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무인 자율주행 차량의 장애물 인식을 위한 LiDAR의 포인트 클라우드 데이터 집단화 및 분류
윤동진(Dongjin Yoon),김재환(Jaehwan Kim),김정하(Jungha Kim) 한국자동차공학회 2012 한국자동차공학회 학술대회 및 전시회 Vol.2012 No.11
When UGV generate and trace the path, using the data of Light Detection and Ranging(LiDAR) is common method to take physical and environmental information of road condition. LiDAR calculate a distance between sensor and obstacle from the flying time of laser pulse, which is transmitted from sensor. Typically, obstacle that UGV have to avoid can be divided into two different types, static and moving-obstacle. Avoidance method for moving-obstacle is different from method for static-obstacle. Data type of LiDAR is point cloud. Judging type of obstacle by calculating vector from each points is difficult. So we have to simplify point cloud data into segments. This research proposes the algorithm of clustering method for segmentation and classifying the type of each segments.