한국ITS학회 논문지 (The Journal of The Korea Institute of Intelligent Transport Systems)

  • 제13권5호
  • /
  • Pages.35-49
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  • 2014
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  • 1738-0774(pISSN)
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  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
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퍼지 기법을 이용한 다수 레이저스캐너 기반 객체 인식 알고리즘

Object Classification Algorithm with Multi Laser Scanners by Using Fuzzy Method

  • 이기룡 (아주대학교 일반대학원 전자공학과) ;
  • 좌동경 (아주대학교 전자공학과)
  • 투고 : 2014.04.11
  • 심사 : 2014.10.06
  • 발행 : 2014.10.31
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초록

본 논문에서는 레이저스캐너만으로 이루어진 감지 시스템을 이용하여 도로 위에 있는 객체의 위치를 추정하고 분류하는 알고리즘을 제안한다. 각각의 레이저 스캐너에서 획득한 데이터는 그리드 맵을 사용하여 데이터를 융합하였으며, 팽창 연산과 레이블링 방법을 사용하여 측정 오차를 보정하였다. 추출한 객체의 정보(길이, 폭)를 입력으로 사용한 퍼지방법을 통해 객체를 보행자, 자전거, 차량으로 분류하였으며, 이러한 방법은 레이저스캐너로만 이루어진 감지 시스템의 정확도를 증가시켰다. 또한 본 논문에서는 실제 도로 환경에서 몇 가지 시나리오를 설정하여 실험을 하였다. 실험을 통해 감지 시스템이 객체를 정확히 분류하는지, GPS-RTK 장비를 사용하여 획득한 위치 정보와 비교하여 객체의 위치 정보를 정확히 추정하는지 검증하였다.

This paper proposes the on-road object detection and classification algorithm by using a detection system consisting of only laser scanners. Each sensor data acquired by the laser scanner is fused with a grid map and the measurement error and spot spaces are corrected using a labeling method and dilation operation. Fuzzy method which uses the object information (length, width) as input parameters can classify the objects such as a pedestrian, bicycle and vehicle. In this way, the accuracy of the detection system is increased. Through experiments for some scenarios in the real road environment, the performance of the proposed detection and classification system for the actual objects is demonstrated through the comparison with the actual information acquired by GPS-RTK.

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참고문헌

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