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A Real Time Lane Detection Algorithm Using LRF for Autonomous Navigation of a Mobile Robot

LRF 를 이용한 이동로봇의 실시간 차선 인식 및 자율주행

  • Kim, Hyun Woo (Department of Electrical Engineering, Pusan National University) ;
  • Hawng, Yo-Seup (Department of Electrical Engineering, Pusan National University) ;
  • Kim, Yun-Ki (Department of Electrical Engineering, Pusan National University) ;
  • Lee, Dong-Hyuk (Department of Electrical Engineering, Pusan National University) ;
  • Lee, Jang-Myung (Department of Electrical Engineering, Pusan National University)
  • 김현우 (부산대학교 전자전기공학과) ;
  • 황요섭 (부산대학교 전자전기공학과) ;
  • 김윤기 (부산대학교 전자전기공학과) ;
  • 이동혁 (부산대학교 전자전기공학과) ;
  • 이장명 (부산대학교 전자전기공학과)
  • Received : 2012.10.18
  • Accepted : 2013.08.19
  • Published : 2013.11.01

Abstract

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.

Keywords

References

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