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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Extraction of Different Types of Geometrical Features from Raw Sensor Data of Two-dimensional LRF

2차원 LRF의 Raw Sensor Data로부터 추출된 다른 타입의 기하학적 특징

  • Yan, Rui-Jun (Department of Mechatronics Engineering, Hanyang University) ;
  • Wu, Jing (Department of Mechatronics Engineering, Hanyang University) ;
  • Yuan, Chao (Department of Mechatronics Engineering, Hanyang University) ;
  • Han, Chang-Soo (Department of Robot Engineering, Hanyang University)
  • 염서군 (한양대학교 메카트로닉스공학과) ;
  • 무경 (한양대학교 메카트로닉스공학과) ;
  • 원조 (한양대학교 메카트로닉스공학과) ;
  • 한창수 (한양대학교 로봇공학과)
  • Received : 2014.10.27
  • Accepted : 2015.01.20
  • Published : 2015.03.01
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Abstract

This paper describes extraction methods of five different types of geometrical features (line, arc, corner, polynomial curve, NURBS curve) from the obtained raw data by using a two-dimensional laser range finder (LRF). Natural features with their covariance matrices play a key role in the realization of feature-based simultaneous localization and mapping (SLAM), which can be used to represent the environment and correct the pose of mobile robot. The covariance matrices of these geometrical features are derived in detail based on the raw sensor data and the uncertainty of LRF. Several comparison are made and discussed to highlight the advantages and drawbacks of each type of geometrical feature. Finally, the extracted features from raw sensor data obtained by using a LRF in an indoor environment are used to validate the proposed extraction methods.

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References

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