Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Data Association of Robot Localization and Mapping Using Partial Compatibility Test

Partial Compatibility Test 를 이용한 로봇의 위치 추정 및 매핑의 Data Association

  • Yan, Rui Jun (Department of Mechatronics Engineering, Hanyang University) ;
  • Choi, Youn Sung (Department of Mechanical Engineering, Hanyang University) ;
  • Wu, Jing (Department of Mechatronics Engineering, Hanyang University) ;
  • Han, Chang Soo (Department of Robot Engineering, Hanyang University)
  • 염서군 (한양대학교 메카트로닉스공학과) ;
  • 최윤성 (한양대학교 기계공학과) ;
  • 무경 (한양대학교 메카트로닉스공학과) ;
  • 한창수 (한양대학교 로봇공학과)
  • Received : 2014.11.18
  • Accepted : 2015.11.27
  • Published : 2016.02.01
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Abstract

This paper presents a natural corners-based SLAM (Simultaneous Localization and Mapping) with a robust data association algorithm in a real unknown environment. Corners are extracted from raw laser sensor data, which are chosen as landmarks for correcting the pose of mobile robot and building the map. In the proposed data association method, the extracted corners in every step are separated into several groups with small numbers of corners. In each group, local best matching vector between new corners and stored ones is found by joint compatibility, while nearest feature for every new corner is checked by individual compatibility. All these groups with local best matching vector and nearest feature candidate of each new corner are combined by partial compatibility with linear matching time. Finally, SLAM experiment results in an indoor environment based on the extracted corners show good robustness and low computation complexity of the proposed algorithms in comparison with existing methods.

Keywords

References

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