무인 자동차의 2차원 레이저 거리 센서를 이용한 도시 환경에서의 빠른 주변 환경 인식 방법 Fast Scene Understanding in Urban Environments for an Autonomous Vehicle equipped with 2D Laser Scanners

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A map of complex environment can be generated using a robot carrying sensors. However,representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings,posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.
Publisher
한국로봇학회
Issue Date
2012-06
Language
Korean
Citation

로봇학회 논문지, v.7, no.2, pp.92 - 100

ISSN
1975-6291
URI
http://hdl.handle.net/10203/191265
Appears in Collection
EE-Journal Papers(저널논문)
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