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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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A Study on the Straight Path Prediction Technology of White LED Marker-based AGV in Indoor Environment

실내 환경에서 White LED 마커 기반 무인 운반차의 직진경로 예측 기술 연구

  • Woo, Deok gun (Graduate School of Nano IT Design Fusion, Seoul National University of Science & Technology) ;
  • vinayagam, Mariappan (Graduate School of Nano IT Design Fusion, Seoul National University of Science & Technology) ;
  • Kim, Young min (Ire front Co., Ltd.) ;
  • Cha, Jae sang (Dept. of Electronics & IT Media Eng., Seoul National University of Science and Technology)
  • 우덕건 (서울과학기술대학교 나노IT디자인융합대학원) ;
  • 마리아판비나야감 (서울과학기술대학교 나노IT디자인융합대학원) ;
  • 김영민 (이레프런트) ;
  • 차재상 (서울과학기술대학교 전자IT미디어공학과)
  • Received : 2018.10.01
  • Accepted : 2018.10.22
  • Published : 2018.10.31
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Abstract

With the 4th industry era, smart factories are emerging. In the era of multi-product small scale production, unmanned transportation vehicles are rapidly increasing in utilization of unmanned transportation vehicles that carry and arrange goods in the work space. The conventional unmanned vehicle detected its position by using the guided line method and the position based method for indoor location recognition and movement. This method has disadvantages of initial high cost and maintenance / maintenance. In this paper, to solve the disadvantages, the method of predicting the direct path of the unmanned vehicle through the Kalman filter is verified using the white LED marker of the warehouse and the position data and the image data of the white LED marker recognition image. Through this, the reliability of the linear movement which occupies the most part in the lattice structure is secured. It is also expected that the reliance on additional position sensors will also be reduced.

4차 산업시대와 함께 스마트 팩토리가 대두되고 있으며, 다품종 소량생산 시대를 맞이하여 무인 운반차는 작업공간에서 물건을 운반하고 정리하는 무인 운반차의 활용도가 빠르게 증대하고 있다. 기존의 무인 운반차는 실내 위치인식 및 이동을 위해 유도선 방식, 위치기반 방식을 사용하여 자신의 위치를 검출하였고 이러한 방법은 초기 고비용 및 유지/관리 보수의 단점이 있었다. 본 논문에서는 단점을 해결하고자 물류창고의 White LED 마커를 이용하여 위치 데이터와 White LED 마커 인식 이미지 데이터를 활용하여 칼만 필터를 통해 무인 운반차의 직전경로를 예측함에 하는 방안에 대해 검증하였다. 이를 통해 격자구조에서 대부분을 차지하는 직선 이동에 대한 신뢰성을 확보하였다. 또한 추가적인 위치 센서에 대한 의존도 또한 줄일 수 있을 것이라 예상된다.

Keywords

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