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

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

DOI QR Code

The Comparison of Pulled- and Pushed-SOFM in Single String for Global Path Planning

전역경로계획을 위한 단경로 스트링에서 당기기와 밀어내기 SOFM을 이용한 방법의 비교

  • 차영엽 (원광대학교 기계자동차공학부) ;
  • 김곤우 (원광대학교 전자및제어공학부)
  • Published : 2009.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper provides a comparison of global path planning method in single string by using pulled and pushed SOFM (Self-Organizing Feature Map) which is a method among a number of neural network. The self-organizing feature map 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 move toward the input vector. On the other hand, the modified SOFM method in this research uses a predetermined initial weight vectors of the one 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 or reverse the input vector, by rising a pulled- or a pushed-SOFM. According to simulation results one can conclude that the modified neural networks in single string are useful tool for the global path planning problem of a mobile robot. In comparison of the number of iteration for converging to the solution the pushed-SOFM is more useful than the pulled-SOFM in global path planning for mobile robot.

Keywords

References

  1. T. Lozano-Perez and M. A. Wesley, 'An algorithm for planning collision-free paths among polyhedrial obstacles,' Commun. ACM, pp. 560-570, 1979 https://doi.org/10.1145/359156.359164
  2. H. Noborio, T. Naniwa, and S. Arimoto, 'A fast path planning algorithm by synchronizing modification and search of its path-graph,' Proc. IEEE Intern. Workshop on Artificial intelligent for Industrial Application, pp. 351-357, 1988 https://doi.org/10.1109/AIIA.1988.13317
  3. R. Brooks, 'Solving the find path problems by good representation of free space,' IEEE Trans. Syst. Man Cybern., vol. SMC-13, no. 3, pp. 190-197, 1983
  4. M. D. Adams and P. J. Probert, 'Towards a real-time navigation strategy for a mobile robot,' Proc. of the IEEE Intern Workshop on Intelligent Robots and Systems, pp. 743-748, 1990 https://doi.org/10.1109/IROS.1990.262491
  5. J. Borenstein and Y. Koren, 'The vector field histogram-fast obstacle avoidance for mobile robots,' IEEE Trans. on Robotics and Automation, no. 3, pp. 278-298, 1991 https://doi.org/10.1109/70.88137
  6. D. Qunjie and Z. Mingjun, 'Local path planning method for AUV based on fuzzy-neural network,' SHIP ENGINEERING, vol. 1, pp. 54-58, 2001
  7. Y. Y. Cha, '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
  8. Y. Zhu, J. Chang, and S. Wang, 'A new path-planning algorithm for mobile robot based on neural network,' TENCOM '02. Proceedings. 2002 IEEE Region 10 Coriference on Computers, Communications, Control and Power Engineering, vol. 3, pp. 1570-1573, 2002
  9. N. G. Bourbakis, 'Path planning in a 2-D known space using neural networks and skeletonization,' Conference proceedings : IEEE International Coriference on Systems, Man, and Cybernetics, vol. 3, pp. 2001-2005, 1997 https://doi.org/10.1109/ICSMC.1997.635147
  10. N. Chaiyaratana and A. M. S. Zalzala, '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
  11. Y. Y. Cha and D. G. Gweon, '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
  12. T. Kohonen, '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
  13. Y. Y. Cha and H. G. Kang, 'A global path planning of mobile robot by using self-organizing feature map,' Journal of Control, Automation and Systems Engineering, vol. 11, no. 2, pp. 137-143, 2005
  14. Y. Y. Cha, D. W. Yu, and S. M. Jeong, 'A global path planning of mobile robot using modified SOFM,' Journal of Control, Automation and Systems Engineering, vol. 12, no. 5, pp. 473-479, 2005