Swarm intelligence approach to safe ship control

• Autorzy: Lazarowska A.
• Języki publikacji: EN

Abstrakty

EN

This paper presents an application of the Ant Colony Optimization (ACO) technique in a safe ship control system. The method developed solves the problem of path planning and collision avoidance of a ship in the open sea as well as in restricted waters. The structure of the developed safe ship control system is introduced, followed by a presentation of the applied algorithm. Results showing the problem-solving capability of the system are also included. The aim of the system developed is to increase automation of a safe ship control process. It is possible to apply the proposed method in Unmanned Surface Vehicles (USVs) control system, what will contribute to the enhancement of their autonomy

• Wydawca: -
• Czasopismo: Polish Maritime Research
• Rocznik: 2015
• Tom: 22
• Numer: 4
• Opis fizyczny: p.34-40,fig.,,ref.

Twórcy

autor

Lazarowska A.

• Gdynia Maritime University, 11/12 Narutowicza St., 80-233 Gdansk, Poland

Bibliografia

• 1. Barbosa H.J.C.: Ant Colony Optimization - Techniques and Applications, InTech, 2013.
• 2. Beni G., Wang Jing: Theoretical problems for the realization of distributed robotic systems. IEEE International Conference on Robotics and Automation, 1991.
• 3. Bonabeau E., Dorigo M., Theraulaz G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, Inc., 1999.
• 4. Brand M., Masuda M., Wehner N. , Yu Xiao-Hua: Ant Colony Optimization Algorithm for Robot Path Planning, International Conference On Computer Design And Applications, 2010.
• 5. Chang Ki-Yin, Jan G. E., Parberry I.: A Method for Searching Optimal Routes with Collision Avoidance on Raster Charts. The Journal of Navigation, Vol. 56, 2003, p. 371–384.
• 6. Coldwell T.G.: Marine Traffic Behaviour in Restricted Waters. The Journal of Navigation, Vol. 36, 1983, p. 430–444. 
• 7. Davis P.V., Dove M. J., Stockel C. T.: A Computer Simulation of Marine Traffic Using Domains and Arenas. The Journal of Navigation, Vol. 33, 1980, p. 215–222. 
• 8. Dorigo M., Stützle T.: Ant Colony Optimization. The MIT Press, 2004.
• 9. Fujii Y., Tanaka K.: Traffic Capacity. The Journal of Navigation, Vol. 24, 1971, p. 543–552.
• 10. Goodwin E. M.: A Statistical Study of Ship Domains. The Journal of Navigation, Vol. 28, 1975, p. 328–344.
• 11. Ito M., Zeng Xiao-Ming: Planning a collision avoidance model for ship using genetic algorithm. IEEE International Conference on Systems, Man, and Cybernetics, 2001.
• 12. Jones K. D.: Application of a Manoeuvre Diagram to Multi-ship Encounters. The Journal of Navigation, Vol. 27, 1974, p. 19–27.
• 13. Kudriaszov V., Lisowski J.: Model of positional game applied for the synthesis of safe ship control. Archiwum Automatyki i Telemechaniki, Vol. 24, 1979, p. 483–497.
• 14. Lazarowska A.: Decision support system for collision avoidance at sea. Polish Maritime Research, Vol. 19, Issue S1 (74), 2012, p. 19–24.
• 15. Lisowski J.: Computational intelligence methods in the safe ship control process. Polish Maritime Research, Vol. 8, Issue 1, 2001, p. 18–24.
• 16. Lisowski J.: Comparison of dynamic games in application to safe ship control. Polish Maritime Research, Vol. 21, Issue 3, 2014, p. 3–12.
• 17. Olsder G. J., Walter J. L.: A differential game approach to collision avoidance of ships. Proceedings of the 8th IFIP Conference on Optimization Techniques, Würzburg, 1977.
• 18. Perera L. P., Carvalho J. P., Guedes Soares C.: Fuzzy logic based decision making system for collision avoidance of ocean navigation under critical collision conditions. Journal of Marine Science and Technology, Vol. 16, No.1, 2011, p. 84–99.
• 19. Pluciński M.: Application of the Ant Colony Algorithm for the Path Planning. Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems, 2005, p. 345–352.
• 20. Szłapczyński R.: A New Method of Ship Routing on Raster Grids, with Turn Penalties and Collision Avoidance. The Journal of Navigation, Vol. 59, 2006, p. 27–42.
• 21. Szłapczyński R.: Evolutionary approach to ship’s trajectory planning within Traffic Separation Schemes. Polish Maritime Research, Vol. 19, Issue 1, 2012, p. 11–20.
• 22. Śmierzchalski R., Michalewicz Z.: Modeling of Ship Trajectory in Collision Situations by an Evolutionary Algorithm. Transactions on Evolutionary Computation, Vol. 4, 2000, p. 227–241.
• 23. Tam Ch., Bucknall R.: Path-planning algorithm for ships in closerange encounters. Journal of Marine Science and Technology, Vol. 15, 2010, p. 395–407.
• 24. Tsou M.-Ch., Cheng H.-Ch.: An Ant Colony Algorithm for efficient ship routing. Polish Maritime Research, Vol. 20, Issue 3, 2013, p. 28–38.
• 25. Tsou M.-Ch., Hsueh Ch.-K.. The Study of Ship Collision Avoidance Route Planning by Ant Colony Algorithm. Journal of Marine Science and Technology - TAIWAN, Vol. 18, 2010, p. 746–756.

Identyfikatory

DOI

10.1515/pomr-2015-0068