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      KCI등재후보

      위상학적 공간 인식을 위한 효과적인 초음파 격자 지도 매칭 기법 개발 = Effective Sonar Grid map Matching for Topological Place Recognition

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      https://www.riss.kr/link?id=A100234126

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment
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      This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching b...

      This paper presents a method of sonar grid map matching for topological place recognition. The proposed method provides an effective rotation invariant grid map matching method. A template grid map is firstly extracted for reliable grid map matching by filtering noisy data in local grid map. Using the template grid map, the rotation invariant grid map matching is performed by Ring Projection Transformation. The rotation invariant grid map matching selects candidate locations which are regarded as representative point for each node. Then, the topological place recognition is achieved by calculating matching probability based on the candidate location. The matching probability is acquired by using both rotation invariant grid map matching and the matching of distance and angle vectors. The proposed method can provide a successful matching even under rotation changes between grid maps. Moreover, the matching probability gives a reliable result for topological place recognition. The performance of the proposed method is verified by experimental results in a real home environment

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      참고문헌 (Reference)

      1 박영빈, "실제 실내 환경에서 이동로봇의 위상학적 위치 추정" 한국로봇학회 4 (4): 25-33, 2009

      2 강한구, "선택적 Anchors 기반 Indoor GPS 및 EKF를 이용한 이동 로봇 위치 추정" 한국로봇학회 6 (6): 58-68, 2011

      3 N. L. Doh, "Systematic Representation of Edges in Topological Maps for Mobile Robots using Wavelet Transformation" 2833-2838, 2005

      4 O. M. Mozos, "Supervised learning of topological maps using semantic information extracted from range data" 2772-2777, 2006

      5 L. Kleeman, "Sonar sensing, in Handbook on Robotics" Springer 2008

      6 S. Thrun, "Robust Monte Carlo localization for mobile robots" 128 (128): 99-141, 2001

      7 Y. Lin, "New Method for Subpixel Image Matching with Rotation Invariance by Combining the Parametric Template Method and The Ring Projection Transform Process" 45 (45): 067202-, 2006

      8 J. J. Leonard, "Mobile robot localization by tracking geometric beacons" 7 (7): 376-382, 1991

      9 J.-S. Gutmann, "Incremental Mapping of Large Cyclic Environments" 318-325, 1999

      10 J. Choi, "Autonomous topological modeling of a home environment and topological localization using a sonar grid map" SPRINGER 30 (30): 351-368, 201105

      1 박영빈, "실제 실내 환경에서 이동로봇의 위상학적 위치 추정" 한국로봇학회 4 (4): 25-33, 2009

      2 강한구, "선택적 Anchors 기반 Indoor GPS 및 EKF를 이용한 이동 로봇 위치 추정" 한국로봇학회 6 (6): 58-68, 2011

      3 N. L. Doh, "Systematic Representation of Edges in Topological Maps for Mobile Robots using Wavelet Transformation" 2833-2838, 2005

      4 O. M. Mozos, "Supervised learning of topological maps using semantic information extracted from range data" 2772-2777, 2006

      5 L. Kleeman, "Sonar sensing, in Handbook on Robotics" Springer 2008

      6 S. Thrun, "Robust Monte Carlo localization for mobile robots" 128 (128): 99-141, 2001

      7 Y. Lin, "New Method for Subpixel Image Matching with Rotation Invariance by Combining the Parametric Template Method and The Ring Projection Transform Process" 45 (45): 067202-, 2006

      8 J. J. Leonard, "Mobile robot localization by tracking geometric beacons" 7 (7): 376-382, 1991

      9 J.-S. Gutmann, "Incremental Mapping of Large Cyclic Environments" 318-325, 1999

      10 J. Choi, "Autonomous topological modeling of a home environment and topological localization using a sonar grid map" SPRINGER 30 (30): 351-368, 201105

      11 I. Ulrich, "Appearance-Based Place Recognition for Topological Localization" 1023-1029, 2000

      12 P. Buschka, "A Virtual Sensor for Room Detection" 637-642, 2002

      13 A. Pronobis, "A Discriminative Approach to Robust Visual Place Recognition" 3829-3836, 2006

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
      2021-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2018-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2015-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2013-01-01 평가 등재후보 1차 FAIL (등재후보1차) KCI등재후보
      2012-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2011-01-01 평가 등재후보학술지 유지 (등재후보1차) KCI등재후보
      2009-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
      2008-09-30 학회명변경 한글명 : 한국로봇공학회 -> 한국로봇학회
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.59 0.59 0.45
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.38 0.31 0.716 0.11
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