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무인 이동 개체의 경로 생성을 위한 레이저 스캐너와 비전 시스템의 데이터 융합을 통한 장애물 감지
鄭珍久(JinGu Jeong),洪錫敎(Sukkyo Hong),左東京(Dongkyoung Chwa) 대한전기학회 2008 전기학회논문지 Vol.57 No.7
This paper proposes object detection algorithm using laser scanner and vision system for the path planning of autonomous mobile agents. As the scanner-based method can observe the obstacles in only two dimensions, it is hard to detect the shape and the number of obstacles. On the other hand, vision-based method is sensitive to the environment and has its difficulty in the accurate distance measurement. Thus, we combine these two methods based on K-means algorithm such that the obstacle avoidance and optimal path planning of autonomous mobile agents can be achieved.
단일 레이저 스캐너를 이용한 모바일 로봇의 장애물 탐색 및 분리 알고리즘
이기룡(Giroung Lee),좌동경(Dongkyoung Chwa),홍석교(Sukkyo Hong) 대한전기학회 2007 대한전기학회 학술대회 논문집 Vol.2007 No.10
This paper proposes obstacle detection and classification algorithm using a single laser scanner. The proposed algorithm searches the object singular points using a differential equation, and finds obstacle singular points shows a boundary of obstacle. And the proposed algorithm can classify object even if several obstacles overlapped. Simulation results show the feasibility of proposed algorithm using a single laser scanner, not using several laser scanners.
張世龍(Seyong Jang),李起龍(Giroung Lee),宋奉燮(Bongsob Song),左東京(Dongkyoung Chwa),洪錫敎(Sukkyo Hong) 대한전기학회 2008 전기학회논문지 Vol.57 No.9
In this paper, the motion coordination algorithm of mobile agents in active sensor network is proposed to track the dynamic boundary for environmental monitoring. While most of dynamic boundary tracking algorithms in the literature were studied under the assumption that the boundary and/or its evolving rate is known a priori, the proposed algorithm is assumed that the individual active agent can measure the state of environment locally without any information of the boundary. When the boundary is evolving dynamically, the formation of active agents is designed to achieve two objectives. One is to track boundary layer based on the measured information and a small deviation. The other is to maintain a uniform distance between adjacent agents. The algorithm structure based on a state diagram is proposed to achieve these two objectives. Finally, it will be shown in the simulations that all given agents converge to a desired boundary layer and maintain a formation along the boundary. (e.g., a circle, an ellipse, a triangle and a rectangle)