Transactions of the Korean Society of Mechanical Engineers A (대한기계학회논문집A)

The Korean Society of Mechanical Engineers (대한기계학회)
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The Object Recognition Using Multi-Sonar Sensor and Neural Networks

복수 초음파센서와 신경망을 이용한 형상인식

  • Kim, Dong-Gi (Dept. of Mechanical Design Engineering, Graduate School of Chungnam National University) ;
  • O, Tae-Gyun (Dept. of Mechanical Design Engineering, Graduate School of Chungnam National University) ;
  • Gang, Lee-Seok (Dept. of Mechanical Design Engineering, Chungnam National University)
  • 김동기 (충남대학교 대학원 기계설계공학과) ;
  • 오태균 (충남대학교 대학원 기계설계공학과) ;
  • 강이석 (충남대학교 기계설계공학과)
  • Published : 2000.11.01
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Abstract

Typically, the ultrasonic sensors can be used in navigation systems for modeling of the enviornment, obstacle avoidance, and map building. In this paper, we tried to approach an object classification method using the range data of the ultrasonic sensors. A characterization of the sonar scan is described that allows the differentiation of planes, corners, edges, cylindrical and rectangular pillars by processing the scanned data from three sonars. To use the data from the ultrasonic sensors as input to the neural networks, we have introduced a clustering, threshold, and bit operation algorithm for the obtained raw data, After repeated training of the neural network, the performance of the proposed method was obtained through experiments. Also, the recognition ranges of the proposed method were investigated. As a result of experiments, we found that the proposed method successfully recognized the objects within the accuracy of 78%.

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References

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