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


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%.


  1. Tsujumura, Tackers, Yabuta, Tetsuro and Morimitsu, T., 1986, 'Three-Dimensional Shape Recognition Method Using Ultrasonics for Manipulator Control System,' Journal of Robotic system, Vol. 3, No. 2, pp. 205-216
  2. Drumheller, Michael, 1987, 'Mobile Robot Localization Using Sonar,' IEEE Trans. on Pattern Analysis and Machine Intelligence, March, Vol. PAMI-9, No. 2, pp. 325- 332
  3. Bozma, Omur and Kuc, Roman, 1991, 'Building a Sonar Map in a Specular Environment Using a Single Mobile 'Sensor,' IEEE Trans. on Pattern Analysis and Machine Intelligence, December, Vol. 13, No. 12, pp. 1260-1269
  4. Watanabe, Sumio and Yoneyama, Masahide, 1992, 'An Ultrasonic Visual Sensor for Three-Dimensional Object Recognition Using Neural Networks,' IEEE Trans. on Robotics and Automation, April, Vol. 8, No. 2, pp. 240-249
  5. Hong, Mun Li and Kleeman, Lindsay, 1992, 'Analysis of Ultrasonic Differentiation of Three Dimensional Comers, Edges and Planes,' IEEE Int. Conf. on Robotics and Automation, pp. 580-584
  6. Akbarally, Huzefa and Kleeman, Lindsay, 1995, 'A Sonar Sensor for Accurate 3D Target Localization and Classification,' IEEE Int. Conf. on Robotics and Automation, pp. 3003-3008
  7. Dror, Itiel E., Zagaeski, Mark and Moss, Cynthia F., 1995, 'Three-Dimensional Target Recognition via Sonar : A Neural Network Model,' Neural Networks, Vol. 8, No. 1, pp. 149-160
  8. 이원, 윤인식, 유영철, 정의섭, 1997, '신경회로망을 이용한 초음파에코의 예측 및 평가,' 대한기계학회논문집, A권 제21권 제4호, pp. 586-595
  9. Song, Kai-Tai and Tang, Wen-Hui, 1996, 'Environment Perception for a Mobile Robot Using Double Ultrasonic Sensors and a CCD Camera,' IEEE Trans. on Industrial electronics, June, Vol. 43, No. 3, pp. 372-379
  10. Ko, Joong Hyup, Kim, Wan Joo and Chung, Myung Jin, 1996, 'A Method of Acoustic Landmark Extraction for Mobile Robot Navigation,' IEEE Trans. on Robotics and Automation, Vol. 12, No. 3, pp. 478-485
  11. Dror, Itiel E., Florer, Faith L., Danmien, Rios and Zagaeski, Mark, 1996, 'Using Artificial Bat Sonar Neural Networks for Complex Pattern Recognition : Recognizing Faces and The Speed of a Moving Target,' Biol. Cybern. , No. 74, pp. 331-338
  12. 한영준, 한헌수, 1998, '2쌍의 초음파센서를 이용한 측정면의 위치 측정 및 종류 분류 기법,' 한국 제어.자동차.시스템공학 논문지, 제4권, 제6호, pp. 747-752
  13. Pao, Y. H., 1989, Adaptive Pattern Recognition and Neural Networks, Addison-Wesley Publishing Company
  14. Kang, E. S. and Cho, H. S., 1995, 'Vibratory , Assembly of Prismatic Parts Using Neural Network-Based Positioning Error Estimation,' Robotica, Vol. 13, No. 2, pp. 185-193
  15. 박강, 1999, '인공신경망을 이용한 삼차원 물체의 인식과 정확한 자세계산,' 대한기계학회논문집, A권 제23권 제11호, pp. 1929-1939