종환,강철웅 제주대학교 공과대학 첨단기술연구소 2003 尖端技術硏究所論文集 Vol.14 No.1
The paper presents an efficient method for extracting the line segments in a local map of a robot's surroundings. The local map is composed of 2-D grids that have both the occupancy and orientation probabilities from sonar information. To find the shape of an object in a local map from orientation information, the orientations are clustered into several groups according to their values. The line segment is ,then, extracted from the clusters based on Hough transform. The proposed technique is illustrated by experiments in an indoor environment.
강승균,임종환,강철웅 제주대학교 공과대학 첨단기술연구소 2004 尖端技術硏究所論文集 Vol.15 No.1
The paper presents an efficient method of extracting line segment in a local map of robot's surroundings. The local map is composed of 2-D grids that have both the occupancy and orientation probabilities based on the bayesian map building model. The local map is continuously updated while the robot explorers its unknown environment and the orientations of all grids in the local map are clustered into several groups according to their values. The line segments are then extracted from the clusters based on least square methods. A merging method that reconstructs lines and corners is developed to build a topological map. The proposed technique is illustrated by experiments in an indoor environment.