International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Autonomous Navigation of an Underwater Robot in the Presence of Multiple Moving Obstacles

  • Kwon, Kyoung-Youb (Dept. of Control & Instrumentation Eng. Changwon National University) ;
  • Joh, Joong-Seon (Dept. of Control & Instrumentation Eng. Changwon National University)
  • Published : 2005.06.01
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Abstract

Obstacle avoidance of underwater robots based on a modified virtual force field algorithm is proposed in this paper. The VFF(Virtual Force Field) algorithm, which is widely used in the field of mobile robots, is modified for application to the obstacle avoidance of underwater robots. This Modified Virtual Force Field(MVFF) algorithm using the fuzzy lgoc can be used in moving obstacles avoidance. A fuzzy algorithm is devised to handle various situations which can be faced during autonomous navigation of underwater robots. The proposed obstacle avoidance algorithm has ability to handle multiple moving obstacles. Results of simulation show that the proposed algorithm can be efficiently applied to obstacle avoidance of the underwater robots.

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References

  1. Jeen-Shing Wang; Lee, C.S.G., 'Self-adaptive recurrent neuro-fuzzy control of an autonomous underwater vehicle Robotics and Automation', IEEE Transactions on,. 19, Issue. 2, pp. 283-295, April 2003
  2. Ishii, K., Nishida, S., Watanabe, K., Ura,T., 'A collision avoidance system based on self-organizing map and its application to an underwater vehicle Control', Automation, Robotics and Vision, 2002. ICARCV 2002. 7th International Conference on ,. 2 ,Dec. 2002 https://doi.org/10.1109/ICARCV.2002.1238492
  3. Sayyaadi, H., Ura, T., Fujii, T., 'Collision avoidance controller for AUV systems using stochastic real value reinforcement learning method', Proceedings of the 39th SICE Annual Conference. International Session Papers, pp.165-170, 26-28 July 2000 https://doi.org/10.1109/SICE.2000.889673
  4. Xuemin Liu, Liang Peng, Jiawei Li, Yuru Xu, 'Obstacle avoidance using fuzzy neural networks Underwater Technology', Proceedings of the 1998 International Symposium on ,pp. 282-286, 15-17 April 1998 https://doi.org/10.1109/UT.1998.670109
  5. A. A. Masoud and M. M. Bayoumi, 'Robot navigation using the vector potential approach', Proc. of IEEE international Conference on Robotics and Automation, vol. 1, pp. 805-811, 1993 https://doi.org/10.1109/ROBOT.1993.292076
  6. Kwang-Young Im, Se-Young Oh, 'An extended virtual force field based behavioral fusion with neural networks and evolutionary programming for mobile robot navigation',Evolutionary Computation, 2000, Proceedings of the 2000 Congress on,. 2 ,pp. 1238-1244, 16-19 July 2000 https://doi.org/10.1109/CEC.2000.870792
  7. Kwang-Young Im, Se-Young Oh, Seong-Joo Han, 'Evolving a modular neural network-based behavioral fusion using extended VFF and environment classification for mobile robot navigation Evolutionary Computation', IEEE Transactions on, 4, pp. 413-419, Aug. 2002
  8. J. Borenstein, 'Real-time obstacle avoidance for fast mobile robot', IEEE Transactions on Systems, Man and Cybernetics, Vol. 19, No. 5, pp. 117 9-1187, Sept./Oct., 1989
  9. Joongseon Joh, Kyung-Yup Kwon and Sang-Min Lee, 'Collision Avoiding Navigation of Marine Vehicles Using Fuzzy Logic', International Journal of Fuzzy Logic and Intelligent Systems, Vol. 2, No. 2, pp. 100-108, June 2002
  10. Donald P. Brutzman, 'A Virtual World for an Autonomous Underwater Vehicle', Dissertation, Naval Postgraduate school, Monterey California, 1994
  11. T . I. . Guidance and Control of Ocean Vehicles, John Wiley & Sons Ltd, Chichester, 1994
  12. A. J. Healey, and D. Lienard, 'Multivariable sliding mode control of autonomous diving and steering of underwater vehicles,' IEEE Journal of Ocean Engineering, OE-18, 3, pp.327-339, 1993