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A Collision Avoidance System for Intelligent Ship using BK-products and COLREGs

BK곱과 COLREGs에 기반한 지능형 선박의 충돌회피시스템

  • 강성수 (진주산업대학교 컴퓨터공학부) ;
  • 이영일 (진주산업대학교 컴퓨터공학부) ;
  • 정희 (진주산업대학교 컴퓨터공학부) ;
  • 김용기 (경상대학교 컴퓨터학과)
  • Published : 2007.01.31

Abstract

This paper presents a collision avoidance system for intelligent ship. Unlike collision avoidance system of other unmanned vehicles, the collision avoidance system for intelligent ship aims at not only deriving a reasonable and safe path to the goal but also keeping COLRECs(International Regulations for Preventing Collisions at Sea). The heuristic search based on the BK-products is adopted to achieve the general purpose of collision avoidance system; deriving a reasonable and safe path. The rule of action to avoid collision is adopted for the other necessary and sufficient condition; keeping the COLREGs. The verification of proposed collision avoidance system is performed with scenarios that represent encounter situations classified in the COLREGs, then it is compared with $A^{\ast}$ search method in view of optimality and safety. The analysis of simulation result revels that the proposed collision avoidance system is practical and effective candidate for real-time collision avoidance system of intelligent ship.

본 논문에서는 지능형 선박의 실시간 장애물회피를 위한 충돌회피시스템을 논한다. 다른 무인자율항체들의 충돌회피시스템과는 달리 지능형 선박의 충돌회피시스템은 목적지까지의 합리적이고 안전한 경로를 통한 충돌회피뿐만 아니라 해양을 항해하는 모든 선박이 준수해야하는 국제해상충돌예방규칙(COLRECs, International Regulations for Preventing Collisions at Sea)을 반영해야한다. 목적지까지의 합리적이고 안전한 경로를 통한 충돌회피라는 일반적인 충돌회피시스템의 목표를 달성하기 위해 BK-곱에 기반한 휴리스틱 탐색기법을 채용하며, 또 다른 목표인 COLREGs의 준수를 위해 충돌회피를 위한 규칙을 적용하는 지식기반시스템을 채용한다. 제안된 충돌회피시스템의 성능검증을 위해 COLREGs에 명시된 여러 가지 조우상황을 설정한 시나리오를 이용하여 최적성과 안정성 관점에서 시뮬레이션을 수행하고 그 결과를 $A^{\ast}$ 탐색기법과 비교한다. 시뮬레이션을 통해 제안된 충돌회피시스템이 지능형 선박의 실용적이고 효율적인 실시간 충돌회피시스템으로 적합함을 확인하였다.

Keywords

References

  1. Samuelides, E. and Frieze. P., 'Experimental and Numerical Simulation of Ship Collisions,' Proc. 3rd Int. Congress on Marine Technology, Vol. 1, Greece, 1984
  2. 윤점동, 국제해상충돌예방규칙 및 관련된 국내법규해설, 세종출판, 서울,2000
  3. Koyama, T. and Yan,J., 'An Expert System Approach to Collision A voidance,' 8th Ship Control System Symposium, Hague, 1987
  4. Hasegawa, K., Kouzuki, A., Muramatsu, T., Komine, R. and Watabe, Y., 'Ship Auto-navigation Fuzzy Expert System (SAFES),' Journal of the Society of Naval Architecture of Japan, Vol. 166, 1989
  5. Zhao, J., Tan, M., Price, W. G., and Wilson, P. A., 'DCPA Simulation Model for Automatic Collision A voidance Decision Making Systems using Fuzzy Sets,' Proceedings of OCEANS'94, Vol. 2, pp. 244-249, 1994
  6. Yang, C., Phan, S., Kuo, P., and Lin, F, O., 'Applying Collision A voidance Expert System to Navigation Training System as an Intelligent Tutor,' LNCS, No. 2070, pp. 941-948, 2001
  7. Lee, H. J., and Rhee, K. P., 'Development of collision avoidance system by using expert system and search algorithm,' International shipbuilding progress, Vol. 48, No.3, pp. 197-212, 2001
  8. Irnazu, H. and Koyama, T., 'The Optimization of the Criterion for Collision Avoidance Action,' Journal of Japan Institute of Navigation, Vol. 71, 1984
  9. Lee, H. J., Yoo, W. J., and Rhee, K. P., 'Development of Collision Avoidance System by Fuzzy Theory,' The Second Japan-Korea Joint Workshop on Ship & Marine Hydrodynamic, Osaka, 1993
  10. Hong, X., Harris, C. J., and Wilson, P. A., 'Autonomous Ship Collision Free Trajectory Navigation and Control Algorithms,' Proceedings ETFA'99, Vol. 2, pp. 923-929, 1999
  11. Zeng,X. M., and Ito, M., 'Planning a Collision Avoidance Model for Ship using Genetic Algorithm,' Proceedings of IEEE International Conference on Systems, Man & Cybernetics, Vol. 4, pp. 2355-2360, 2001
  12. Harris, C. J., and Hong, X., 'Neurofuzzy Approaches to Intelligent Collision Avoidance Problems in (semi)Autonomous Transportation,' IFSA World Congress and 20th NAFIPS International Conference, Vol. 1, pp. 517-512. 2001
  13. Bandler, W., and Kohout, L. J., 'Fuzzy Relational Products as a Tool for Analysis and Synthesis of the Behaviour of Complex natural and Artificial System,' in: Wang, S. K, and Chang, P. P. eds., Fuzzy Sets: Theory and Application to Analysis and Information Systems, Plenum Press, New York, pp. 341-367, 1980
  14. Bandler, W., and Kohout, L. J., 'Semantics of Implication Operators and Fuzzy Relational Products,' Intl, Joumal of Man-Machine Studies, 1980
  15. Kohout, L. J., Keravnou, E., and Bandler, W., 'Automatic Documentary Information Retrieval by Means of Fuzzy Relational Products,' In Gaines, B. R., Zadeh, L. A. and Zimmermann, H. J., editors Fuzzy Sets in Decision Analysis, pp. 308-404, North-Holland, Amsterdam, 1984
  16. Bandler, W., and Kohout L. J., 'Fuzzy Power Sets and Fuzzy Implication Operator,' Fuzzy Set and System Vol. 4, pp. 13-30, 1980 https://doi.org/10.1016/0165-0114(80)90060-3
  17. Lozano-Perez, T., and Wesley, M. A., 'An Algorithm for Planning Collision Free Paths among Polyhedral Obstacles,' Communications, Vol. ACM-22(10), pp. 560-570, 1979
  18. Borenstein, J., and Koren, Y., 'Real-time Obstacle Avoidance for Fast Mobile Robots,' IEEE Transactions on System, Man, and Cybernetics, Vol. 19, Oct., 1989
  19. Borenstein, J., and Koren, Y., 'The Vector Field Histogram - Fast Obstacle Avoidance for Mobile Robots,' IEEE Journal of Robotics and Automation, 1991
  20. Borenstein, J., and Koren, Y., 'Real-Time Obstacle Avoidance for Fast Mobile Robots in Cluttered Environments,' IEEE Internatinoal Conference of Robotics and Automation, pp. 572-577. 1990
  21. Lee, Y. I. and Kim, Y. G., 'An Intelligent Collision Avoidance System for AUVs using Fuzzy Relational Products,' Information Sciences, Vol. 158, pp. 209-232, 2004 https://doi.org/10.1016/j.ins.2003.07.003