Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Localization using Ego Motion based on Fisheye Warping Image

어안 워핑 이미지 기반의 Ego motion을 이용한 위치 인식 알고리즘

  • Choi, Yun Won (Automotive IT Platform Research Team, ETRI) ;
  • Choi, Kyung Sik (Secondary Vocational Education Policy Division, Ministry of Education) ;
  • Choi, Jeong Won (Department of Automatic Electrical Engineering, Yeungnam College of Science & Technology) ;
  • Lee, Suk Gyu (Department of Electrical Engineering, Yeungnam University)
  • 최윤원 (한국전자통신연구원 자동차IT플랫폼연구팀) ;
  • 최경식 (교육부 직업교육정책과) ;
  • 최정원 (영남이공대학교 전기자동화과) ;
  • 이석규 (영남대학교 전기공학과)
  • Received : 2013.06.21
  • Accepted : 2013.10.04
  • Published : 2014.01.01
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Abstract

This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

Keywords

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