Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Global Path Planning of Mobile Robot Using String and Modified SOFM

스트링과 수정된 SOFM을 이용한 이동로봇의 전역 경로계획

  • 차영엽 (원광대학교 공과대학 기계자동차공학부)
  • Published : 2008.04.01
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Abstract

The self-organizing feature map(SOFM) among a number of neural network uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are moved toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors of the 1-dimensional string, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the opposite direction of input vector. According to simulation results one can conclude that the method using string and the modified neural network is useful tool to mobile robot for the global path planning.

Keywords

References

  1. Qunjie, D. and Mingjun, Z., "Local Path Planning Method for AUV Based on Fuzzy-neural Network," SHIP ENGINEERING, Vol. 1, pp. 54-58, 2001
  2. Cha, Y. Y., "Navigation of a free ranging mobile robot using heuristic local path planning algorithm," Robotics and Computer Integrated Manufacturing, Vol. 13, No. 2, pp. 145-156, 1997 https://doi.org/10.1016/S0736-5845(96)00037-3
  3. Zhu, Y., Chang, J. and Wang, S., "A new path-planning algorithm for mobile robot based on neural network," TENCOM Proceedings, IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering, Vol. 3, pp. 1570-1573, 2002
  4. Bourbakis, N. G., "Path Planning in a 2-D Known Space Using Neural Networks and Skeletonization," Conference proceedings : IEEE International Conference on Systems, Man and Cybernetics, Vol. 3, pp. 2001-2005, 1997
  5. Chaiyaratana, N. and Zalzala, A. M. S., "Time-Optimal Path Planning and Control using Neural Networks and a Genetic Algorithm," International Journal of Computational Intelligence and Applications, Vol. 2, No. 2, pp. 153-172, 2002 https://doi.org/10.1142/S1469026802000531
  6. Cha, Y. Y. and Gweon, D. G., "The development of a free ranging mobile robot equipped with a structured light range sensor," Intelligent Automation and Soft Computing, Vol. 4, No. 4, pp. 289-312, 1998 https://doi.org/10.1080/10798587.1998.10750739
  7. Cha, Y. Y. and Jeong, S. M., "Self-organizing Feature Map for Global Path Planning of Mobile Robot," Journal of the Korean Society for Precision Engineering, Vol. 23, No. 3, pp. 94-101, 2006
  8. Kohonen, T., "The self-organizing map," Proceedings of the Institute of Electrical and Electronics Engineers, Vol. 78, No. 9, pp. 1464-1480, 1990 https://doi.org/10.1109/5.58325