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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Maze Navigation System Using Image Recognition for Autonomous Mobile Robot

자율이동로봇의 영상인식 미로탐색시스템

  • Published : 2005.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, the maze navigation system using image recognition for autonomous mobile robot is proposed. The proposed maze navigation system searches the target by image recognition method based on ADALINE neural network. The infrared sensor system must travel all blocks to find target because it can recognize only one block information each time. But the proposed maze navigation system can reduce the number of traveling blocks because of the ability of sensing several blocks at once. Especially, due to the simplicity of the algorithm, the proposed method could be easily implemented to the system which has low capacity processor.

Keywords

References

  1. A. C. Schultz, 'Using a genetic algorithm to learn strategies for collision avodiance and local navigation,' 7th Int, Symp on Unmanned, Untethered, Submersible Technology, Durham, NH, pp. 213-225, 1991
  2. M. Drigo and U. Schnepf, 'Genetics-based machine learning and behavior-based robotics: a new synthesis,' IEEE Trans. on Systems, Man and Cybernetics, vol. SMC-23, no. 1, 1993 https://doi.org/10.1109/21.214773
  3. G. Li and S. J. Louis, 'Designing control strategies for a simulated robot using non-randomly initialized genetic algorithms,' Proc. ISCA 5th Int. Conf. on Intelligent Systems, pp. 145-149, ISCA Press, 1996
  4. 이동욱, 심귀보, '분산유전알고리즘을 이용한 자율이동 로봇군의 행동진화', 제 5회 인공지능, 신경망 및 퍼지시스템 종합학술대회 발표논문집, pp. 127-130, 1996
  5. K. S. Narendra, 'Adaptive control of dynamical using neural networks in handbook of intelligent control,' van Nostrand, 1994
  6. L. Fausett, Fundamentals of neural networks, Prentice Hall, 1994
  7. C. G. Looney, Pattern recognition using neural network, Oxford Univ. Press, 1997
  8. S. S. Soliman, and S. Z. Hsue, 'Signal classfication using statistical monents,' IEEE Transactions on communications, vol. 40, no. 5, pp. 908-916, 1992 https://doi.org/10.1109/26.141456